CN109373525B - Control optimization method and device of air conditioning system, computer equipment and storage medium - Google Patents
Control optimization method and device of air conditioning system, computer equipment and storage medium Download PDFInfo
- Publication number
- CN109373525B CN109373525B CN201811339436.8A CN201811339436A CN109373525B CN 109373525 B CN109373525 B CN 109373525B CN 201811339436 A CN201811339436 A CN 201811339436A CN 109373525 B CN109373525 B CN 109373525B
- Authority
- CN
- China
- Prior art keywords
- time
- simulation
- energy consumption
- parameters
- model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004378 air conditioning Methods 0.000 title claims abstract description 189
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000005457 optimization Methods 0.000 title claims abstract description 28
- 238000004088 simulation Methods 0.000 claims abstract description 313
- 238000005265 energy consumption Methods 0.000 claims abstract description 234
- 238000004364 calculation method Methods 0.000 claims description 81
- 238000004590 computer program Methods 0.000 claims description 31
- 238000013178 mathematical model Methods 0.000 claims description 28
- 230000000007 visual effect Effects 0.000 claims description 14
- 238000000547 structure data Methods 0.000 claims description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 94
- 238000001816 cooling Methods 0.000 description 30
- 238000013461 design Methods 0.000 description 23
- 238000007710 freezing Methods 0.000 description 23
- 230000008014 freezing Effects 0.000 description 23
- 230000008569 process Effects 0.000 description 18
- 239000000498 cooling water Substances 0.000 description 16
- 239000007788 liquid Substances 0.000 description 14
- 230000007613 environmental effect Effects 0.000 description 10
- 238000009434 installation Methods 0.000 description 7
- 238000012886 linear function Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000005057 refrigeration Methods 0.000 description 3
- 238000012800 visualization Methods 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 2
- 238000004134 energy conservation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 238000009833 condensation Methods 0.000 description 1
- 230000005494 condensation Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000011545 laboratory measurement Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000010792 warming Methods 0.000 description 1
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/46—Improving electric energy efficiency or saving
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Signal Processing (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The application relates to an optimization control method and system of an air conditioning system, computer equipment and a storage medium. The method comprises the following steps: establishing an air conditioner simulation model, and acquiring a candidate control scheme; acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme; and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption. The method can solve the problem that the existing centralized air-conditioning system has a long debugging period when determining the energy-saving control scheme.
Description
Technical Field
The present disclosure relates to the field of energy saving control technology for air conditioning systems, and in particular, to a control optimization method and apparatus for an air conditioning system, a computer device, and a storage medium.
Background
A central air conditioning system is a so-called central air conditioner, in which all air processing equipment is centralized in an air conditioning room.
With global warming and increasingly prominent energy problems in China, energy conservation and emission reduction are imperative. The key point of reducing the energy consumption of the centralized air-conditioning system is to adopt an energy-saving control technology to control the centralized air-conditioning system.
However, the centralized air-conditioning system is composed of a large number of devices such as a refrigerating unit, a chilled water pump, a cooling tower and an air-conditioning box surface cooler, and is complex in structure.
Therefore, the existing centralized air-conditioning system has a problem of long debugging period when determining the energy-saving control scheme.
Disclosure of Invention
In view of the above, it is necessary to provide a control optimization method and apparatus for an air conditioning system, a computer device, and a storage medium, which can shorten the debugging period of an energy saving control scheme, in order to solve the above technical problems.
A method of control optimization for an air conditioning system, the method comprising:
establishing an air conditioner simulation model, and acquiring a candidate control scheme;
acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
In one embodiment, the obtaining the simulated operating energy consumption includes:
setting a starting time and an ending time;
acquiring the running environment of the starting time and acquiring the running environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity;
acquiring a simulation operation parameter of the starting time and acquiring a simulation operation parameter of the ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulating the operation of the air conditioner system under the operation environment according to the candidate control scheme;
generating the simulation operation energy consumption; and the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time.
In one embodiment, when a deep simulation request is received, the generating the simulation running energy consumption includes:
determining an intermediate time; the intermediate time is the time between the start time and the end time;
estimating an estimated operation environment of the intermediate time according to the operation environment of the starting time and the operation environment of the ending time;
estimating the estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the estimated operation environment of the intermediate time;
and calculating the simulation operation energy consumption by adopting the simulation operation parameters of the starting time, the simulation operation parameters of the ending time and the estimated operation parameters of the intermediate time.
In one embodiment, the intermediate time includes a previous time point and a next time point, and the estimating the estimated operating parameter of the intermediate time according to the simulated operating parameter of the starting time and the estimated operating environment of the intermediate time includes:
estimating the estimated operation parameters of the last time point according to the simulated operation parameters of the starting time and the estimated operation environment of the last time point;
and estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point.
In one embodiment, the generating the simulated operating energy consumption includes:
acquiring the simulated operation energy consumption of the starting time and acquiring the simulated operation energy consumption of the ending time; the simulation operation energy consumption of the starting time is generated according to the simulation operation parameters of the starting time; generating the simulation operation energy consumption of the end time according to the simulation operation parameters of the end time;
and accumulating the simulated operation energy consumption of the starting time and the simulated operation energy consumption of the ending time to obtain the simulated operation energy consumption.
In one embodiment, said calculating said simulated operating energy consumption using said simulated operating parameters of said start time, said simulated operating parameters of said end time and said estimated operating parameters of said intermediate time comprises:
extracting initial power from the simulated operation parameters of the initial time, extracting intermediate power from the estimated operation parameters of the intermediate time, and extracting end power from the simulated operation parameters of the end time;
and integrating the initial power, the intermediate power and the end power to obtain the simulated operation energy consumption.
In one embodiment, the creating of the air conditioner simulation model includes:
acquiring all-working-condition operation data of the air conditioning system;
fitting the full-working-condition operation data to obtain a semi-empirical mathematical model;
obtaining an equipment control model according to the semi-empirical mathematical model and a preset equipment control logic;
and acquiring a thermodynamic hydraulic parameter calculation model, and generating the air conditioner simulation model according to the equipment control model and the thermodynamic hydraulic parameter calculation model.
In one embodiment, the obtaining a thermodynamic and hydraulic parameter calculation model includes:
performing hydraulic iterative calculation on the air conditioning system to obtain hydraulic parameters of each time, and performing thermal iterative calculation on the air conditioning system to obtain thermal parameters of each time;
and obtaining the thermodynamic and hydraulic parameter calculation model according to the hydraulic parameters and the thermodynamic parameters.
In one embodiment, the creating an air conditioner simulation model further includes:
acquiring structural part data of the air conditioning system;
querying virtual reality characteristics of the structural part data;
constructing a virtual reality model of the air conditioning system; the virtual reality model includes virtual reality characteristics of the structure data;
and displaying the virtual reality model of the air conditioner simulation model.
In one embodiment, the method further comprises the following steps:
generating a visual energy consumption result of the simulation operation energy consumption;
displaying the visual energy consumption result; the visualized energy consumption result comprises at least one of a curve graph, a histogram, a three-dimensional surface graph and a three-dimensional grid graph.
A control optimization device for an air conditioning system, the device comprising:
the acquisition module is used for establishing an air conditioner simulation model and acquiring a candidate control scheme;
the simulation module is used for acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and the optimization module is used for determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
establishing an air conditioner simulation model, and acquiring a candidate control scheme;
acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
establishing an air conditioner simulation model, and acquiring a candidate control scheme;
acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
According to the technical scheme provided by the embodiment of the application, an air conditioner simulation model is established according to a design scheme of an air conditioner system preset by a designer, a plurality of candidate control schemes of the air conditioner system are preliminarily drawn up and input into the air conditioner simulation model, the air conditioner simulation model simulates the operation of the air conditioner system according to the candidate control schemes and calculates the simulation operation energy consumption, and finally the simulation operation energy consumption is sequenced to determine the energy-saving control scheme of the air conditioner system. Therefore, the control scheme of the centralized air-conditioning system does not need to be debugged on site, and the problem that the debugging period is long when the energy-saving control scheme is determined by the conventional centralized air-conditioning system is solved.
Drawings
FIG. 1 is a flow chart illustrating a method for optimizing control of an air conditioning system according to an embodiment;
FIG. 2 is a block diagram of a control optimization device of an air conditioning system according to an embodiment;
FIG. 3 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, there is provided a control optimization method of an air conditioning system, including the steps of:
step 110, establishing an air conditioner simulation model and obtaining a candidate control scheme.
The air conditioner simulation model may be a digital virtual model for simulating the operation of the air conditioner system, where the model is a generalized model, such as a mathematical model.
Wherein the air conditioning system may be a central air conditioning system.
The candidate control scheme may be various candidate schemes for controlling the operation of each device of the air conditioning system. For example, when the power of the water chiller unit is increased from 700kW (kilowatt) to 800kW at 12 pm, when the user adjusts the air-conditioning refrigerating temperature from 27 ℃ (centigrade) to 26 ℃, the air volume of the fan is increased by 4%, and the like.
In the specific implementation, designers preliminarily formulate air conditioning system design schemes according to customer requirements, and determine the types, installation positions and the like of various equipment models of the air conditioning system according to the air conditioning system design schemes. And establishing an air conditioner simulation model with a consistent design scheme according to the model type and the installation position of each device. Meanwhile, a designer preliminarily plans a plurality of candidate control schemes of the air conditioning system according to the design scheme of the air conditioning system, and inputs the candidate control schemes into an air conditioning simulation model. After the air conditioner simulation model acquires the candidate control scheme, the air conditioner simulation model simulates the process of performing energy-saving control on the air conditioner system by the candidate control scheme.
Step 120, acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme.
In the specific implementation, a designer preliminarily plans a plurality of candidate control schemes of the air conditioning system according to the design scheme of the air conditioning system, inputs the candidate control schemes into an air conditioning simulation model, and the air conditioning simulation model can sequentially simulate different candidate control schemes to control the air conditioning system, so as to simulate the operation conditions of different devices in the air conditioning system, such as the change process of the fan power along with time, the change process of the water cooling unit power along with time, and the like. And finally, calculating and acquiring the energy consumption generated when the air conditioning system operates according to the candidate control scheme according to the operating conditions of different devices. Because the energy consumption is obtained by the operation of the air conditioner simulation model, the energy consumption is named as simulation operation energy consumption.
In addition, the air conditioner simulation model can also perform more accurate simulation, improve the running condition running times of different equipment in the simulated air conditioning system, and accurately calculate and acquire the simulated running energy consumption generated when the air conditioning system runs according to the candidate control scheme according to a large amount of running condition data of the different equipment.
And step 130, determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulation operation energy consumption.
In specific implementation, when an air conditioning system on an actual site operates according to different candidate control schemes, energy consumption of different degrees is generated. Similarly, when the air conditioner simulation model is simulated according to different candidate control schemes, different simulation operation energy consumption can be calculated. When the simulation operation energy consumption is minimum, the situation that the air conditioning system in the actual field uses the candidate control scheme is shown, the lowest energy consumption can be generated, and the purpose of energy conservation is achieved. Therefore, the candidate control scheme is determined to be the energy saving control scheme.
In the technical scheme of the embodiment, an air conditioner simulation model is established according to a design scheme of an air conditioner system preset by a designer, a candidate control scheme which is preliminarily drawn up for a plurality of air conditioner systems is input into the air conditioner simulation model, the air conditioner simulation model simulates the operation of the air conditioner system according to the candidate control scheme and calculates the energy consumption of the simulation operation, and finally the energy consumption of the simulation operation is sequenced to determine the energy-saving control scheme of the air conditioner system. Therefore, the control scheme of the centralized air-conditioning system does not need to be debugged on site, and the problem that the debugging period is long when the energy-saving control scheme is determined by the conventional centralized air-conditioning system is solved.
In another embodiment, the obtaining the simulated operating energy consumption includes: setting a starting time and an ending time; acquiring the running environment of the starting time and acquiring the running environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity; acquiring a simulation operation parameter of a starting time and acquiring a simulation operation parameter of an ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulation air conditioning system in operation environment according to the candidate control scheme; generating simulation operation energy consumption; and the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time.
The building cold load can be used for maintaining the hot and humid environment of the building and the required indoor temperature, and the heat which must be taken away from a room by an air conditioning system comprises two parts, namely sensible heat and latent heat. In practical applications, a building model may be constructed in the building cooling load calculation software according to the design scheme of the air conditioning system, for example, a designer draws a room model of an actual site in the building cooling load calculation software. And then, performing simulation analysis on the building model by using building cold load calculation software to obtain the building cold load of the building model.
The ambient temperature and humidity may refer to at least one of an indoor temperature, an indoor humidity, an outdoor temperature, and an outdoor humidity. In practical application, a weather database with geographic positions mapped with historical weather data is established, the weather database is inquired according to the measured geographic position information of an actual site, and the environmental temperature and humidity of the actual site at different historical moments are obtained.
The simulation operation parameters may refer to equipment parameters of the air conditioner simulation model simulation air conditioning system in an operation environment and in an operation process according to the candidate control scheme, for example, fan frequency, fan power, chilled water pump frequency, chilled water pump power, chilled main pipe lift, chilled main pipe water supply temperature, chilled main pipe return water temperature, and the like.
In the concrete implementation, when a designer needs to simulate the operation of the air conditioning system according to a preset control scheme, the starting time and the ending time of the simulation are set. And then, obtaining the building cold load obtained by simulation analysis according to the actual site room model in the building cold load calculation software. Meanwhile, according to the geographical position of the actual site, the environmental temperature and humidity of the actual site at different times are obtained. And extracting the building cold load and the environment temperature and humidity corresponding to the starting time, and extracting the cold load and the environment temperature and humidity corresponding to the ending time. And then, calculating and acquiring simulation operation parameters corresponding to the starting time according to the building cold load and the environment temperature and humidity corresponding to the starting time, and calculating and acquiring simulation operation parameters corresponding to the ending time according to the building cold load and the environment temperature and humidity corresponding to the ending time. Further, according to the simulation operation parameters corresponding to the starting time and the simulation operation parameters corresponding to the ending time, the simulation operation energy consumption generated between the starting time and the ending time of the air conditioning system is calculated.
For example, when the designer needs to operate the simulated air conditioning system according to the control scheme established in advance, the starting time of the simulated operation is set to be 8, and the ending time of the simulated operation is set to be 9. Firstly, a room model of an actual site is constructed in building cold load calculation software according to a design scheme of an air conditioning system, and the room model is simulated by using the building cold load calculation software to obtain building cold loads from 8 hours to 9 hours, namely the building cold load from 8 hours and the building cold load from 9 hours. Secondly, a weather database with the geographic position mapped with historical weather data is established in advance, the weather database is inquired according to the measured geographic position information of the actual site, and the environmental temperature and humidity from 8 hours to 9 hours, namely the environmental temperature and humidity from 8 hours and the environmental temperature and humidity from 9 hours, of the actual site are obtained. And thirdly, simulating and calculating the operation parameters by the air conditioner simulation model when the air conditioner system operates in the corresponding operation environment according to the candidate control scheme. Specifically, the flow rate of the chilled water of the air conditioning equipment at 8 hours is calculated in a simulation mode according to the building cold load at 8 hours and the environment temperature and humidity at 8 hours. And calculating the frequency and power of the freezing water pump of the air conditioning equipment in 8 hours according to the head set value of the freezing main pipe and the flow of the freezing water. And then, according to the building cold load at the time of 9 and the environment temperature and humidity at the time of 9, simulating and calculating the chilled water flow of the air conditioning equipment at the time of 9. And calculating the frequency and power of the frozen water pump of the air-conditioning equipment at 9 hours according to the head set value and the frozen water flow of the freezing main pipe. And finally, obtaining the simulated operation energy consumption of the air conditioning system between the starting time 8 and the ending time 9 according to the frozen water pump power at 8 and the frozen water pump power at 9.
In addition, if the set starting time is 10 months and 01 days, and the set ending time is 10 months and 02 days, the method can be used for respectively and simulatively calculating the simulated operation energy consumption of the air-conditioning system in 24 time periods from 0 hour to 1 hour, from 1 hour to 2 hours, from … … hours, from 23 hours to 24 hours, and further obtaining the simulated operation energy consumption of the air-conditioning system from 10 months and 01 days to 10 months and 02 days, which is not described herein again.
In the technical scheme of the embodiment, the starting time and the ending time of the simulation calculation are set by obtaining; acquiring an operating environment between a starting time and an ending time; the air conditioner simulation model simulates the air conditioner system to perform simulation calculation to obtain simulation operation parameters of the starting time in the operation environment of the starting time according to the candidate control scheme; the air conditioner simulation model simulates the air conditioner system to perform simulation calculation to obtain simulation operation parameters of the ending time in the running environment of the ending time according to the candidate control scheme; and finally, calculating the simulation operation energy consumption generated by the air conditioning system from the start time to the end time according to the simulation operation parameters of the start time and the end time. In the whole simulation calculation process, the simulation operation parameters corresponding to the starting time are calculated only by using the operation environment corresponding to the starting time, and the simulation operation parameters corresponding to the ending time are calculated by using the operation environment corresponding to the ending time, so that the calculation steps are short, the data volume is small, and the simulation operation energy consumption of the air conditioning system in the set operation time period can be quickly simulated.
In another embodiment, generating the simulated operating energy consumption upon receiving the deep simulation request includes:
determining an intermediate time; the intermediate time is the time between the starting time and the ending time; estimating an estimated operation environment of the intermediate time according to the operation environment of the starting time and the operation environment of the ending time; estimating estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the estimated operation environment of the intermediate time; and calculating the simulation operation energy consumption by adopting the simulation operation parameters of the starting time, the simulation operation parameters of the ending time and the estimated operation parameters of the intermediate time.
The deep simulation request may refer to a request that a user needs to accurately simulate the running energy consumption.
The intermediate time may include more than one time point, and the number of the time points may be determined according to a time interval preset by a user. When the time interval preset by the user is smaller, the number of the time points is larger, and the simulation operation result is more accurate.
Most of building cold load calculation software carries out cold load calculation on a building model on an actual site, the precision level of obtained building cold load data is one hour, and simulation operation energy consumption obtained by simulating by using the building cold load of the hour level cannot meet deep simulation requests of users, so that the building cold load of the intermediate time needs to be estimated, and further, the air conditioning system can be subjected to more deep simulation calculation according to the known building cold load and the estimated building cold load of the intermediate time, and further, the simulation operation energy consumption meeting the requirements of the users is obtained.
In specific implementation, when a user needs to accurately simulate the request of running energy consumption, a deep simulation instruction is input. And when a deep simulation request is received, performing deep simulation calculation. Specifically, an intermediate time of the simulation calculation is determined between a start time of the simulation calculation and an end time of the simulation calculation. And then, obtaining the building cold load obtained by simulation analysis according to the actual site room model in the building cold load calculation software. Meanwhile, according to the geographical position of the actual site, the environmental temperature and humidity of the actual site at different times are obtained. And extracting the building cold load and the environment temperature and humidity corresponding to the starting time, and extracting the building cold load and the environment temperature and humidity corresponding to the ending time. And then, calculating the estimated building cold load of the intermediate time by using a linear interpolation mode according to the building cold load of the starting time and the building cold load of the ending time. Similarly, according to the environment temperature and humidity at the starting time and the environment temperature and humidity at the ending time, the estimated environment temperature and humidity at the intermediate time is calculated in a linear interpolation mode. Estimating estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the cold load and the environment temperature and humidity of the intermediate time; and finally, calculating the simulation operation energy consumption by adopting the simulation operation parameters of the starting time, the simulation operation parameters of the ending time and the estimated operation parameters of the intermediate time.
For example, when the designer needs to simulate the operation of the air conditioning system according to a predetermined control scheme, the set start time is 8, and the set end time is 9. An intermediate time, i.e. a preset time interval, is taken to be half an hour, so that the intermediate time is determined to be 8 hours and 30 minutes. Firstly, a room model of an actual site is constructed in building cold load calculation software according to a design scheme of an air conditioning system, the room model is simulated by using the building cold load calculation software, building cold loads from 8 hours to 9 hours, namely building cold loads from 860W (watt) at 8 hours and 900W at 9 hours are obtained, and a linear function of a time value and the building cold load is established according to the building cold loads from 860W at 8 hours and 900W at 9 hours, wherein the linear function is y which is 40x + 540: wherein y is the building cooling load and x is the time value. Since the intermediate time of 8 hours and 30 minutes is converted into the intermediate time value of 8.5, and then the intermediate time value of 8.5 is substituted into the linear function, y is 880, the building cooling load corresponding to 8 hours and 30 minutes is 880W. By using the same method, the environmental temperature and humidity of 30 minutes at 8 hours are calculated according to the environmental temperature and humidity from 8 hours to 9 hours, namely the environmental temperature and humidity at 8 hours and the environmental temperature and humidity at 9 hours.
Further, the flow rate of the chilled water of the air conditioning equipment at the time of 8 is calculated in a simulation mode according to the building cold load at the time of 8 and the environment temperature and humidity at the time of 8. And calculating the frequency and power of the freezing water pump of the air conditioning equipment in 8 hours according to the head set value of the freezing main pipe and the flow of the freezing water. And then, calculating the frozen water pump power of 30 minutes at 8 hours according to the frozen water pump power of 8 hours, the environment temperature and humidity of 30 minutes at 8 hours and the building cooling load corresponding to 30 minutes at 8 hours in a simulation mode, and calculating the chilled water flow of the air conditioning equipment at 9 hours according to the building cooling load at 9 hours and the environment temperature and humidity at 9 hours in a simulation mode. And calculating the frequency and power of the frozen water pump of the air-conditioning equipment at 9 hours according to the head set value and the frozen water flow of the freezing main pipe. And finally, obtaining the simulated operation energy consumption generated between the starting time and the ending time of the frozen water pump of the air conditioning system according to the frozen water pump power at 8 hours, the frozen water pump power at 8 hours and 30 minutes and the frozen water pump power at 9 hours.
In the technical solution of this embodiment, the intermediate time is determined between the start time and the end time; estimating the estimated operation environment of the intermediate time by using a linear interpolation method according to the operation environment of the starting time and the operation environment of the ending time; estimating the estimated running parameters of the intermediate time according to the simulated running parameters of the starting time and the estimated running environment of the intermediate time, and calculating the simulated running energy consumption by adopting the simulated running parameters of the starting time, the simulated running parameters of the ending time and the estimated running parameters of the intermediate time. Therefore, the air conditioner simulation model can simulate and calculate the operation parameters of each device of the air conditioner system according to more operation environments, and further improve the calculation accuracy of simulation operation energy consumption.
In another embodiment, the estimating the estimated operating parameters of the intermediate time according to the simulated operating parameters of the starting time and the estimated operating environment of the intermediate time includes: estimating the estimated operation parameters of the previous time point according to the simulated operation parameters of the starting time and the estimated operation environment of the previous time point; and estimating the estimated operation parameters of the next time point according to the estimated operation parameters of the previous time point and the estimated operation environment of the next time point.
The designer can shorten the time interval to increase the number of the intermediate time, and the simulation operation times of the air conditioner simulation model is improved, so that the air conditioner simulation model can better accord with the actual operation process of the air conditioner system when the air conditioner system is simulated.
The actual operation process refers to a project in which the centralized air-conditioning control system controls various devices by using an incremental PID (proportional integral differential) control method in an actual project. The incremental PID control method is a basic form of a digital PID control algorithm, and is a control algorithm for PID control of an increment of a controlled variable (a difference between a current controlled variable and a last controlled variable). Therefore, in practical application, a designer can set the time interval to be smaller than the control period of the air conditioning control system, so that the air conditioning simulation model can better conform to the actual operation process of the air conditioning system when the air conditioning system is simulated.
In the concrete reality, the middle time has a plurality of time points, two adjacent time points in the middle time are taken as a previous time point and a next time point, and estimated operation parameters of the previous time point are estimated according to simulated operation parameters of the starting time and estimated operation environment of the previous time point; estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point; and after the estimation of the estimated operation parameter of the next time point is finished, taking the estimated operation parameter of the time point as the estimated operation parameter of the previous time point, and estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point. The above process is continuously executed circularly until the estimated operation parameters of all time points are estimated in a simulation mode.
For example, when the designer needs to operate the simulated air conditioning system according to the control scheme established in advance, the starting time of the simulated operation is set to be 8, and the ending time of the simulated operation is set to be 9. First, the designer may set the time interval to 10s (seconds) to ensure that the time interval is less than the control period of the climate control system, and then determine 359 points of time with intermediate times of 8 hours, 0 minutes, 10 seconds, … …, and 8 hours, 59 minutes, 50 seconds. Then, by simulating a preset building model using building cold load calculation software, building cold loads from 8 hours to 9 hours, that is, a building cold load at 8 hours and a building cold load at 9 hours, are obtained. A linear function of the duration and the building cooling load is established based on the building cooling load at 8 and the building cooling load at 9. Then, the 359 time points of the building cooling load are estimated according to the linear function of the time value and the building cooling load.
Further, according to the building cold load of 8 hours, 0 minutes and 0 seconds, the head data of the freezing main pipe and the power of the freezing water pump of the air conditioning equipment at 8 hours, 0 minutes and 0 seconds are obtained through simulation calculation. And according to the building cold load of 8 hours, 0 minute and 10 seconds and the freezing main pipe head data of 8 hours, 0 minute and 0 second, the freezing main pipe head data of 8 hours, 0 minute and 10 seconds and the freezing water pump power of the air-conditioning equipment are obtained through simulation calculation. And (4) according to the building cold load of 8 hours, 0 minute and 20 seconds and the refrigeration main pipe head data of 8 hours, 0 minute and 10 seconds, performing simulation calculation to obtain the refrigeration main pipe head data of 8 hours, 0 minute and 20 seconds and the refrigeration water pump power of the air-conditioning equipment. The process is continuously and circularly executed until the 359 times of the data of the head of the freezing main pipe and the power of the freezing water pump at all the times are estimated through simulation. And finally, calculating to obtain the simulated operation energy consumption generated between the starting time and the ending time of the frozen water pump of the air conditioning system according to the frozen water pump power of 8 hours, 0 minute and 0 second, the frozen water pump power of all the intermediate time points and the frozen water pump power of 9 hours.
In addition, the curves of the estimated operation parameters at the 359 time points can be drawn, the curves are displayed on a display, and a designer finely adjusts the control scheme of the air conditioning system by observing the variation trend of the curves.
In the technical scheme of the embodiment, the estimated operation parameter of the last time point is estimated according to the simulated operation parameter of the starting time and the estimated operation environment of the last time point; estimating the estimated operation parameters of the next time point according to the estimated operation parameters of the previous time point and the estimated operation environment of the next time point, and continuously iterating and circulating the processes, so that the process of simulating the operation of the air conditioning system is more consistent with the actual operation process, and more accurate simulated operation energy consumption is obtained. Meanwhile, because the period of each simulation calculation is equivalent to the minimum period of the system controller, a user can observe the stability of the control scheme through simulation operation parameters obtained by simulation operation, and further the reliability of the energy-saving control scheme of the centralized air-conditioning system is improved.
In another embodiment, the generating the simulated operating energy consumption comprises: acquiring the simulation running energy consumption of the starting time and acquiring the simulation running energy consumption of the ending time; generating simulation operation energy consumption of the starting time according to the simulation operation parameters of the starting time; generating simulation operation energy consumption of the end time according to the simulation operation parameters of the end time; and accumulating the simulated operation energy consumption of the starting time and the simulated operation energy consumption of the ending time to obtain the simulated operation energy consumption.
The simulation operation energy consumption of the starting time may refer to simulation operation energy consumption generated by simulating the operation of the air conditioning system in the first half of the simulation time. The simulation operation energy consumption of the end time may refer to simulation operation energy consumption generated by simulating the operation of the air conditioning system in the lower half of the simulation time.
In the specific implementation, firstly, the simulation operation parameters of the starting time are obtained, the equipment power parameters are extracted from the simulation operation parameters of the starting time, and the simulation operation energy consumption of the starting time, namely the simulation operation energy consumption generated in the last half of the simulation time of the air conditioning system, is calculated. And then acquiring the simulation operation parameters of the end time, extracting the equipment power parameters from the simulation operation parameters of the end time, and calculating the simulation operation energy consumption of the end time, namely the simulation operation energy consumption of the air conditioning system generated in the next half of simulation time. And adding the simulation operation energy consumption generated in the upper half period of simulation time and the simulation operation energy consumption generated in the lower half period of simulation time to obtain the simulation operation energy consumption generated from the starting time to the ending time of the air-conditioning system.
For example, the air conditioner simulation model is subjected to simulation calculation, the power of the chilled water pump at 8 hours is 800W, the power of the chilled water pump at 9 hours is 850W, and the simulation operation time is 1 hour. Therefore, the simulated operation energy consumption of 8 hours is the operation energy consumption of half an hour before the chilled water pump, and the operation energy consumption of half an hour before the chilled water pump is calculated to be 400 W.h (watt hour). And the simulated operation energy consumption of 9 hours is the operation power consumption of the chilled water pump for half an hour, the operation power consumption of the chilled water pump for half an hour is calculated to be 425 W.h, and the simulated operation energy consumption of 8 hours and the simulated operation energy consumption of 9 hours are accumulated to obtain the simulated operation energy consumption 825 W.h generated from the starting time to the ending time of the air conditioning equipment.
In the technical scheme of this embodiment, the simulated operation energy consumption generated by the start time device and the simulated operation energy consumption generated by the end time device are roughly estimated according to the simulated operation parameters of the start time and the simulated operation parameters of the end time, and then the simulated operation energy consumption generated by the start time device and the simulated operation energy consumption generated by the end time device are accumulated, so that the data calculation amount is reduced, and the speed of calculating the simulated operation energy consumption of the air conditioning system is increased.
In another embodiment, the calculating the simulated operation energy consumption by using the simulated operation parameters of the start time, the simulated operation parameters of the end time and the estimated operation parameters of the intermediate time includes: extracting initial power from the simulated operation parameters of the initial time, extracting intermediate power from the estimated operation parameters of the intermediate time, and extracting end power from the simulated operation parameters of the end time; and integrating the initial power, the intermediate power and the end power to obtain the simulated operation energy consumption.
In the specific implementation, the starting power is extracted from the simulated operation parameters of the starting time, the intermediate power is extracted from the estimated operation parameters of the intermediate time, and the ending power is extracted from the simulated operation parameters of the ending time; establishing a rectangular coordinate system with a horizontal axis representing time and a vertical axis representing equipment power, and drawing a two-dimensional curve of all the power changing along with time; and integrating the two-dimensional curve to obtain an integral value. The integral value is the simulated operation energy consumption generated by the operation of the air conditioning equipment from the starting time to the ending time.
For example, it is known that the set period of the simulation operation is 8 hours to 9 hours on 10 months and 01 days. First, the time interval was set to 10s, and 359 time points were determined with intermediate times of 8 hours, 0 minutes, 10 seconds, … …, and 8 hours, 59 minutes, 50 seconds. And obtaining the fan operation parameters of the starting time, the fan operation parameters of the intermediate time and the fan operation parameters of the ending time through simulation operation. And extracting fan power data of the starting time, fan power data corresponding to the intermediate time and fan power data of the ending time from the fan operation parameters. Next, a rectangular coordinate system is established in which the horizontal axis represents time and the vertical axis represents the power of the device. And drawing a two-dimensional curve of the change of the fan power along with time in the rectangular coordinate system. And integrating the two-dimensional curve to obtain an integral value, namely the simulated operation energy consumption generated when the fan operates from the starting time to the ending time.
In the technical scheme of the embodiment, the air conditioner simulation model simulates the operation of the air conditioner system to obtain simulation operation parameters. Extracting simulation power corresponding to different time points from simulation operation parameters, and drawing a two-dimensional curve of the power changing along with time; and integrating the two-dimensional curve to obtain an integral value, so that the simulated operation energy consumption of the air conditioning system can be accurately obtained according to the integral value.
In another embodiment, the creating of the air conditioner simulation model includes: acquiring all-condition operation data of an air conditioning system; fitting the full-working-condition operation data to obtain a semi-empirical mathematical model; obtaining an equipment control model according to the semi-empirical mathematical model and a preset equipment control logic; and acquiring a thermodynamic and hydraulic parameter calculation model, and generating an air conditioner simulation model according to the equipment control model and the thermodynamic and hydraulic parameter calculation model.
The full-working-condition operation data can be all the equipment operation data generated by the equipment operating under the normal use condition and the conditions of temperature, humidity, dirt, condensation and the like exceeding the requirements of normal use.
The full-working-condition operation data of the air conditioning system can refer to full-working-condition operation data of each device in the air conditioning system, such as full-working-condition operation data of a water chilling unit, full-working-condition operation data of a water pump, full-working-condition operation data of a cooling tower, full-working-condition operation data of a valve, full-working-condition operation data of a cold water pipeline and full-working-condition operation data of a pipe fitting. In practical application, the full-working-condition operation data of the air conditioning system can be acquired through measurement and calculation in a laboratory or through an actual operation field.
The semi-empirical mathematical model may be a model obtained by modifying a model based on theory by adding experimental data and determining parameters of the model.
The device control logic may refer to an air conditioning device control logic commonly used in an actual operation site.
The thermodynamic and hydraulic parameter calculation model may be a model for calculating an air-conditioning freezing side hydraulic parameter, a cooling side hydraulic parameter, a freezing side hydraulic parameter, and a cooling side hydraulic parameter corresponding to time.
In the concrete implementation, firstly, the full-working-condition operation data of equipment such as a water chilling unit, a water pump, cooling equipment, a tower valve, a cold water pipeline and the like in an air conditioning system is obtained through laboratory measurement and calculation or actual operation field acquisition; then, fitting the full-working-condition operation data of each device to obtain a semi-empirical mathematical model of each device; obtaining an equipment control model according to the semi-empirical mathematical model of each equipment and preset equipment control logic; and acquiring a pre-constructed thermodynamic and hydraulic parameter calculation model, and generating an air conditioner simulation model according with the actual operation process of the air conditioning system according to the equipment control model and the thermodynamic and hydraulic parameter calculation model.
For example, a large amount of full-working-condition operation data of the water chilling unit is acquired in a laboratory or an actual operation field, and the full-working-condition operation data of the water chilling unit is fitted to obtain a semi-empirical mathematical model of the water chilling unit; acquiring a large amount of water pump set full-working-condition operation data through collection in a laboratory or an actual operation field, and fitting the water pump full-working-condition operation data to obtain a water pump semi-empirical mathematical model; acquiring a large amount of cooling tower full-working-condition operation data in a laboratory or an actual operation field, and fitting the cooling tower full-working-condition operation data to obtain a cooling tower semi-empirical mathematical model; acquiring a large amount of valve full-working-condition operation data in a laboratory or an actual operation field, and fitting the valve full-working-condition operation data to obtain a valve semi-empirical mathematical model; acquiring a large amount of full-working-condition operation data of the cold water pipeline and the pipe fitting in a laboratory or an actual operation field, and fitting the full-working-condition operation data of the cold water pipeline and the pipe fitting to obtain a semi-empirical mathematical model of the cold water pipeline and the pipe fitting; and setting equipment control logic through control logic of mature water chilling units and group control products.
Further, an object-oriented programming method is used for establishing an equipment control model according to a semi-empirical mathematical model of the water chilling unit, a semi-empirical mathematical model of the water pump, a semi-empirical mathematical model of the cooling tower, a semi-empirical mathematical model of the valve, a semi-empirical mathematical model of the cold water pipeline and the pipe fitting and preset control logic. And acquiring a pre-established thermodynamic and hydraulic parameter calculation model, and generating an air conditioner simulation model according with the actual operation process of the air conditioning system according to the equipment control model and the thermodynamic and hydraulic parameter calculation model.
In the technical scheme of the embodiment, full-working-condition operation data of equipment such as a water chilling unit, a water pump, cooling, a tower valve, a cold water pipeline and the like in an air conditioning system is acquired through a laboratory or an actual operation field, and the full-working-condition operation data of the equipment is subjected to mathematical modeling to obtain a full-working-condition operation data semi-empirical mathematical model; and combining the full-working-condition operation data semi-empirical mathematical model with a control logic algorithm of the equipment to obtain an equipment control model. Finally, generating an air conditioner simulation model according to the equipment control model and the thermodynamic and hydraulic parameter calculation model; the air conditioner simulation model is constructed completely based on the full-working-condition operation data of different equipment when the air conditioner system operates in an actual field, the air conditioner simulation model which accords with the actual operation process of the air conditioner system is generated, the air conditioner simulation model simulates the operation of the air conditioner system to obtain accurate simulation operation energy consumption, and the reliability of the air conditioner simulation model for simulating the operation of the air conditioner system is improved.
In another embodiment, the obtaining the thermodynamic and hydraulic parameter calculation model includes: performing hydraulic iterative calculation on the air conditioning system to obtain hydraulic parameters of each time, and performing thermal iterative calculation on the air conditioning system to obtain thermal parameters of each time; and obtaining a thermodynamic and hydraulic parameter calculation model according to the hydraulic parameters and the thermodynamic parameters.
Here, each time may refer to each time, for example, every hour, every minute, every second, or the like.
The hydraulic parameter may refer to a flow parameter of liquid in each pipeline in the air conditioning system, for example, a flow rate of chilled water in a freezing-side pipeline, a flow rate of cooling water in a cooling-side pipeline, and the like.
The thermal parameter may be a temperature parameter of liquid in pipelines of different devices in the air conditioning system, for example, a return water temperature of chilled water in the chilled side pipeline, an outlet water temperature of cooling water in the cooling side pipeline, and a return water temperature of cooling water in the cooling side pipeline
The iterative computation refers to a computation method for recurrently deriving a new value by using an old value of a variable.
In the concrete implementation, the hydraulic parameters of the liquid in each pipeline in the air-conditioning system are obtained by measuring the air-conditioning system which actually operates on site, iterative calculation is carried out on the hydraulic parameters of the liquid in each pipeline to obtain the hydraulic parameters which correspond to each time one by one, meanwhile, the air-conditioning system which actually operates on site is measured to obtain the thermodynamic parameters of the liquid in each pipeline in the air-conditioning system, iterative calculation is carried out on the thermodynamic parameters of the liquid in each pipeline to obtain the thermodynamic parameters which correspond to each time one by one. And finally, establishing a thermodynamic and hydraulic parameter calculation model by using an object-oriented programming method according to the one-to-one correspondence of each moment to the hydraulic parameters and the one-to-one correspondence of each moment to the thermodynamic parameters. The thermodynamic and hydraulic parameter calculation model can calculate hydraulic parameters of liquid in each pipeline and thermodynamic parameters of liquid in each pipeline corresponding to time.
For example, iterative calculation is performed on the initial flow of the chilled water in the freezing side pipeline to obtain the flow of the chilled water at each moment; performing iterative calculation on the initial flow of the cooling water in the cooling side pipeline to obtain the flow of the cooling water at each moment; performing iterative calculation on the initial return water temperature of the chilled water in the freezing side pipeline to obtain the return water temperature of the chilled water at each moment; performing iterative calculation on the initial outlet water temperature of the chilled water in the freezing side pipeline to obtain the outlet water temperature of the chilled water at each moment; performing iterative calculation on the initial return water temperature of the cooling water in the cooling side pipeline to obtain the return water temperature of the cooling water at each moment; performing iterative calculation on the initial outlet water temperature of the cooling water in the cooling side pipeline to obtain the outlet water temperature of the cooling water at each moment; storing the chilled water flow, the cooling water flow, the chilled water return temperature, the chilled water outlet temperature, the cooling water return temperature and the cooling water outlet temperature of each moment as the operating parameters of each moment of the air conditioning system; and establishing a thermodynamic and hydraulic parameter calculation model by using an object-oriented programming method according to the operation parameters of the air conditioning system at each moment. The thermodynamic and hydraulic parameter calculation model can perform calculation according to the input time value, and calculate the operation parameters such as the freezing water flow, the cooling water flow, the freezing water return water temperature, the freezing water outlet water temperature, the cooling water return water temperature and the cooling water outlet water temperature corresponding to the time value.
In the technical scheme of the embodiment, the hydraulic parameters in each measured pipeline are subjected to hydraulic iterative calculation to obtain the hydraulic parameters corresponding to each moment one by one, and the thermal parameters in each measured pipeline are subjected to thermal iterative calculation to obtain the thermal parameters corresponding to each moment one by one; according to the large amount of hydraulic parameters and thermal parameters, the thermal hydraulic parameter calculation model is obtained by using an object-oriented programming method, so that the thermal hydraulic parameter calculation model can calculate the hydraulic parameters of the liquid in each pipeline and the thermal parameters of the liquid in each pipeline corresponding to time, and meanwhile, the hydraulic parameters of the liquid in each pipeline and the thermal parameters of the liquid in each pipeline which are obtained by calculation are ensured to accord with the hydraulic parameters of the liquid in each pipeline and the thermal parameters of the liquid in each pipeline which are measured by the actual operation of the air-conditioning system, and the reliability of the air-conditioning simulation model for simulating the operation of the air-conditioning system is further improved.
In another embodiment, the creating of the air conditioner simulation model further includes:
acquiring structural part data of an air conditioning system; querying virtual reality characteristics of the structural part data; constructing a virtual reality model of the air conditioning system; the virtual reality model includes virtual reality characteristics of the structure data; and displaying the virtual reality model of the air conditioner simulation model.
The structural component data may refer to model data of each device in the air conditioning system. For example, the type of cooling pump, the type of cold water pump, the type of blower, the type of valve, the type of pipe fitting, and the like.
The virtual reality features can refer to virtual shape features of each device in the air conditioning system in a computer interface.
In specific implementation, a structural member database is established according to structural member data of each device of the air conditioning system; a designer inquires the virtual reality characteristics of each device in a structural member database according to a device list in an air conditioning system design scheme; then, a designer constructs a virtual reality model of the air conditioning system according to an equipment installation scheme in the design scheme of the air conditioning system; and finally, displaying the virtual reality model of the air conditioner simulation model on a display.
For example, a designer obtains the model of a cooling pump, the model of a cold water pump, the model of a fan, the model of a valve, the model of a pipeline and the model of a pipe fitting in an air conditioning system according to an equipment list in an air conditioning system design scheme, and then queries virtual reality characteristics corresponding to the equipment models from a structural part database. A designer builds a virtual reality model consistent with a design scheme according to an equipment installation scheme in an air conditioning system design scheme and a pre-modeled customer room model; more specifically, a designer selects a proper cooling pump model, a proper cooling water pump model, a proper fan model, a proper valve model, a proper pipeline model and a proper pipe fitting model according to an equipment list in an air conditioning system design scheme, and builds a virtual reality model completely consistent with the air conditioning system design scheme according to an equipment installation drawing in a centralized air conditioning design scheme. Meanwhile, the built air conditioning system virtual reality model can be displayed by the display.
In the technical scheme of the embodiment, a virtual reality model consistent with the design scheme is built by a designer according to the equipment installation scheme in the design scheme of the air-conditioning system and a pre-modeled customer room model, and the design scheme of the air-conditioning system is converted into a more visual and intuitive virtual reality model, so that the designer can conveniently determine whether the equipment type selection and the installation position are reasonable, and the design scheme of the centralized air conditioner is pertinently adjusted and improved.
In another embodiment, the method further comprises: generating a visual energy consumption result of the simulation operation energy consumption; displaying a visual energy consumption result; the visualized energy consumption result comprises at least one of a graph, a histogram, a three-dimensional surface graph and a three-dimensional grid graph.
In the concrete implementation, after the air conditioner simulation model finishes simulating the operation of the air conditioner system according to different candidate control schemes, the obtained simulation operation energy consumption is calculated, the obtained simulation operation energy consumption is converted into a visual energy consumption result, for example, the horizontal axis represents the candidate schemes, the vertical axis represents an energy consumption histogram of the simulation operation energy consumption, and finally the energy consumption histogram is displayed on a display. In addition, the visualized energy consumption result can also be a curve graph, a three-dimensional surface graph, a three-dimensional grid graph and the like.
For example, first, a designer has previously made ten candidate control schemes according to the design scheme of the air conditioning system. And then, sequentially simulating the operation of the air conditioning system according to the ten candidate control schemes by the air conditioning simulation model, and calculating ten simulation operation energy consumptions. Then, drawing an energy consumption histogram with a horizontal axis representing the candidate scheme and a vertical axis representing the simulated operation energy consumption, wherein the lower the height of the stripe in the operation energy consumption histogram is, the lower the simulated operation energy consumption corresponding to the stripe is, and further, the lower energy consumption is generated when the air conditioning system operates according to the candidate control scheme corresponding to the stripe, so that the candidate control scheme can enable the air conditioning system to save energy consumption compared with other candidate control schemes.
In the technical solution of this embodiment, the simulated operation energy consumption corresponding to the candidate control scheme is converted into a visualized energy consumption result, for example, a histogram. And the visual energy consumption result is displayed to the user on the display, so that the user can more visually observe the simulated operation energy consumption of the air conditioning system according to different candidate control schemes, and the user can conveniently and quickly select the candidate control schemes.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 2, there is provided a control optimization apparatus of an air conditioning system, including: an acquisition module 210, a simulation module 220, and an optimization module 230, wherein:
an obtaining module 210, configured to establish an air conditioner simulation model and obtain a candidate control scheme;
the simulation module 220 is used for acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and an optimizing module 230, configured to determine, according to the simulated operation energy consumption, that the candidate control scheme of the air conditioning system is an energy saving control scheme.
In one embodiment, the simulation module 220 in the control optimization apparatus of the air conditioning system includes: the energy consumption control system comprises a time setting submodule, an operating environment obtaining submodule, an operating parameter obtaining submodule and an energy consumption generating submodule, wherein:
the time setting submodule is used for setting the starting time and the ending time; the operation environment acquisition submodule is used for acquiring the operation environment of the starting time and the operation environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity; the operation parameter acquisition sub-module is used for acquiring the simulation operation parameters of the starting time and acquiring the simulation operation parameters of the ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulating the operation of the air conditioner system under the operation environment according to the candidate control scheme; the energy consumption generation submodule is used for generating the simulation operation energy consumption; and the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time.
In an embodiment, the simulation module 220 in the control optimization apparatus of an air conditioning system further includes: the energy consumption calculating system comprises an intermediate time determining submodule, an operating environment estimating submodule, an operating parameter estimating submodule and an energy consumption calculating submodule, wherein:
the middle time determining submodule is used for determining the middle time; the intermediate time is the time between the start time and the end time; the running environment estimation submodule is used for estimating the estimated running environment of the intermediate time according to the running environment of the starting time and the running environment of the ending time; the operation parameter estimation submodule is used for estimating the estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the estimated operation environment of the intermediate time; and the energy consumption calculation submodule is used for calculating the simulated operation energy consumption by adopting the simulated operation parameters of the starting time, the simulated operation parameters of the ending time and the estimated operation parameters of the intermediate time.
In one embodiment, the operating parameter estimation sub-module in the control optimization device of the air conditioning system includes: a first parameter estimation unit and a second parameter estimation unit, wherein:
the first parameter estimation unit is used for estimating the estimated operation parameter of the previous time point according to the simulated operation parameter of the starting time and the estimated operation environment of the previous time point; and the second parameter estimation unit is used for estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point.
In one embodiment, the energy consumption generation submodule in the control optimization device of the air conditioning system includes: an operating energy consumption acquisition unit and an accumulation unit, wherein:
the operation energy consumption obtaining unit is used for obtaining the simulation operation energy consumption of the starting time and obtaining the simulation operation energy consumption of the ending time; the simulation operation energy consumption of the starting time is generated according to the simulation operation parameters of the starting time; generating the simulation operation energy consumption of the end time according to the simulation operation parameters of the end time; and the accumulation unit is used for accumulating the simulation operation energy consumption of the starting time and the simulation operation energy consumption of the ending time to obtain the simulation operation energy consumption.
In one embodiment, the energy consumption calculation submodule in the control optimization device of the air conditioning system includes: an extraction unit and an integration unit, wherein:
the extracting unit is used for extracting starting power from the simulated operation parameters of the starting time, extracting intermediate power from the estimated operation parameters of the intermediate time and extracting ending power from the simulated operation parameters of the ending time; and the integration unit is used for integrating the starting power, the intermediate power and the ending power to obtain the simulation operation energy consumption.
In an embodiment, the obtaining module 210 in the control optimization apparatus of an air conditioning system includes: the system comprises an operation data obtaining submodule, a fitting submodule, a first model obtaining submodule and a second model obtaining submodule, wherein:
the operation data acquisition sub-module is used for acquiring all-working-condition operation data of the air conditioning system; the fitting submodule is used for fitting the full-working-condition operation data to obtain a semi-empirical mathematical model; the first model acquisition submodule is used for acquiring an equipment control model according to the semi-empirical mathematical model and preset equipment control logic; and the second model acquisition submodule is used for acquiring a thermodynamic and hydraulic parameter calculation model and generating the air conditioner simulation model according to the equipment control model and the thermodynamic and hydraulic parameter calculation model.
In one embodiment, the second model obtaining sub-module in the control optimization device of the air conditioning system includes: an iterative computation unit and a computation model acquisition unit, wherein:
the iterative calculation unit is used for performing hydraulic iterative calculation on the air conditioning system to obtain hydraulic parameters of each time, and performing thermal iterative calculation on the air conditioning system to obtain thermal parameters of each time; and the calculation model obtaining unit is used for obtaining the thermodynamic and hydraulic parameter calculation model according to the hydraulic parameters and the thermodynamic parameters.
In an embodiment, the obtaining module 210 in the control optimization apparatus of an air conditioning system further includes: the device comprises a data acquisition sub-module, a query sub-module, a model construction sub-module and a display sub-module, wherein:
the data acquisition submodule is used for acquiring structural part data of the air conditioning system; the query submodule is used for querying the virtual reality characteristics of the structural part data; the model building submodule is used for building a virtual reality model of the air conditioning system; the virtual reality model includes virtual reality characteristics of the structure data; and the display submodule is used for displaying the virtual reality model of the air conditioner simulation model.
In an embodiment, the above control optimization device for an air conditioning system further includes: visualization module and display module, wherein:
the visualization module is used for generating a visualization energy consumption result of the simulation operation energy consumption; the display module is used for displaying the visual energy consumption result; the visualized energy consumption result comprises at least one of a curve graph, a histogram, a three-dimensional surface graph and a three-dimensional grid graph.
For specific limitations of the control optimization device of the air conditioning system, reference may be made to the above limitations of the control optimization method of the air conditioning system, which are not described herein again. The various modules in the control optimization device of the air conditioning system can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 3. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a control optimization method for an air conditioning system. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
establishing an air conditioner simulation model, and acquiring a candidate control scheme;
acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
setting a starting time and an ending time; acquiring the running environment of the starting time and acquiring the running environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity; acquiring a simulation operation parameter of the starting time and acquiring a simulation operation parameter of the ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulating the operation of the air conditioner system under the operation environment according to the candidate control scheme; generating the simulation operation energy consumption; and the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
determining an intermediate time; the intermediate time is the time between the start time and the end time; estimating an estimated operation environment of the intermediate time according to the operation environment of the starting time and the operation environment of the ending time; estimating the estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the estimated operation environment of the intermediate time; and calculating the simulation operation energy consumption by adopting the simulation operation parameters of the starting time, the simulation operation parameters of the ending time and the estimated operation parameters of the intermediate time.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
estimating the estimated operation parameters of the last time point according to the simulated operation parameters of the starting time and the estimated operation environment of the last time point; and estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring the simulated operation energy consumption of the starting time and acquiring the simulated operation energy consumption of the ending time; the simulation operation energy consumption of the starting time is generated according to the simulation operation parameters of the starting time; generating the simulation operation energy consumption of the end time according to the simulation operation parameters of the end time; and accumulating the simulated operation energy consumption of the starting time and the simulated operation energy consumption of the ending time to obtain the simulated operation energy consumption.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
extracting initial power from the simulated operation parameters of the initial time, extracting intermediate power from the estimated operation parameters of the intermediate time, and extracting end power from the simulated operation parameters of the end time; and integrating the initial power, the intermediate power and the end power to obtain the simulated operation energy consumption.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring all-working-condition operation data of the air conditioning system; fitting the full-working-condition operation data to obtain a semi-empirical mathematical model; obtaining an equipment control model according to the semi-empirical mathematical model and a preset equipment control logic; and acquiring a thermodynamic hydraulic parameter calculation model, and generating the air conditioner simulation model according to the equipment control model and the thermodynamic hydraulic parameter calculation model.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
performing hydraulic iterative calculation on the air conditioning system to obtain hydraulic parameters of each time, and performing thermal iterative calculation on the air conditioning system to obtain thermal parameters of each time; and obtaining the thermodynamic and hydraulic parameter calculation model according to the hydraulic parameters and the thermodynamic parameters.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring structural part data of the air conditioning system; querying virtual reality characteristics of the structural part data; constructing a virtual reality model of the air conditioning system; the virtual reality model includes virtual reality characteristics of the structure data; and displaying the virtual reality model of the air conditioner simulation model.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
generating a visual energy consumption result of the simulation operation energy consumption; displaying the visual energy consumption result; the visualized energy consumption result comprises at least one of a curve graph, a histogram, a three-dimensional surface graph and a three-dimensional grid graph.
In one embodiment, a computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of:
establishing an air conditioner simulation model, and acquiring a candidate control scheme;
acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme;
and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
In one embodiment, the computer program when executed by the processor further performs the steps of:
setting a starting time and an ending time; acquiring the running environment of the starting time and acquiring the running environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity; acquiring a simulation operation parameter of the starting time and acquiring a simulation operation parameter of the ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulating the operation of the air conditioner system under the operation environment according to the candidate control scheme; generating the simulation operation energy consumption; and the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining an intermediate time; the intermediate time is the time between the start time and the end time; estimating an estimated operation environment of the intermediate time according to the operation environment of the starting time and the operation environment of the ending time; estimating the estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the estimated operation environment of the intermediate time; and calculating the simulation operation energy consumption by adopting the simulation operation parameters of the starting time, the simulation operation parameters of the ending time and the estimated operation parameters of the intermediate time.
In one embodiment, the computer program when executed by the processor further performs the steps of:
estimating the estimated operation parameters of the last time point according to the simulated operation parameters of the starting time and the estimated operation environment of the last time point; and estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the simulated operation energy consumption of the starting time and acquiring the simulated operation energy consumption of the ending time; the simulation operation energy consumption of the starting time is generated according to the simulation operation parameters of the starting time; generating the simulation operation energy consumption of the end time according to the simulation operation parameters of the end time; and accumulating the simulated operation energy consumption of the starting time and the simulated operation energy consumption of the ending time to obtain the simulated operation energy consumption.
In one embodiment, the computer program when executed by the processor further performs the steps of:
extracting initial power from the simulated operation parameters of the initial time, extracting intermediate power from the estimated operation parameters of the intermediate time, and extracting end power from the simulated operation parameters of the end time; and integrating the initial power, the intermediate power and the end power to obtain the simulated operation energy consumption.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring all-working-condition operation data of the air conditioning system; fitting the full-working-condition operation data to obtain a semi-empirical mathematical model; obtaining an equipment control model according to the semi-empirical mathematical model and a preset equipment control logic; and acquiring a thermodynamic hydraulic parameter calculation model, and generating the air conditioner simulation model according to the equipment control model and the thermodynamic hydraulic parameter calculation model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
performing hydraulic iterative calculation on the air conditioning system to obtain hydraulic parameters of each time, and performing thermal iterative calculation on the air conditioning system to obtain thermal parameters of each time; and obtaining the thermodynamic and hydraulic parameter calculation model according to the hydraulic parameters and the thermodynamic parameters.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring structural part data of the air conditioning system; querying virtual reality characteristics of the structural part data; constructing a virtual reality model of the air conditioning system; the virtual reality model includes virtual reality characteristics of the structure data; and displaying the virtual reality model of the air conditioner simulation model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
generating a visual energy consumption result of the simulation operation energy consumption; displaying the visual energy consumption result; the visualized energy consumption result comprises at least one of a curve graph, a histogram, a three-dimensional surface graph and a three-dimensional grid graph.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements are not limited by these terms. These terms are used only to distinguish a first model acquisition submodule from another model acquisition submodule. For example, the first model acquisition sub-module may be referred to as a second model acquisition sub-module, and similarly, the second model acquisition sub-module may be referred to as a first model acquisition sub-module, without departing from the scope of the present invention. The first model acquisition submodule and the second model acquisition submodule are both model acquisition submodules, but are not the same model acquisition submodule.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (12)
1. A control optimization method of an air conditioning system is characterized by comprising the following steps:
establishing an air conditioner simulation model, and acquiring a candidate control scheme;
acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme; the acquiring of the simulated operation energy consumption comprises the following steps: setting a starting time and an ending time;
acquiring the running environment of the starting time and acquiring the running environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity;
acquiring a simulation operation parameter of the starting time and acquiring a simulation operation parameter of the ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulating the operation of the air conditioner system under the operation environment according to the candidate control scheme;
generating the simulation operation energy consumption; the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time;
and determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
2. The method of claim 1, wherein generating the simulation operating energy consumption when a deep simulation request is received comprises:
determining an intermediate time; the intermediate time is the time between the start time and the end time;
estimating an estimated operation environment of the intermediate time according to the operation environment of the starting time and the operation environment of the ending time;
estimating the estimated operation parameters of the intermediate time according to the simulated operation parameters of the starting time and the estimated operation environment of the intermediate time;
and calculating the simulation operation energy consumption by adopting the simulation operation parameters of the starting time, the simulation operation parameters of the ending time and the estimated operation parameters of the intermediate time.
3. The method of claim 2, wherein the intermediate time comprises a previous time point and a next time point, and wherein estimating the estimated operating parameters of the intermediate time based on the simulated operating parameters of the start time and the estimated operating environment of the intermediate time comprises:
estimating the estimated operation parameters of the last time point according to the simulated operation parameters of the starting time and the estimated operation environment of the last time point;
and estimating the estimated operation parameter of the next time point according to the estimated operation parameter of the previous time point and the estimated operation environment of the next time point.
4. The method of claim 1, wherein the generating the simulated operating energy consumption comprises:
acquiring the simulated operation energy consumption of the starting time and acquiring the simulated operation energy consumption of the ending time; the simulation operation energy consumption of the starting time is generated according to the simulation operation parameters of the starting time; generating the simulation operation energy consumption of the end time according to the simulation operation parameters of the end time;
and accumulating the simulated operation energy consumption of the starting time and the simulated operation energy consumption of the ending time to obtain the simulated operation energy consumption.
5. The method of claim 2, wherein said calculating said simulated operating energy consumption using said simulated operating parameters of said start time, said simulated operating parameters of said end time, and said estimated operating parameters of said intermediate time comprises:
extracting initial power from the simulated operation parameters of the initial time, extracting intermediate power from the estimated operation parameters of the intermediate time, and extracting end power from the simulated operation parameters of the end time;
and integrating the initial power, the intermediate power and the end power to obtain the simulated operation energy consumption.
6. The method of claim 1, wherein the creating an air conditioner simulation model comprises:
acquiring all-working-condition operation data of the air conditioning system;
fitting the full-working-condition operation data to obtain a semi-empirical mathematical model;
obtaining an equipment control model according to the semi-empirical mathematical model and a preset equipment control logic;
and acquiring a thermodynamic hydraulic parameter calculation model, and generating the air conditioner simulation model according to the equipment control model and the thermodynamic hydraulic parameter calculation model.
7. The method of claim 6, wherein said obtaining a thermodynamic hydraulic parameter calculation model comprises:
performing hydraulic iterative calculation on the air conditioning system to obtain hydraulic parameters of each time, and performing thermal iterative calculation on the air conditioning system to obtain thermal parameters of each time;
and obtaining the thermodynamic and hydraulic parameter calculation model according to the hydraulic parameters and the thermodynamic parameters.
8. The method of claim 1, wherein the creating an air conditioner simulation model further comprises:
acquiring structural part data of the air conditioning system;
querying virtual reality characteristics of the structural part data;
constructing a virtual reality model of the air conditioning system; the virtual reality model includes virtual reality characteristics of the structure data;
and displaying the virtual reality model of the air conditioner simulation model.
9. The method according to any one of claims 1-8, further comprising:
generating a visual energy consumption result of the simulation operation energy consumption;
displaying the visual energy consumption result; the visualized energy consumption result comprises at least one of a curve graph, a histogram, a three-dimensional surface graph and a three-dimensional grid graph.
10. A control optimization device for an air conditioning system, the device comprising:
the acquisition module is used for establishing an air conditioner simulation model and acquiring a candidate control scheme;
the simulation module is used for acquiring simulation operation energy consumption; the simulation operation energy consumption is the operation energy consumption generated when the air conditioner simulation model simulates the air conditioner system to operate according to the candidate control scheme; the acquiring of the simulated operation energy consumption comprises the following steps: setting a starting time and an ending time;
acquiring the running environment of the starting time and acquiring the running environment of the ending time; the operation environment comprises a building cold load and the environment temperature and humidity;
acquiring a simulation operation parameter of the starting time and acquiring a simulation operation parameter of the ending time; the simulation operation parameters are operation parameters of the air conditioner simulation model simulating the operation of the air conditioner system under the operation environment according to the candidate control scheme;
generating the simulation operation energy consumption; the simulation operation energy consumption is generated according to the simulation operation parameters of the starting time and the simulation operation parameters of the ending time;
and the optimization module is used for determining the candidate control scheme of the air conditioning system as an energy-saving control scheme according to the simulated operation energy consumption.
11. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 9 when executing the computer program.
12. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 9.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811339436.8A CN109373525B (en) | 2018-11-12 | 2018-11-12 | Control optimization method and device of air conditioning system, computer equipment and storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811339436.8A CN109373525B (en) | 2018-11-12 | 2018-11-12 | Control optimization method and device of air conditioning system, computer equipment and storage medium |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109373525A CN109373525A (en) | 2019-02-22 |
CN109373525B true CN109373525B (en) | 2020-03-06 |
Family
ID=65384555
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811339436.8A Active CN109373525B (en) | 2018-11-12 | 2018-11-12 | Control optimization method and device of air conditioning system, computer equipment and storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109373525B (en) |
Families Citing this family (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113557393B (en) * | 2019-03-05 | 2022-08-02 | 亿可能源科技(上海)有限公司 | Management method, control method and system of air conditioning system and storage medium |
CN109945403A (en) * | 2019-03-13 | 2019-06-28 | 珠海格力电器股份有限公司 | Big data-based equipment power consumption management system and method and air conditioner |
CN113614460B (en) * | 2019-03-29 | 2022-08-26 | 亿可能源科技(上海)有限公司 | Management method, control method and system of air conditioning system and storage medium |
CN110186157A (en) * | 2019-06-13 | 2019-08-30 | 宁波奥克斯电气股份有限公司 | A kind of control method, device and the air conditioner of electrical equipment electricity consumption |
CN110619152B (en) * | 2019-08-16 | 2022-08-02 | 珠海格力电器股份有限公司 | Simulation experiment parameter setting method, device, equipment and storage medium |
CN110736241B (en) * | 2019-10-29 | 2020-10-09 | 珠海格力电器股份有限公司 | Method and device for controlling air conditioning equipment |
CN111076354A (en) * | 2019-12-31 | 2020-04-28 | 珠海格力电器股份有限公司 | Equipment model selection method and system of central air conditioner |
CN113739364B (en) * | 2020-05-29 | 2023-12-26 | 广东美的制冷设备有限公司 | Energy consumption estimating method, air conditioner and storage medium |
CN112417619B (en) * | 2020-11-23 | 2021-10-08 | 江苏大学 | Pump unit optimal operation adjusting system and method based on digital twinning |
CN112489227B (en) * | 2020-11-30 | 2022-02-15 | 珠海格力电器股份有限公司 | Type selection method, device and system of air conditioning unit |
CN112749950A (en) * | 2021-01-14 | 2021-05-04 | 珠海大横琴科技发展有限公司 | Energy consumption management method and device, electronic equipment and storage medium |
CN114637350A (en) * | 2022-02-28 | 2022-06-17 | 青岛海尔空调电子有限公司 | Space environment control method, device and storage medium |
CN115930376A (en) * | 2022-10-08 | 2023-04-07 | 佳都科技集团股份有限公司 | Air conditioner control algorithm evaluation method, device, equipment and storage medium |
CN116026007A (en) * | 2022-12-21 | 2023-04-28 | 珠海格力电器股份有限公司 | Temperature adjusting method and device, storage medium and electronic equipment |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2013142494A (en) * | 2012-01-10 | 2013-07-22 | Hitachi Plant Technologies Ltd | Air conditioner control system and method of controlling air conditioner |
CN105678429B (en) * | 2016-02-19 | 2019-04-16 | 西南交通大学 | A method of realizing the multidisciplinary multiple-objection optimization of electric automobile air-conditioning system |
CN107314498A (en) * | 2017-05-25 | 2017-11-03 | 中国农业大学 | The efficiency on-line monitoring method and device of a kind of central air conditioner system |
-
2018
- 2018-11-12 CN CN201811339436.8A patent/CN109373525B/en active Active
Also Published As
Publication number | Publication date |
---|---|
CN109373525A (en) | 2019-02-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109373525B (en) | Control optimization method and device of air conditioning system, computer equipment and storage medium | |
CN109595747B (en) | Energy consumption simulation method and device of air conditioning system | |
Yin et al. | Quantifying flexibility of commercial and residential loads for demand response using setpoint changes | |
Vrettos et al. | Experimental demonstration of frequency regulation by commercial buildings—Part I: Modeling and hierarchical control design | |
Yun et al. | Building hourly thermal load prediction using an indexed ARX model | |
Afram et al. | Gray-box modeling and validation of residential HVAC system for control system design | |
KR100830095B1 (en) | Prediction method for cooling load | |
US9429921B2 (en) | Method and system for energy control management | |
CN105091076B (en) | Energy-saving effect computational methods and device | |
Urieli et al. | A learning agent for heat-pump thermostat control | |
CN107735735A (en) | Device characteristics model learning device, device characteristics model learning method and storage medium | |
US9454173B2 (en) | Predictive alert system for building energy management | |
Ruschenburg et al. | Validation of a black-box heat pump simulation model by means of field test results from five installations | |
Gomes et al. | A physically-based model for simulating inverter type air conditioners/heat pumps | |
Ruiz-Calvo et al. | Reference data sets for validating and analyzing GSHP systems based on an eleven-year operation period | |
Kalogeras et al. | Predictive capability testing and sensitivity analysis of a model for building energy efficiency | |
CN109595746B (en) | Water pump operation efficiency optimization control method and device and computer equipment | |
Souayfane et al. | A weather-clustering and energy-thermal comfort optimization methodology for indoor cooling in subtropical desert climates | |
Dermentzis et al. | An overview of energy district tools in Europe and the importance of an equivalent heating reference temperature for district simulations | |
Baker et al. | Frequency regulation services from connected residential devices: Short paper | |
Mehrfeld | Evaluation of heat pump systems under dynamic operating conditions | |
Atam et al. | Borehole dynamics parameterization for thermal performance optimization under operational constraints | |
Afram et al. | Data-driven modeling of thermal energy storage tank | |
Gunay et al. | Development of a clustering-based morning start time estimation algorithm for space heating and cooling | |
Narayanan et al. | Systems approach to energy efficient building operation: case studies and lessons learned in a university campus |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |