CN105320118B - Air-conditioning system electricity needs response control mehtod based on cloud platform - Google Patents

Air-conditioning system electricity needs response control mehtod based on cloud platform Download PDF

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CN105320118B
CN105320118B CN201510894110.1A CN201510894110A CN105320118B CN 105320118 B CN105320118 B CN 105320118B CN 201510894110 A CN201510894110 A CN 201510894110A CN 105320118 B CN105320118 B CN 105320118B
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air conditioning
power consumption
humidity
conditioning system
building
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CN105320118A (en
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张迎春
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/41885—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by modeling, simulation of the manufacturing system

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  • Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • General Engineering & Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

The present invention provides a kind of the air-conditioning system electricity needs response control mehtod based on cloud platform, a cloud platform connection at least air-conditioning system, comprising: instructed according to dispatching of power netwoks, determine the total electricity consumption value of the maximum of all air-conditioning systems；According to the indoor target temperature and humidity of air-conditioning system, the electricity consumption and its architecture indoor temperature and humidity relational model of air-conditioning system are established；Construction, indoor environment and air-conditioning system based on building establish architecture noumenon model respectively to the indoor temperature and humidity contribution data of the building；Establish total power consumption control model of all air-conditioning systems；The real time execution parameter of the air-conditioning system, the warm and humid data of real-time indoor and outdoor of the real-time power load and the building of the air-conditioning system are inputted into total power consumption control model, the control parameter change curve of the air-conditioning system is calculated, and controls the electricity needs response of the air-conditioning system accordingly.The present invention can utmostly meet users'comfort demand in the case where completing dispatching of power netwoks instruction.

Description

Cloud platform based air conditioning system power demand response control method
Technical Field
The invention relates to the field of air conditioners and smart power grids, in particular to an air conditioner system power demand response control method based on a cloud platform.
Background
Demand Response (DR) is power Demand Response, which is a short-term behavior that when the price of the wholesale market of power is increased or the reliability of the system is threatened, after a power consumer receives a direct compensation notification of inductive load reduction or a power price increase signal sent by a power supplier, the power consumer changes the inherent power consumption pattern, and the power consumption load in a certain period of time is reduced or shifted to respond to power supply, so that the stability of the power grid is guaranteed, and the power price increase is suppressed. The demand response strategy is divided into demand response based on price and demand response based on incentive, the demand response based on price implements time-sharing price, the corresponding demand response strategy is more, the demand response based on incentive means that a demand response implementing mechanism makes a corresponding policy according to the supply and demand condition of the power system, a user reduces the power demand when the system needs or the power is in tension, so as to obtain preferential electricity price of direct compensation or other periods, before implementing a demand response plan, the demand response implementing mechanism generally needs to sign a contract with a participating user in advance, the content of demand response is agreed in the contract (the size of the power load and the accounting standard, the response duration, the maximum response times in the contract period, and the like), the advance notification time, the compensation or electricity price discount standard, the penalty measure of default, and the like. The system can be classified into Direct Load Control (DLC), Interruptible Load (IL), Demand Side Bidding (DSB), Emergency Demand Response (EDR), capacity market project, auxiliary service project, and the like.
The power consumption of the air conditioning system accounts for about 50% of the power consumption of the building, and due to the cold storage capacity of the building body and the air conditioning system, the comfort is not affected by the short-time closing of the air conditioning system, and the air conditioning system is suitable as a target for demand response. At present, researchers propose a model considering thermodynamic characteristics and various parameters of equipment, a State Queuing (SQ) method is adopted to model the switching state transition characteristics of the temperature control equipment, and a numerical model based on discrete integration is proposed to perform corresponding control optimization based on a user-side comfort degree constraint algorithm.
However, these methods are limited to adjusting the temperature setting value of the temperature control device, or simply sequencing and controlling the start and stop of the device according to the temperature setting value, and thus the comfort requirement of the user cannot be met well.
Disclosure of Invention
The invention provides a cloud platform-based air conditioning system demand response control method, which aims to solve one or more defects in the prior art.
The invention provides an air conditioning system power demand response control method based on a cloud platform, wherein the cloud platform is connected with at least one air conditioning system and comprises the following steps: determining the maximum total power utilization value of all the air conditioning systems according to a power grid dispatching instruction; establishing a relation model between the power consumption of the air conditioning system and the indoor temperature and humidity of the building according to the indoor target temperature and humidity of the air conditioning system; building a building body model based on the structure of the building, the indoor environment and the contribution data of the air conditioning system to the indoor temperature and humidity of the building respectively so as to calculate the indoor temperature and humidity which dynamically change; establishing a general power consumption control model of all the air conditioning systems by combining the maximum total power consumption value, the power consumption of the air conditioning systems, a building indoor temperature and humidity relation model, the building body model and a set temperature and humidity comfort level interval; and respectively inputting the real-time operation parameters of the air conditioning system, the real-time power load of the air conditioning system and the real-time indoor and outdoor temperature and humidity data of the building into the general power control model, calculating to obtain a control parameter change curve of the air conditioning system, and controlling the power demand response of the air conditioning system according to the control parameter change curve.
In one embodiment, the power grid dispatching instruction is an actual power grid dispatching instruction obtained from a power grid dispatching system, wherein the cloud platform is connected with the power grid dispatching system.
In one embodiment, the difference between the obtaining time of the actual power grid dispatching command and the starting time of the power demand response of the air conditioning system is less than or equal to a set time; the general electricity consumption control model simultaneously satisfies the following conditions: the indoor target humiture of building is located set for temperature and humidity comfort level interval in and all air conditioning system's total power consumption is less than the biggest total power consumption value combines the biggest total power consumption value air conditioning system's power consumption rather than the indoor humiture relation model of building the building body model and one set for temperature and humidity comfort level interval, establish all air conditioning system's total power consumption control model includes: establishing a total power consumption objective function of all the air conditioning systems according to a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building; establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval; establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value; and generating the total power consumption control model by combining the total power consumption target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
In one embodiment, the difference between the obtaining time of the actual power grid dispatching command and the starting time of the power demand response of the air conditioning system is less than or equal to a set time; the general electricity consumption control model simultaneously satisfies the following conditions: the indoor target humiture of building is located set for outside the warm and humid comfort level interval and all air conditioning system's total power consumption is less than the biggest total power consumption value combines the biggest total power consumption value air conditioning system's power consumption rather than the indoor humiture relation model of building the building body model and one set for warm and humid comfort level interval, establish all air conditioning system's total power consumption control model includes: according to the building body model and the set temperature and humidity comfort level interval, establishing an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature and humidity comfort level interval; establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value; and establishing a total power consumption control model which preferentially meets the constraint function of the total power consumption by combining the target function which is minimally deviated from the set temperature-humidity comfort degree interval and the constraint function of the total power consumption.
In one embodiment, the difference between the obtaining time of the actual power grid dispatching instruction and the starting time of the power demand response of the air conditioning system is greater than a set time; the general electricity consumption control model takes the water system of the air conditioning system and the cold storage capacity of the body of the building into consideration.
In one embodiment, the general electric control model simultaneously satisfies: the indoor target humiture of building is located set for temperature and humidity comfort level interval in and all air conditioning system's total power consumption is less than the biggest total power consumption value combines the biggest total power consumption value air conditioning system's power consumption rather than the indoor humiture relation model of building the building body model and one set for temperature and humidity comfort level interval, establish all air conditioning system's total power consumption control model includes: establishing a total power consumption objective function of all the air conditioning systems according to a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building, wherein the total power consumption objective function is an integral model; establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval; establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value; and generating the total power consumption control model by combining the total power consumption target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
In one embodiment, the general electric control model simultaneously satisfies: the indoor target humiture of building is located set for outside the warm and humid comfort level interval and all air conditioning system's total power consumption is less than the biggest total power consumption value combines the biggest total power consumption value air conditioning system's power consumption rather than the indoor humiture relation model of building the building body model and one set for warm and humid comfort level interval, establish all air conditioning system's total power consumption control model includes: according to the building body model and the set temperature-humidity comfort level interval, establishing an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature-humidity comfort level interval, wherein the objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature-humidity comfort level interval is an integral model; establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value; and establishing a total power consumption control model which preferentially meets the constraint function of the total power consumption by combining the target function which is minimally deviated from the set temperature-humidity comfort degree interval and the constraint function of the total power consumption.
In one embodiment, the power grid dispatching instruction is a predicted power grid dispatching instruction; and the air conditioning system carries out power demand response according to the plurality of predicted power grid dispatching instructions.
In one embodiment, the general electric control model simultaneously satisfies: the indoor target humiture of building is located set for temperature and humidity comfort level interval in and all air conditioning system's total power consumption is less than the biggest total power consumption value combines the biggest total power consumption value air conditioning system's power consumption rather than the indoor humiture relation model of building the building body model and one set for temperature and humidity comfort level interval, establish all air conditioning system's total power consumption control model includes: establishing a total power consumption electric charge/electric quantity objective function of all the air conditioning systems according to the occurrence probability of each predicted power grid dispatching instruction and a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building, wherein the total power consumption electric charge/electric quantity objective function is an integral model; establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval; establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value; and generating the total power consumption control model by combining the total power consumption electric charge/electric quantity target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
In one embodiment, the method further comprises: and generating the predicted power grid scheduling instruction according to load data of a power supply power grid of the air conditioning system and/or historical operating parameter data of the air conditioning system based on one or more parameters of time, electricity price, outdoor temperature, outdoor humidity, outdoor illumination and wind power, and calculating the occurrence probability of the predicted power grid scheduling instruction.
In one embodiment, the relation between the power consumption of the air conditioning system and the indoor temperature and humidity of the building model includes: the power consumption of the refrigerating unit, the power consumption of the freezing and cooling water pump, the power consumption of the cooling tower and the power consumption of the tail end fan.
In one embodiment, the control parameters include: the air conditioning system is characterized by comprising one or more of start-stop state of the air conditioning system, chilled water temperature, unit load rate, chilled water flow, cooling water flow, start-stop state of a fan of a cooling tower, air volume of the air conditioning unit, air volume of a fan coil, air outlet temperature of a fresh air unit and air volume of the fresh air unit.
In one embodiment, the general power consumption control model is:
or
Tpj,Hdj∈Sj，
Wherein,andrespectively a total power consumption objective function and a total power consumption and electricity charge objective function; t ispj,Hdj∈SjIs an indoor temperature and humidity constraint function of the building;is a total power consumption constraint function of all the air conditioning systems; pe is the total electricity consumption of all the air conditioning systems in unit time; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; m is the number of the air conditioning systems, m is more than or equal to 1, and m is a positive integer; pejIs the power consumption of the air conditioning system j in a unit time; t ispjIs the building indoor temperature of air conditioning system j; ce is the total electricity charge used by all the air conditioning systems per unit time; cejIs the electricity charge used by the air conditioning system j in a unit time; hdjIs the building indoor humidity of air conditioning system j; sjIs the set temperature and humidity comfort interval of the air conditioning system j; pemax is the maximum total power usage value of all the air conditioning systems per unit time.
In one embodiment, the general power consumption control model is:
minρ((Tpj,Hdj),Sj)；
wherein, min ρ ((T)pj,Hdj),Sj) Is the most indoor temperature and humidity of the buildingA target function slightly deviating from the set temperature-humidity comfort interval;is a total power consumption constraint function of all the air conditioning systems; t ispjIs the building indoor temperature of air conditioning system j; hdjIs the building indoor humidity of air conditioning system j; sjIs the set temperature and humidity comfort interval of the air conditioning system j; pe is the total electricity consumption of all the air conditioning systems in unit time; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; m is the number of the air conditioning systems, m is more than or equal to 1, and m is a positive integer; pejIs the power of the air conditioning system j per unit time; pemax is the maximum total power consumption value of all the air conditioning systems in unit time; rho is the temperature and humidity deviation set temperature and humidity comfort level interval S in the building roomjAs a function of (c).
In one embodiment, the general power consumption control model is:
or wherein the one or more of the one,
ts＜t＜te；
wherein,andrespectively, integrating models of a total power consumption objective function and a total power consumption and electricity charge objective function;is an indoor temperature and humidity constraint function of the building;is a total power consumption constraint function of all the air conditioning systems; t is t0Obtaining time of a power grid dispatching instruction; t is teIs the end time of the air conditioning system power demand response; t represents a time; t is tsIs a starting time of a power demand response of the air conditioning system; petThe total power consumption of all the air conditioning systems at the moment t; cetIs the total electricity charge used by all the air conditioning systems in the unit time at the time t; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; m is the number of the air conditioning systems, m is more than or equal to 1, and m is a positive integer;is the power consumption of the air conditioning system j at time t;is the electricity charge used by the air conditioning system j in the unit time at time t;is the building indoor temperature of the air conditioning system j at time t;is the building indoor humidity of the air conditioning system j at time t; sjIs the set temperature and humidity comfort interval of the air conditioning system j;is the maximum total electrical power used by all the air conditioning systems per unit time at time t.
In one embodiment, the general power consumption control model is:
ts＜t＜te；
wherein,the integral model is an objective function of the set temperature and humidity comfort degree interval of the minimum deviation of the indoor temperature and humidity of the building;is a total power consumption constraint function of all the air conditioning systems;is the building indoor temperature of the air conditioning system j at time t;is the building indoor humidity of the air conditioning system j at time t; rho is the temperature and humidity deviation set temperature and humidity comfort level interval S in the building roomjA function of (a); sjIs the set temperature and humidity comfort interval of the air conditioning system j; petThe total electricity consumption of all the air conditioning systems in unit time at the time t;is the maximum total power consumption value of all the air conditioning systems in unit time at the time t; t is t0Obtaining time of a power grid dispatching instruction; t is teIs the end time of the air conditioning system power demand response; t represents a time; t is tsIs the starting time of the power demand response of the air conditioning system.
In one embodiment, the general power consumption control model is:
ti,s＜t＜te；
wherein,is an integral model of the total electricity and power charge objective function;is an indoor temperature and humidity constraint function of the building;is a total power consumption constraint function of all the air conditioning systems; i is the serial number of a predicted power grid scheduling instruction, i is more than or equal to 1 and less than or equal to n, and i and n are positive integers; piPredicting the occurrence probability of a power grid dispatching instruction i; t represents a time; t is t0Predicting the acquisition time of a power grid dispatching instruction; t is teIs the end time of the air conditioning system power demand response; cei,tThe total electricity charge used by all the air conditioning systems in the unit time at the moment t and under the condition of predicting a power grid dispatching instruction i;predicting the building indoor temperature of an air conditioning system j under the condition of a power grid dispatching instruction i at the moment t;predicting the building indoor humidity of the air conditioning system j under the condition of the power grid dispatching instruction i at the moment t; siThe method is a set temperature and humidity comfort level interval under the condition of predicting a power grid dispatching instruction i; pei,tThe total power consumption of all the air conditioning systems is within unit time at the moment t and under the condition of predicting a power grid dispatching instruction i;the maximum total power utilization value of all the air conditioning systems is within unit time at the time t and under the condition of predicting a power grid dispatching instruction i; t is ti,sIs the response of the air conditioning system to the power demand of the forecast scheduling command iThe time of the start of the response.
In one embodiment, the relation model between the power consumption of the air conditioning system and the indoor temperature and humidity of the building is as follows:
s.t.Tj p≤Tj p0，Hj d≤Hj d0；
ors.t.Tj p≤Tj p0，Hj d≤Hj d0；
Wherein,indicating elapsed power demand response time teThe electricity charge of the air conditioning system j; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; t is the response time of the air conditioning system j; teis the end time of the power demand response of the air conditioning system j; pj,t chillerIs a system of air-conditioning systems j in a unit time at time tThe power consumption of the cooling unit; pj,t pumpThe electricity consumption of the refrigeration cooling water pump of the air conditioning system j in unit time at the time t; pj,t towerThe electricity consumption of the cooling tower of the air conditioning system j in unit time at the moment t; pj,t fanIs an air conditioning system in unit time at the time of tThe power consumption of a fan at the tail end of the system j is calculated; s.t. denotes constrained; t isj pIs the building indoor temperature of air conditioning system j; t isj p0Is an air conditioning system jThe building indoor target temperature of (1); hj dIs the building indoor humidity of air conditioning system j; hj d0Is the building indoor target humidity of the air conditioning system jDegree;is the lapse of the power demand response time teAir conditioning system j usesTotal electricity charge of (c); ctIs the electricity rate at time t.
In one embodiment, the building ontology model is:
wherein C is air hot melt; v is the total building indoor air capacity of the air conditioning system; t ispIs the building indoor temperature of the air conditioning system; t is a time variable; Δ Hf＝CFf(Tf-Tp) Is the fresh air heat exchange quantity of the air conditioning system; qc＝CFc(Tc-Tp) Is the heat exchange capacity of the indoor fan coil of the air conditioning system; qt＝α(Te-Tp) Is the indoor and outdoor heat exchange capacity of the building of the air conditioning system; qiIs the indoor heat source heat dissipation of the air conditioning system; ffIs the fresh air flow rate; t isfIs the fresh air outlet temperature; fcIs the circulating air flow rate; t iscIs the outlet air temperature of the circulating air, α is the comprehensive heat exchange coefficient of the window wall, TeIs the building outdoor temperature of the air conditioning system; ρ is the air density; v is the total building indoor air capacity of the air conditioning system; hdIs the building indoor moisture content of the air conditioning system; t is a time variable; ffIs the fresh air flow rate; wfThe moisture content of the fresh air outlet; fcIs the circulating air flow rate; wcIs the moisture content of the air outlet of the circulating air; and w is the indoor human body and object moisture dissipation capacity of the building of the air conditioning system.
According to the embodiment of the invention, the power demand response control of the multiple air-conditioning systems can be carried out based on the cloud platform, the multiple air-conditioning systems can be coordinated with each other, not only can the power grid dispatching instruction be completed, but also the comfort level demand of a user can be ensured. In the embodiment of the invention, the total power consumption control model of all the air conditioning systems takes various factors such as a power grid dispatching instruction, the relation between the power consumption and the indoor temperature and humidity of a building, a building body, a temperature and humidity comfort degree interval and the like into consideration, and the power consumption of the air conditioning systems can be effectively reduced under the condition of meeting the power grid dispatching requirement and meeting the comfort degree requirement of users as much as possible.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a schematic diagram of an embodiment of an air conditioning system power demand response control system according to the present invention;
FIG. 2 is a basic flow diagram of the air conditioning system power demand response method of the present invention;
fig. 3 is a schematic flow chart of a power demand response control method of an air conditioning system based on a cloud platform according to an embodiment of the present invention;
FIG. 4 is a flow chart illustrating a method for building an overall power consumption control model according to an embodiment of the present invention;
FIG. 5 is a flow chart illustrating a method for building an overall power consumption control model according to an embodiment of the invention;
FIG. 6 is a flow chart illustrating a method for building an overall power consumption control model according to an embodiment of the invention;
FIG. 7 is a flow chart illustrating a method for building an overall power consumption control model according to an embodiment of the invention;
FIG. 8 is a flow chart illustrating a method for building an overall power consumption control model according to an embodiment of the present invention;
fig. 9 is a flowchart illustrating a power demand response control method for an air conditioning system based on a cloud platform according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
Fig. 1 is a schematic structural diagram of an air conditioning system power demand response control system according to an embodiment of the present invention. As shown in fig. 1, a system of an embodiment of the invention may include: the system comprises a cloud platform 100, a power grid dispatching system 200, a plurality of air conditioning systems 300, an indoor temperature and humidity sensor 500 and a network 600. The cloud platform 100 is connected to the grid dispatching system 200 to obtain a grid dispatching instruction, connected to the air conditioning systems 300 to obtain information related to air conditioning equipment and control an operation state of the air conditioning systems, connected to the indoor temperature and humidity sensor 500 to obtain indoor temperature and humidity, and connected to the network 600 to obtain information related to the network, such as outdoor temperature and humidity, an air conditioning state, and the like. The cloud platform 100 may include a database 101 and a control policy engine 102, where the database 101 may be used to store information such as various control models, power grid scheduling instruction data, and air conditioning system operation data, and the control policy engine 102 may be used to control a power demand response of the air conditioning system 300.
The invention provides an air conditioning system power demand response method based on a cloud platform. Fig. 2 is a schematic diagram of a basic flow of the method for responding to the power demand of the air conditioning system, and as shown in fig. 2, the method can establish a general power consumption control model according to information such as a power grid scheduling instruction, indoor and outdoor temperature and humidity/weather information of the air conditioning system, and an operation parameter of the air conditioning system, and in combination with an indoor comfort level section corresponding to the air conditioning system, calculate a control parameter or a control parameter variation curve of the air conditioning system connected to a cloud platform according to the general power consumption control model, and finally control the power demand response of the air conditioner according to the control parameter or the control parameter variation curve.
Fig. 3 is a schematic flow chart of a power demand response control method of an air conditioning system based on a cloud platform according to an embodiment of the present invention. As shown in fig. 3, the cloud platform on which the method for controlling the response to the demand for electric power of the air conditioning system according to the present invention is based is connected to at least one air conditioning system, and the method may include the steps of:
s110: determining the maximum total power utilization value of all the air conditioning systems according to a power grid dispatching instruction;
s120: establishing a relation model between the power consumption of the air conditioning system and the indoor temperature and humidity of the building according to the indoor target temperature and humidity of the air conditioning system;
s130: building a building body model based on the structure of the building, the indoor environment and the contribution data of the air conditioning system to the indoor temperature and humidity of the building respectively so as to calculate the indoor temperature and humidity which dynamically change;
s140: establishing a general power consumption control model of all the air conditioning systems by combining the maximum total power consumption value, the power consumption of the air conditioning systems, a building indoor temperature and humidity relation model, the building body model and a set temperature and humidity comfort level interval;
s150: and respectively inputting the real-time operation parameters of the air conditioning system, the real-time power load of the air conditioning system and the real-time indoor and outdoor temperature and humidity data of the building into the general power control model, calculating to obtain a control parameter change curve of the air conditioning system, and controlling the power demand response of the air conditioning system according to the control parameter change curve.
In step S110, the grid dispatching command may be an actual grid dispatching command from the grid dispatching system, or a predicted grid dispatching command obtained according to various historical data. And the maximum total power utilization value determined according to the power grid dispatching command is the upper power utilization limit of all the air conditioning systems during power demand response. The maximum total power usage value may be expressed in terms of power, such as an amount of electricity per hour, or may be expressed in terms of total power usage over a period of power demand response. The power grid dispatching instruction may specifically include various information such as electricity price, time interval, dispatching time, and maximum power consumption/power, and may be specifically selected as needed.
In the step S120, the model of the relationship between the power consumption of the air conditioning system and the building indoor temperature and humidity may refer to a minimum power consumption required by the air conditioning system when the building indoor temperature of the air conditioning system is maintained at a target temperature and the humidity is maintained at a target humidity. For example, the relationship between the power consumption of the air conditioning system and the indoor temperature and humidity of the building in the model may include: the power consumption of the refrigerating unit, the power consumption of the freezing and cooling water pump, the power consumption of the cooling tower and the power consumption of the tail end fan. The specific power consumption considered may depend on the actual conditions of the air conditioning system. The power usage may be power consumption or energy consumption.
In the step S130, the structure of the building, the indoor environment and the air conditioning system may all have an influence on the indoor temperature and humidity of the building. The structure of the building can refer to the structure (such as a door and a window) of the building where the air conditioning system is located, the size of the space, building materials and other building body factors influencing the indoor temperature and humidity; the indoor environment can refer to indoor temperature and humidity influence factors such as indoor temperature, a heat dissipation source and the like; the influence factors of the air conditioning system on the indoor temperature and humidity of the building can include fan coil heat dissipation, fresh air flow rate, fresh air outlet temperature, circulating air outlet temperature and other factors.
In step S130, the obtained building body model may be a dynamic change equation of temperature and a dynamic change equation of humidity. The building body model considers a plurality of factors influencing indoor temperature and humidity, such as buildings, environments, air conditioning systems and the like, and is more in line with the actual situation.
In the step S140, the requirement of the power grid dispatching command is considered through the maximum total power consumption value, the requirement of the comfort level of the user is considered through the set temperature and humidity comfort level section, and a more accurate and reasonable total power consumption control model can be obtained under the condition of comprehensively considering the power grid dispatching command and the comfort level according to the power consumption of the air conditioning system, the building indoor temperature and humidity relation model and the building body model. The reasonable air conditioning system control parameter change curve can be obtained by utilizing the general power consumption control model.
In the step S140, the comfort zone may relate to various comfort parameters, such as temperature, humidity, customs, carbon dioxide concentration, and the like, in the embodiment of the present invention, the temperature and humidity are mainly considered, and in other embodiments, other factors to be considered may be selected as needed to perform the power demand response. The set temperature-humidity comfort interval may be a temperature-humidity comfort interval of an indoor environment corresponding to each air conditioning system. It should be noted that, in the embodiments of the present invention, the description of "warm and humid" may refer to temperature and humidity, for example, the temperature and humidity may refer to temperature and humidity, and the warm and humid comfort interval may refer to a temperature comfort interval and a humidity comfort interval.
The air conditioning system, such as a large building central air conditioner, a household air conditioner, and an industrial air conditioner, may set the temperature and humidity comfort level setting range according to the type and/or the user's requirement. Comfort intervals of a large building central air conditioner and a household air conditioner can be determined according to the comfort intervals published by ASHREA or national building energy-saving national standards and the like, or the comfort intervals can be customized according to user requirements; the comfort zone of the industrial air conditioner can be defined according to the requirements of the industrial process.
In the step S150, the real-time operation parameters of the air conditioning system, the real-time electrical load of the air conditioning system, and the real-time indoor and outdoor temperature and humidity data of the building are various data obtained from the air conditioning system for calculating the control parameters of the air conditioning system, which may be determined as needed. The real-time operation parameters of the air conditioning system may include: the air conditioning system comprises parameters such as state/start-stop, power consumption, temperature of freezing water, flow, unit load rate, air quantity and air outlet temperature of the air conditioning unit, air quantity and air outlet temperature of the fresh air unit and the like. The parameters of the air conditioning system can be saved to the cloud platform to be called when needed. In addition, the cloud platform can be used for controlling parameters such as starting and stopping of the air conditioning system, chilled water temperature/unit load rate and the like.
For example, the control parameters of the air conditioning system may include: the air conditioning system is characterized by comprising one or more of start-stop state of the air conditioning system, chilled water temperature, unit load rate, chilled water flow, cooling water flow, start-stop state of a fan of a cooling tower, air volume of the air conditioning unit, air volume of a fan coil, air outlet temperature of a fresh air unit and air volume of the fresh air unit.
According to the embodiment of the invention, the power demand response control of the multiple air-conditioning systems can be carried out based on the cloud platform, the multiple air-conditioning systems can be coordinated with each other, not only can the power grid dispatching instruction be completed, but also the comfort level demand of a user can be ensured. In the embodiment of the invention, the total power consumption control model of all the air conditioning systems takes various factors such as a power grid dispatching instruction, the relation between the power consumption and the indoor temperature and humidity of a building, a building body, a temperature and humidity comfort degree interval and the like into consideration, and the power consumption of the air conditioning systems can be effectively reduced under the condition of meeting the power grid dispatching requirement and meeting the comfort degree requirement of users as much as possible.
In an embodiment, the power grid dispatching command may be an actual power grid dispatching command directly obtained from a power grid dispatching system, and at this time, the power grid dispatching system needs to be connected to the cloud platform to transmit the actual power grid dispatching command to the cloud platform.
The actual grid dispatching command may be obtained at a time earlier than the start time of the power demand response of the air conditioning system or close to the start time of the power demand response of the air conditioning system.
In one embodiment, the difference between the obtaining time of the actual grid dispatching command and the starting time of the power demand response of the air conditioning system may be less than or equal to a set time, for example, ten minutes or half an hour, that is, the obtaining time of the actual grid dispatching command may be close to the starting time of the power demand response of the air conditioning system. The cloud platform carries out collaborative optimization on control parameters of all air conditioning systems in an indoor temperature and humidity comfort interval corresponding to each air conditioning system through a built-in relation model between the power consumption of all air conditioning systems and the indoor temperature and humidity of the building, and searches for a control strategy which meets the power grid dispatching requirement and simultaneously keeps all the systems in the comfort interval.
Fig. 4 is a flowchart illustrating a method for establishing an overall power consumption control model according to an embodiment of the invention. As shown in fig. 4, the obtaining time of the actual grid dispatching command may be close to the starting time of the power demand response of the air conditioning system, and the total power consumption control model may simultaneously satisfy: in step S140, the method for building a general power consumption control model of all the air conditioning systems by combining the maximum total power consumption value, the power consumption of the air conditioning system, the building indoor temperature and humidity relationship model, the building body model and a set temperature and humidity comfort level section may include the steps of:
s1411: establishing a total power consumption objective function of all the air conditioning systems according to a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building;
s1412: establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval;
s1413: establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
s1414: and generating the total power consumption control model by combining the total power consumption target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
In the above step S1411, the minimum total power consumption in the total power consumption objective function may refer to the minimum total power consumption of all the air conditioning systems in the unit time, and accordingly, in the above step S1413, the maximum total power consumption value may be the maximum total power consumption allowed by the power supply grid in the unit time.
In the embodiment of the invention, the indoor temperature and humidity constraint function and the total power consumption constraint function can be used for seeking the control parameters of the air conditioning system which simultaneously meet the requirement of the power grid dispatching instruction and the requirement of the comfort degree interval of the user, and the total power consumption objective function can further select the control parameters of the air conditioning system with the lowest power consumption from the obtained multiple groups of control parameters which meet the requirements of the power grid dispatching instruction and the comfort degree.
In a specific embodiment, when the time of obtaining the power grid dispatching instruction is close to the power demand response time of the air conditioning system for the actual power grid dispatching instruction, the total power consumption control model obtained by using the method shown in fig. 4 may be:
or
Tpj,Hdj∈Sj， (2)
Wherein, in the formula (1),(in terms of total electricity usage of all air conditioning systems per unit time) and(in terms of the total electricity rate of all the air conditioning systems per unit time) is the total electricity usage objective function obtained by the above step S1411; formula (2) is the indoor temperature and humidity constraint function of the building obtained in step S1412; equation (3) is the total power consumption constraint function of all the air conditioning systems obtained through the above-described step S1413. Pe is the total electricity consumption of all the air conditioning systems in unit time; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; m is the number of the air conditioning systems, m is more than or equal to 1, and m is a positive integer; pejIs the power consumption of the air conditioning system j in a unit time; t ispjIs the building indoor temperature of air conditioning system j; ce is the total electricity charge used by all the air conditioning systems per unit time; cejIs the electricity charge used by the air conditioning system j in a unit time; hdjIs the building indoor humidity of air conditioning system j; sjIs the set temperature and humidity comfort interval of the air conditioning system j; pemax is the maximum total power usage value of all the air conditioning systems per unit time.
It should be noted that, in each embodiment of the present invention, the power consumption Pe of the air conditioning system jjThe total power consumption Pe and the maximum total power consumption value Pe max can represent the power consumption, namely the power consumption, of the air conditioning system in unit time, and can also represent the power consumption in the whole power demand response time period; similarly, the total electricity rate Ce and the electricity rate Ce used by the air conditioning system jjThe power consumption charge of the air conditioning system in unit time can be represented, and the power consumption charge in the whole power demand response time period can also be represented. The specific metering mode of the electric quantity or the electric charge can be determined according to the requirement.
In one embodiment, with the general power consumption control model obtained by the method shown in fig. 4, in the step S150, when the control parameter of the air conditioning system is calculated, there is no solution, that is, the general power consumption control model cannot satisfy: the indoor target temperature and humidity of the building are located in the set temperature and humidity comfort degree interval, and the total power consumption of all the air conditioning systems is smaller than the maximum total power consumption value. At this time, preferably, the power grid dispatching command requirement is preferentially met, and then the air conditioning system control parameter with the comfort degree closest to the user comfort degree requirement is searched.
Fig. 5 is a flowchart illustrating a method for establishing an overall power consumption control model according to an embodiment of the invention. As shown in fig. 5, the difference between the obtaining time of the actual grid dispatching command and the starting time of the power demand response of the air conditioning system is less than or equal to a set time, that is, in a case of approaching, the total power consumption control model simultaneously satisfies: in step S140, the method for establishing all the general power consumption control models of the air conditioning system, which is based on the maximum total power consumption value, the power consumption of the air conditioning system and the building indoor temperature and humidity relationship model, the building body model and a set temperature and humidity comfort interval, may include the steps of:
s1415: according to the building body model and the set temperature and humidity comfort level interval, establishing an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature and humidity comfort level interval;
s1416: establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
s1417: and establishing a total power consumption control model which preferentially meets the constraint function of the total power consumption by combining the target function which is minimally deviated from the set temperature-humidity comfort degree interval and the constraint function of the total power consumption.
In step S1416, the total power consumption in the total power consumption constraint function may refer to the total power consumption of all the air conditioning systems in unit time, and accordingly, the maximum total power consumption value may refer to the maximum total power consumption allowed by the power supply grid for all the air conditioning systems in unit time.
In the embodiment of the invention, the total power consumption control model cannot meet the requirements of temperature and humidity comfort levels and power dispatching instructions at the same time, the requirements of power grid dispatching instructions can be met preferentially through the total power consumption constraint functions of all air conditioning systems, and the temperature and the humidity which are closest to the set temperature and humidity comfort level interval can be sought under the condition of meeting the requirements of the power grid dispatching instructions by means of minimum deviation of the indoor temperature and the indoor humidity of a building from the target function of the set temperature and humidity comfort level interval, so that the indoor temperature and humidity comfort level of a user is improved as much as possible. It is worth mentioning that the power dispatching command and the grid dispatching command may have the same meaning.
In a specific embodiment, for an actual power grid dispatching instruction, under the condition that the requirement of the power grid dispatching instruction is preferentially met and the temperature, humidity and comfort of a user are met as much as possible, the total power consumption control model obtained by using the method shown in fig. 5 may be:
minρ((Tpj,Hdj),Sj)， (4)
wherein, the formula (4) is an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature and humidity comfort interval obtained in the step S1415, and the formula (5) is a total power consumption constraint function of all the air conditioning systems obtained in the step S1416; t ispjIs the building indoor temperature of air conditioning system j; hdjIs the building indoor humidity of air conditioning system j; sjIs the set temperature and humidity comfort interval of the air conditioning system j; pe is the total electricity consumption of all the air conditioning systems in unit time; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; m is the number of the air conditioning systems, m is more than or equal to 1, and m is a positive integer; pejIs the power of the air conditioning system j per unit time; pemax is the maximum total power consumption value of all the air conditioning systems in unit time; rho is the temperature and humidity deviation set temperature and humidity comfort level interval S in the building roomjAs a function of (c).
Similarly, the above-described electric power consumption Pe of the air conditioning system jjThe total power consumption Pe and the maximum total power consumption Pemax can represent the air conditioning system in unit timeThe power consumption, i.e. the power consumption, may also represent the power consumption in the whole power demand response time period, and the specific metering manner may be determined according to the requirement.
In another embodiment, the difference between the time of acquiring the actual grid dispatching command and the starting time of the power demand response of the air conditioning system is greater than a set time, such as ten minutes, half an hour, or an hour, and at this time, the total power consumption control model may consider the cold storage capacities of the water system of the air conditioning system and the building body. Due to the water system of the air conditioning system and the cold accumulation capacity of the building body, the running state of the air conditioning system can be adjusted in advance after a power grid dispatching instruction is obtained and before the response of the air conditioning power demand begins, so that the electric charge of the air conditioning system is further reduced under the condition of considering the indoor temperature and humidity demands of users. For example, if the air conditioning system changes the load on the unit or stops operating for a period of time, the temperature and humidity in the building room may remain at or near the comfort zone for a period of time.
In one embodiment, in a case that a difference between an acquisition time of the actual grid dispatching command and a start time of the power demand response of the air conditioning system is greater than a set time, the total power consumption control model can simultaneously satisfy: the method for generating the total power consumption control model may have similar steps to the method shown in fig. 4, where the indoor target temperature and humidity of the building are within the set temperature and humidity comfort interval and the total power consumption of all the air conditioning systems is less than the maximum total power consumption value.
The difference between the two is that for the condition that the initial time of the power demand response is advanced, the total power consumption objective function of all the air conditioning systems can be an integral model due to the consideration of the water systems of the air conditioning systems and the cold storage capacity of the body of the building; in the case that the starting time of the power demand response is close to the obtaining time of the actual power grid dispatching command, the total power consumption objective function of all the air conditioning systems can be a summation model because the cold storage capacity is not considered.
Fig. 6 is a flowchart illustrating a method for establishing an overall power consumption control model according to an embodiment of the invention. As shown in fig. 6, the method for establishing the general power consumption control model in consideration of the cold storage capacity of the water system of the air conditioning system and the building body for an actual power grid dispatching command under the condition of meeting the requirements of the temperature, humidity and comfort level and the power grid dispatching command simultaneously may include the following steps:
s1421: establishing a total power consumption objective function of all the air conditioning systems according to a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building, wherein the total power consumption objective function is an integral model;
s1422: establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval;
s1423: establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
s1424: and generating the total power consumption control model by combining the total power consumption target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
In step S1421, the minimum total power consumption in the total power consumption objective function may refer to the total power consumption of all air conditioning systems after all power grid dispatching time periods/air conditioning system power demand response time periods have elapsed. In step S1423, the maximum total power consumption value may refer to a maximum total power consumption allowed by the power grid for all air conditioning systems in a unit time.
In the embodiment of the invention, the total power consumption target function of all the air conditioning systems after the cold storage capacity is considered can be more accurately represented through the integral model. The change condition of the control parameters of the air conditioning system between the start of the power demand response of the air conditioning system can be calculated through the general power consumption control model, so that the running state of the air conditioning system can be regulated in advance, and the air conditioning system can be regulated and controlled better in the power demand response period.
For example, in summer, the actual grid dispatching command is obtained two hours in advance, and the actual grid dispatching command can be that the electricity price is increased within one hour after the power demand response starts. At this time, the temperature of the fresh air provided by the air conditioning system can be reduced as much as possible within the temperature comfort interval within two hours in advance, and the temperature of the fresh air provided by the air conditioning system can be turned off or increased as much as possible within one hour of the power demand response. Since the indoor temperature is low before, even if the air conditioner is turned off in the power demand response period, the comfort level of the indoor temperature can be ensured due to the above cold storage capacity, and at the same time, the high-price power supply using the power demand response period is also avoided. Therefore, the beneficial effects of meeting the requirement of a power grid dispatching instruction, improving the indoor temperature and humidity comfort level and reducing the electricity consumption cost are achieved.
In a specific embodiment, regarding an actual power grid dispatching command, when the cold storage capacity is considered and the temperature and humidity comfort requirement and the power dispatching command requirement are simultaneously satisfied, the total power consumption control model obtained by the method shown in fig. 6 may be:
or
Wherein,
wherein, ts＜t＜te。
In the above-mentioned formula (6),(in terms of electric power consumption) and(power consumption representation) is an integral model of a total power consumption objective function and a total power consumption objective function respectively; formula (7) is an indoor temperature and humidity constraint function of the building; formula (8) is a constraint function of the total power consumption of all the air conditioning systems, and can be expressed by electric power; t is t0Obtaining time of a power grid dispatching instruction; t is teIs the end time of the air conditioning system power demand response; t represents a time; t is tsIs a starting time of a power demand response of the air conditioning system; petThe total power consumption of all the air conditioning systems at the moment t; cetIs the total electricity charge used by all the air conditioning systems in the unit time at the time t; j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; m is the number of the air conditioning systems, m is more than or equal to 1, and m is a positive integer;is the power consumption of the air conditioning system j at time t;is the electricity charge used by the air conditioning system j in the unit time at time t;is the building indoor temperature of the air conditioning system j at time t;is the building indoor humidity of the air conditioning system j at time t; sjIs the set temperature and humidity comfort interval of the air conditioning system j;is the maximum total electrical power used by all the air conditioning systems per unit time at time t.
When the difference between the obtaining time of the actual grid dispatching command and the starting time of the power demand response of the air conditioning system is greater than a set time, the total power consumption control model obtained by using the method shown in fig. 6 is a no-solution condition when calculating the control parameters of the air conditioning system in the step S150, that is, the total power consumption control model cannot satisfy the following conditions: the indoor target temperature and humidity of the building are located in the set temperature and humidity comfort degree interval, and the total power consumption of all the air conditioning systems is smaller than the maximum total power consumption value. At this time, a method similar to that shown in fig. 5 may be adopted to establish the total power consumption control model, that is, the power grid dispatching command requirement is preferentially met, and then the air conditioning system control parameter with the comfort level closest to the user comfort level requirement is sought.
Under the condition that the difference value between the obtaining time of the actual power grid dispatching instruction and the starting time of the power demand response of the air conditioning system is greater than a set time, the general power consumption control model simultaneously meets the following conditions: the method for establishing the total power consumption control model may have similar steps to those in fig. 5, where the indoor target temperature and humidity of the building are outside the set temperature and humidity comfort interval and the total power consumption of all the air conditioning systems is less than the maximum total power consumption value. The difference is that, for the case of obtaining the power grid dispatching command in advance, the objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature and humidity comfort interval may be an integral model due to consideration of the cold storage capacities of the water system of the air conditioning system and the building body, and for the case of obtaining the power grid dispatching command time close to the power demand response time of the air conditioning system, the objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature and humidity comfort interval may be a summation model in the step S1415.
FIG. 7 is a flowchart illustrating a method for building an overall power consumption control model according to an embodiment of the invention. As shown in fig. 7, after considering the cold storage capacity for an actual power grid dispatching command, the method for establishing the general power consumption control model under the condition that the requirement of the power grid dispatching command can be met but the requirement of the temperature and humidity comfort interval cannot be met may include the steps of:
s1425: according to the building body model and the set temperature-humidity comfort level interval, establishing an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature-humidity comfort level interval, wherein the objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature-humidity comfort level interval is an integral model;
s1426: establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
s1427: and establishing a total power consumption control model which preferentially meets the constraint function of the total power consumption by combining the target function which is minimally deviated from the set temperature-humidity comfort degree interval and the constraint function of the total power consumption.
In step S1426, the total power consumption in the total power consumption constraint function may refer to the total power consumption of all the air conditioning systems in unit time, and accordingly, the maximum total power consumption value may refer to the total power consumption allowed by the power supply grid in unit time for all the air conditioning systems.
In the embodiment of the invention, after the cold storage capacity of a water system of an air conditioning system and a building body is considered can be more accurately represented by the integral model, the indoor temperature and humidity of the building are minimally deviated from the target function of the set temperature and humidity comfort level interval, and thus accurate air conditioning system control parameters are obtained.
In a specific embodiment, by using the method shown in fig. 7, the total power consumption control model that preferentially meets the requirement of the power grid dispatching instruction and that meets the requirement of the user on the temperature and humidity comfort level to the greatest extent can be obtained as follows:
wherein, ts＜t＜te。
Formula (9) is an integral model of an objective function of the building in which the indoor temperature and humidity are minimally deviated from the set temperature and humidity comfort interval; formula (10) is a total power consumption constraint function for all the air conditioning systems;is the building indoor temperature of the air conditioning system j at time t;is the building indoor humidity of the air conditioning system j at time t; rho is the temperature and humidity deviation set temperature and humidity comfort level interval S in the building roomjA function of (a); sjIs the set temperature and humidity comfort interval of the air conditioning system j; petThe total electricity consumption of all the air conditioning systems in unit time at the time t;is the maximum total power consumption value of all the air conditioning systems in unit time at the time t; t is t0Obtaining time of a power grid dispatching instruction; t is teIs the end time of the air conditioning system power demand response; t represents a time; t is tsIs the starting time of the power demand response of the air conditioning system. It is worth noting that the amount of electricity used per unit time has the same meaning as power.
The power grid dispatching instruction in each embodiment may be an actual power grid dispatching instruction obtained from a power grid dispatching system. In order to better respond to the power demand, in other embodiments, the scheduling instruction of the power grid scheduling system may be predicted, and the predicted power grid scheduling instruction may be used to control the operating state of the air conditioning system. Therefore, the power grid dispatching instruction may be a predicted power grid dispatching instruction. A plurality of predicted power grid dispatching instructions can be obtained by predicting the dispatching instructions of the power grid dispatching system, different predicted power grid dispatching instructions have respective occurrence probabilities, and at the moment, each air-conditioning system can respond to power demand according to the plurality of predicted power grid dispatching instructions.
In an embodiment, the predicted grid scheduling command may include a scheduling time, a scheduling load, and a probability of occurrence of the scheduling command, and may be generated by a grid load prediction model. The power grid load prediction model can be an empirical model which is formed by fitting according to historical power grid load and time relation data, historical power grid load and electricity price relation data and historical power grid load and meteorological environment relation data. The renewable energy power generation amount can be calculated based on a physical model according to meteorological information. And the command prediction of the dispatching adjustment of the power grid can be carried out by comprehensively considering the factors and the data. In other embodiments, other grid prediction models may be used to predict grid loads and schedules.
The grid load prediction model may be a difference between the electrical power of the consumed grid load and the distributed energy generation power. The electric power consumed by the user is related to time, electricity price, environment (temperature, humidity) and other factors, and the distributed generation power can comprise internal combustion engine power generation, solar power generation, wind power generation and the like. The solar power generation and the wind power generation are related to environmental factors such as illumination, wind speed and the like, and have large changes, so that the power grid load in the power grid load prediction model can be a function of time, electricity price, environmental temperature, environmental humidity, illumination and wind power, namely:
Q＝f(t,Ct,Tp,Hd,Rd,Fv)。
wherein Q is the load of the power grid, t is the time, Ct is the price of electricity at the time, Tp is the ambient temperature, Hd is the ambient humidity, Rd is the illuminance, and Fv is the wind power.
The power supply of the power grid can be limited by the maximum power of the generator and the maximum load capacity of the power transmission and transformation equipment. When the power supply of the power grid cannot meet the load of the power grid, the power grid scheduling is needed, so the power grid scheduling is performed on the basis that the power load exceeds a certain amount. Therefore, the grid dispatching command can also be expressed as a probability function of time, electricity price, ambient temperature, ambient humidity, illumination and wind power. The probability density function of the occurrence of grid load x that cannot be met at time t in the future can be expressed as: pt (x) f (t, Ct, Tp, Hd, Rd, Fv). The probability function Pt (x) can be obtained by carrying out model identification according to the actual power grid dispatching instruction and the environmental information in the historical data.
In one embodiment, the predicted power grid scheduling instruction may be generated according to load data of a power supply power grid of the air conditioning system and/or historical operation parameter data of the air conditioning system based on one or more parameters of time of day, electricity price, outdoor temperature, outdoor humidity, outdoor illuminance and wind power, and the occurrence probability of the predicted power grid scheduling instruction may be calculated. Therefore, when the predicted power grid dispatching instruction is generated, the power grid load data and the environmental data are fully considered, and the prediction accuracy of the predicted power grid dispatching instruction can be improved.
In one embodiment, for the above predicted grid dispatching command, the total power consumption control model simultaneously satisfies: the indoor target temperature and humidity of the building are located in the set temperature and humidity comfort level interval, the total power consumption of all the air conditioning systems is smaller than the maximum total power consumption value, and the total power consumption control model can be obtained by utilizing a method similar to that shown in fig. 4 or fig. 6 under the condition that the cold storage capacity of a water system of the air conditioning system and the cold storage capacity of the building body are considered. The difference between the method for obtaining the total power consumption control model in the embodiment of the present invention and the method shown in fig. 4 is that, in addition to the fact that the minimum total objective function of all air conditioning systems adopts an integral model, the integral model takes into account a plurality of predicted power grid scheduling instructions and their respective occurrence probabilities.
Fig. 8 is a flowchart illustrating a method for establishing an overall power consumption control model according to an embodiment of the invention. As shown in fig. 8, the method for establishing the general power control models of all air conditioning systems according to the predicted power grid dispatching command, the temperature and humidity requirements, and the predicted power grid dispatching command requirements can include the following steps:
s1431: establishing a total power consumption electric charge/electric quantity objective function of all the air conditioning systems according to the occurrence probability of each predicted power grid dispatching instruction and a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building, wherein the total power consumption electric charge/electric quantity objective function is an integral model;
s1432: establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval;
s1433: establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
s1434: and generating the total power consumption control model by combining the total power consumption electric charge/electric quantity target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
In the step S1431, the total power consumption rate/amount in the total power consumption rate/amount objective function may refer to a total power consumption rate/amount from the obtaining of the predicted grid scheduling command to the ending of the air conditioning system power demand response, or may refer to a total power consumption rate/amount from the beginning of the air conditioning system power demand response to the ending of the air conditioning system power demand response.
According to the embodiment of the invention, the power demand response of the air conditioning system is controlled according to the predicted power grid dispatching instruction, so that the power consumption of the air conditioning system can be reduced as much as possible while the requirement of the comfort degree of a user is ensured.
In one embodiment, dynamic simulation of the thermal environment of the building can be performed according to external link parameters and historical air conditioner operation data, and collaborative optimization of a control curve in a time period can be performed on control parameters of the cloud platform air conditioning system according to predicted power grid scheduling time and probability. If the control of the air conditioning system is performed according to the dispatching command of the power grid, generally, the power consumption or the cost of the air conditioning system increases in a period of time, and the value of the increase is defined as the power consumption Δ Pe or the cost Δ Ce, then:
ΔPe＝Pe-Pe0，
ΔCe＝Ce-Ce0。
wherein Pe and Ce are the total power consumption Pe considered in the methodtThe results obtained after optimization after the constraint conditions of (1), Pe0 and Ce0 are the results obtained in the above method without considering the total power consumption PetThe constraint condition of (2) to obtain an optimization result. On the basis, the probability distribution of the predicted scheduling instructions is considered, the lowest expected value of the air conditioning system cost can be considered in optimization calculation, n possible scheduling instruction situations can be assumed to be predicted, and the corresponding probability is Pi。
In a specific embodiment, for predicting the grid dispatching command, the total power consumption control model established by using the method shown in fig. 8 may be:
wherein, ti,s＜t＜te。
Equation (11) is an integral model of the total electricity rate objective function obtained by step S1431; formula (12) is the indoor temperature and humidity constraint function of the building obtained in step S1432; formula (13) is the total power consumption constraint function of all the air conditioning systems obtained by step S1433; i is predictive grid dispatchingThe serial number of the instruction, i is more than or equal to 1 and less than or equal to n, and i and n are positive integers; piPredicting the occurrence probability of a power grid dispatching instruction i; t represents a time; t is t0Predicting the acquisition time of a power grid dispatching instruction; t is teIs the end time of the air conditioning system power demand response; cei,tThe total electricity charge used by all the air conditioning systems in the unit time at the moment t and under the condition of predicting a power grid dispatching instruction i;predicting the building indoor temperature of an air conditioning system j under the condition of a power grid dispatching instruction i at the moment t;predicting the building indoor humidity of the air conditioning system j under the condition of the power grid dispatching instruction i at the moment t; siThe method is a set temperature and humidity comfort level interval under the condition of predicting a power grid dispatching instruction i; pei,tThe total power consumption of all the air conditioning systems is within unit time at the moment t and under the condition of predicting a power grid dispatching instruction i;the maximum total power utilization value of all the air conditioning systems is within unit time at the time t and under the condition of predicting a power grid dispatching instruction i; t is ti,sThe time is the starting time of the air conditioning system for responding to the predicted scheduling command i with the power demand.
In other embodiments, for the predicted power grid dispatching instruction, when the medium power consumption control model established by the method shown in fig. 8 is not solved, the total power consumption control model established by the method similar to that shown in fig. 7 may be used to control that the temperature and humidity comfort level requirement of the user is met as much as possible under the condition that the predicted power grid dispatching instruction requirement is met, which is not described herein again.
The relation model of the power consumption of the air conditioning system and the indoor temperature and humidity of the building can mean a relation model of the minimum power consumption of the air conditioning system and the temperature and humidity by keeping the indoor temperature and humidity of the building at a certain temperature and humidity.
In the above embodiments, in the case of not considering the cold storage factor, the relationship model between the power consumption of the air conditioning system and the indoor temperature and humidity of the building may be:
Pej＝min(Pj chiller+Pj pump+Pj tower+Pj fan)， (14)
s.t.Tj p≤Tj p0，Hj d≤Hj d0。
in formula (14), PejRefers to the electricity consumption of the air conditioning system j; pj chillerIs the electricity consumption of the refrigerating unit of the air-conditioning system j; pj pumpThe power consumption of a refrigeration cooling water pump of the air conditioning system j is shown; pj towerThe power consumption of the cooling tower of the air-conditioning system j; pj fanThe power consumption of a tail end fan of the air conditioning system j is shown; s.t. denotes constrained; t isj pIs the building indoor temperature of air conditioning system j; t isj p0Is the building indoor target temperature of air conditioning system j; hj dIs the building indoor humidity of air conditioning system j; hj d0Is the building indoor target humidity for air conditioning system j. The above-mentioned electric quantity and electric quantity can be measured by power or power consumption.
Under the condition of considering the cold storage factor, the relation model of the power consumption of the air conditioning system and the indoor temperature and humidity of the building can be as follows:
s.t.Tj p≤Tj p0，Hj d≤Hj d0；
or
s.t.Tj p≤Tj p0，Hj d≤Hj d0。
Wherein j is the serial number of the air conditioning system, j is more than or equal to 1, and j is a positive integer; equation (15) is the elapsed power demand response time teJ electricity consumption of the air conditioning system; t is the response time of the air conditioning system j; t is teIs the end time of the power demand response of the air conditioning system j; pj,t chillerIs the electricity consumption of the refrigerating unit of the air conditioning system j in the unit time at the time t; pj,t pumpThe electricity consumption of the refrigeration cooling water pump of the air conditioning system j in unit time at the time t; pj,t towerThe electricity consumption of the cooling tower of the air conditioning system j in unit time at the moment t; pj,t fanThe power consumption of a tail end fan of the air conditioning system j in unit time at the moment t; s.t. denotes constrained; t isj pIs the building indoor temperature of air conditioning system j; t isj p0Is the building indoor target temperature of air conditioning system j; hj dIs the building indoor humidity of air conditioning system j; hj d0Is the building indoor target humidity for air conditioning system j; equation (16) is the elapsed power demand response time teTotal electricity charge used by air conditioning system j; ctIs the electricity rate at time t. The electricity consumption of each part of the air conditioning system can be measured by power or power consumption.
In the above embodiments, the building body model may be used to obtain the indoor temperature and the indoor humidity that change with the difference in the structure of the building, the indoor environment, and the indoor temperature and humidity contribution data of the air conditioning system to the building. For example, the building ontology model may be:
in formulas (17) to (18), C is air heat fusion; v is the total building indoor air capacity of the air conditioning system; t ispIs the building indoor temperature of the air conditioning system; t is a time variable; Δ Hf＝CFf(Tf-Tp) Is the fresh air heat exchange quantity of the air conditioning system; qc＝CFc(Tc-Tp) Is the heat exchange capacity of the indoor fan coil of the air conditioning system; qt＝α(Te-Tp) Is the indoor and outdoor heat exchange capacity of the building of the air conditioning system; qiIs the indoor heat source heat dissipation of the air conditioning system; ffIs the fresh air flow rate; t isfIs the fresh air outlet temperature; fcIs the circulating air flow rate; t iscIs the outlet air temperature of the circulating air, α is the comprehensive heat exchange coefficient of the window wall, TeIs the building outdoor temperature of the air conditioning system; ρ is the air density; v is the total building indoor air capacity of the air conditioning system; hdIs the building indoor moisture content of the air conditioning system; t is a time variable; ffIs the fresh air flow rate; wfThe moisture content of the fresh air outlet; fcIs the circulating air flow rate; wcIs the moisture content of the air outlet of the circulating air; and w is the indoor human body and object moisture dissipation capacity of the building of the air conditioning system.
Fig. 9 is a flowchart illustrating a power demand response control method for an air conditioning system based on a cloud platform according to an embodiment of the present invention. As shown in fig. 9, the air conditioning system may obtain the actual grid schedule or may predict the grid schedule command. When an actual power grid dispatching instruction is not received, calculating control parameters of each air conditioning system in the period from the current time when the dispatching prediction response time is finished according to the predicted power grid dispatching instruction, and calculating the control parameters of each air conditioning system in the cloud platform in real time according to the obtained control parameters of each air conditioning system, wherein information such as indoor and outdoor temperature and humidity, air conditioning state and the like used when the control parameters of the air conditioning systems are calculated in real time can be obtained in real time or can be obtained through prediction. If an actual power grid scheduling instruction is acquired, network related information such as indoor and outdoor temperature and humidity, air conditioner states and the like can be acquired at the same time, whether the time for receiving the actual power grid scheduling instruction is earlier than the time for requiring response of an air conditioner system is judged, if yes, control parameters of all air conditioner systems in the cloud platform are calculated in real time, and if not, the control parameters of all air conditioner systems in the time period from the time for receiving the actual power grid scheduling instruction to the time for finishing response are calculated.
According to the air conditioning system power demand response control method based on the cloud platform, the power consumption situation among the air conditioning systems is coordinated by comprehensively considering the power grid dispatching instruction requirement, the relation between the power consumption of the air conditioning system and the indoor temperature and humidity of the building and the temperature and humidity comfort degree interval of the building body and users, the total power consumption control model which meets the power grid dispatching instruction requirement and meets the temperature and humidity comfort degree requirement of the users as far as possible can be obtained, and the operating parameters of the air conditioning system are adjusted through the total power consumption control model, so that a better air conditioning system power demand response effect can be achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A cloud platform-based air conditioning system power demand response control method is characterized by comprising the following steps of:
determining the maximum total power utilization value of all the air conditioning systems according to a power grid dispatching instruction; the maximum total electricity utilization value is an upper electricity utilization limit of all the air conditioning systems when the air conditioning systems respond to the electricity demand;
establishing a relation model between the power consumption of the air conditioning system and the indoor temperature and humidity of the building according to the indoor target temperature and humidity of the air conditioning system;
building a building body model based on the structure of the building, the indoor environment and the contribution data of the air conditioning system to the indoor temperature and humidity of the building respectively so as to calculate the indoor temperature and humidity which dynamically change;
establishing a general power consumption control model of all the air conditioning systems by combining the maximum total power consumption value, the power consumption of the air conditioning systems, a building indoor temperature and humidity relation model, the building body model and a set temperature and humidity comfort level interval;
and respectively inputting the real-time operation parameters of the air conditioning system, the real-time power load of the air conditioning system and the real-time indoor and outdoor temperature and humidity data of the building into the general power control model, calculating to obtain a control parameter change curve of the air conditioning system, and controlling the power demand response of the air conditioning system according to the control parameter change curve.
2. The cloud platform based power demand response control method for the air conditioning system according to claim 1, wherein the grid dispatching command is an actual grid dispatching command obtained from a grid dispatching system, and wherein the cloud platform is connected to the grid dispatching system.
3. The cloud platform-based power demand response control method for the air conditioning system according to claim 2, wherein a difference between an acquisition time of the actual grid scheduling command and a start time of the power demand response of the air conditioning system is less than or equal to a set time;
the general electricity consumption control model simultaneously satisfies the following conditions: the indoor target temperature and humidity of the building are positioned in the set temperature and humidity comfort degree interval, the total power consumption of all the air conditioning systems is less than the maximum total power consumption value,
combining the maximum total electricity utilization value, the electricity consumption of the air conditioning system and the indoor temperature and humidity relation model of the building, the building body model and a set temperature and humidity comfort interval, establishing all the total electricity utilization control models of the air conditioning system, including:
establishing a total power consumption objective function of all the air conditioning systems according to a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building;
establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval;
establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
and generating the total power consumption control model by combining the total power consumption target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
4. The cloud platform-based power demand response control method for the air conditioning system according to claim 2, wherein a difference between an acquisition time of the actual grid scheduling command and a start time of the power demand response of the air conditioning system is less than or equal to a set time;
the general electricity consumption control model simultaneously satisfies the following conditions: the indoor target temperature and humidity of the building are positioned outside the set temperature and humidity comfort degree interval, the total power consumption of all the air conditioning systems is smaller than the maximum total power consumption value,
combining the maximum total electricity utilization value, the electricity consumption of the air conditioning system and the indoor temperature and humidity relation model of the building, the building body model and a set temperature and humidity comfort interval, establishing all the total electricity utilization control models of the air conditioning system, including:
according to the building body model and the set temperature and humidity comfort level interval, establishing an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature and humidity comfort level interval;
establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
and establishing a total power consumption control model which preferentially meets the constraint function of the total power consumption by combining the target function which is minimally deviated from the set temperature-humidity comfort degree interval and the constraint function of the total power consumption.
5. The cloud platform-based power demand response control method for the air conditioning system according to claim 2, wherein a difference between an acquisition time of the actual grid scheduling command and a start time of the power demand response of the air conditioning system is greater than a set time; the general electricity consumption control model takes the water system of the air conditioning system and the cold storage capacity of the body of the building into consideration.
6. The cloud platform-based air conditioning system power demand response control method of claim 5, wherein the total power consumption control model simultaneously satisfies: the indoor target temperature and humidity of the building are positioned in the set temperature and humidity comfort degree interval, the total power consumption of all the air conditioning systems is less than the maximum total power consumption value,
combining the maximum total electricity utilization value, the electricity consumption of the air conditioning system and the indoor temperature and humidity relation model of the building, the building body model and a set temperature and humidity comfort interval, establishing all the total electricity utilization control models of the air conditioning system, including:
establishing a total power consumption objective function of all the air conditioning systems according to a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building, wherein the total power consumption objective function is an integral model;
establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval;
establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
and generating the total power consumption control model by combining the total power consumption target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
7. The cloud platform-based air conditioning system power demand response control method of claim 5, wherein the total power consumption control model simultaneously satisfies: the indoor target temperature and humidity of the building are positioned outside the set temperature and humidity comfort degree interval, the total power consumption of all the air conditioning systems is smaller than the maximum total power consumption value,
combining the maximum total electricity utilization value, the electricity consumption of the air conditioning system and the indoor temperature and humidity relation model of the building, the building body model and a set temperature and humidity comfort interval, establishing all the total electricity utilization control models of the air conditioning system, including:
according to the building body model and the set temperature-humidity comfort level interval, establishing an objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature-humidity comfort level interval, wherein the objective function of the minimum deviation of the indoor temperature and humidity of the building from the set temperature-humidity comfort level interval is an integral model;
establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
and establishing a total power consumption control model which preferentially meets the constraint function of the total power consumption by combining the target function which is minimally deviated from the set temperature-humidity comfort degree interval and the constraint function of the total power consumption.
8. The cloud platform-based air conditioning system power demand response control method of claim 1, wherein the grid scheduling command is a predictive grid scheduling command; and the air conditioning system carries out power demand response according to the plurality of predicted power grid dispatching instructions.
9. The cloud platform-based air conditioning system power demand response control method of claim 8, wherein the total power consumption control model simultaneously satisfies: the indoor target temperature and humidity of the building are positioned in the set temperature and humidity comfort degree interval, the total power consumption of all the air conditioning systems is less than the maximum total power consumption value,
combining the maximum total electricity utilization value, the electricity consumption of the air conditioning system and the indoor temperature and humidity relation model of the building, the building body model and a set temperature and humidity comfort interval, establishing all the total electricity utilization control models of the air conditioning system, including:
establishing a total power consumption electric charge/electric quantity objective function of all the air conditioning systems according to the occurrence probability of each predicted power grid dispatching instruction and a relation model of the power consumption of the air conditioning systems and the indoor temperature and humidity of the building, wherein the total power consumption electric charge/electric quantity objective function is an integral model;
establishing an indoor temperature and humidity constraint function of the building according to the building body model and the set temperature and humidity comfort level interval;
establishing a total power consumption constraint function of all the air conditioning systems based on a power consumption of the air conditioning systems and a building indoor temperature and humidity relation model thereof by taking the maximum total power consumption value as a maximum value;
and generating the total power consumption control model by combining the total power consumption electric charge/electric quantity target function, the indoor temperature and humidity constraint function and the total power consumption constraint function.
10. The cloud platform-based air conditioning system power demand response control method of claim 9, wherein the method further comprises:
and generating the predicted power grid scheduling instruction according to load data of a power supply power grid of the air conditioning system and/or historical operating parameter data of the air conditioning system based on one or more parameters of time, electricity price, outdoor temperature, outdoor humidity, outdoor illumination and wind power, and calculating the occurrence probability of the predicted power grid scheduling instruction.
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