CN112072637B - Intelligent and emergency bidirectional power distribution method for large power grid area - Google Patents
Intelligent and emergency bidirectional power distribution method for large power grid area Download PDFInfo
- Publication number
- CN112072637B CN112072637B CN202010729362.XA CN202010729362A CN112072637B CN 112072637 B CN112072637 B CN 112072637B CN 202010729362 A CN202010729362 A CN 202010729362A CN 112072637 B CN112072637 B CN 112072637B
- Authority
- CN
- China
- Prior art keywords
- signal
- module
- measurement
- control center
- power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
- H02J3/0012—Contingency detection
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02B90/20—Smart grids as enabling technology in buildings sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/242—Home appliances
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a large power grid area intelligent and emergency bidirectional power distribution method, which comprises the following steps: firstly, establishing a measurement and control center network; secondly, a measurement and control center software system is constructed, and a parameter setting module, a signal receiving module, a signal analyzing module, a signal output module and a learning optimization module are constructed in the measurement and control center; thirdly, the measurement and control center is put into use, and signals transmitted by all electrical components are processed through all modules of the measurement and control center; according to the invention, a measurement and control center network is constructed to monitor the power transmission and distribution conditions of each network point in the whole large power grid, and the power transmission and distribution conditions are compared with the planned power transmission and distribution parameters, and the power transmission and distribution plan is improved through comparison, so that the electric energy can be optimized and applied to a greater extent; through arranging the data of the whole measurement and control center, a visual image-text mode is formed, and the method has important reference significance for continuous improvement and scientific research of a subsequent power distribution plan.
Description
Technical Field
The invention belongs to the technical field of intelligent power distribution, and particularly relates to an intelligent and emergency bidirectional power distribution method for a large power grid region.
Background
The large power grid is a power network system which distributes electric energy from an electric field to a power utilization area, the electric energy is supplied to the required power utilization area in real time through reasonable distribution, the power distribution mode of the large power grid generally transmits electric quantity through high voltage, during the whole power transmission process, certain loss of power inevitably occurs, so that a compensation power is needed between the power consumption of the distribution area and the power transmission of the large power grid, meanwhile, in order to ensure the reasonability of the distribution electric quantity as much as possible, the statistics of the electric quantity used in the power distribution area is generally needed, the corresponding distribution plan is designated according to the statistical result, in the prior art, the adopted distribution statistics are generally counted by the total consumption of the regional users, the distribution method can meet the general distribution requirement, however, in practical application, the power distribution method in the prior art has certain disadvantages:
1. the power distribution method in the prior art only counts the total power consumption of a user, and the statistical method is relatively general and neglects the power consumption detail problem in real production and life, so that the statistical method is not careful, and the existing power distribution method causes certain phenomena of power distribution insufficiency and power distribution excess in the power distribution process by considering the power consumption time period, the power consumption season and the sudden power consumption situation;
2. the power distribution method in the prior art does not have the automatic learning and predicting capability, each power distribution plan is distributed according to the reported and summarized data, the time consumption is long, and effective scientific power distribution cannot be formed, so that the disadvantages and the further improvement of the power distribution method are avoided.
The present invention has been made in view of the above circumstances, and is directed to effectively solve the above problems.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art, and provide a large power grid area intelligent and emergency bidirectional power distribution method, which specifically comprises the following steps:
step one, establishing a measurement and control center network, and connecting each power transformation output signal with a computer terminal through a centralized signal transmitter to form a power transmission and distribution network framework capable of performing signal transmission;
step two, constructing a measurement and control center software system, converting each signal transmitted to a network center into a digital signal which can be processed, constructing a parameter setting module, a signal receiving module, a signal analysis module, a signal output module and a learning optimization module in the measurement and control center through software programming, and performing simulation test on each module; inputting an analog test signal through manual control, observing whether a feedback signal of a signal output module is consistent with manual control input information or not, if so, successfully testing, and completing the whole test process, so that the whole measurement and control center can be put into use;
step three, the measurement and control center is put into use, and signals transmitted by each electrical element are processed through each module of the measurement and control center, and the specific operation is as follows: the method comprises the steps of setting corresponding basic parameters according to each electrical appliance element in a signal transmission network in a parameter setting module, classifying received signals through a classification module, analyzing and comparing the classified signals through a signal analysis module to obtain a logic comparison result, converting the comparison result into executable feedback signals through a signal output module, and transmitting the executable feedback signals to each electrical appliance execution element to finish intelligent power distribution.
Preferably, in the second step, the parameter setting module is responsible for performing basic setting on parameters of each level of electrical components; the signal receiving module is responsible for classifying and storing the signals transmitted back by the centralized signal transmitter; the signal analysis module is responsible for carrying out logic calculation comparison on the classified and stored information, comparing the information with a reference parameter and carrying out logic judgment on a comparison result; the signal output module is responsible for converting the logic judgment result into an executable feedback signal and performing feedback transmission on the executable feedback signal to each electric appliance execution element; the learning optimization module carries out statistical processing on data of the whole measurement and control center, converts the data in each module into a chart, and provides a scientific basis for continuous research for intelligent power distribution.
Preferably, in the second step, the parameter setting module performs parameter basic setting including: rated output voltage of the power transmission station U1, planned output electric quantity of the power transmission station Q1, rated output voltage of the entire distribution area U2, planned output electric quantity of the entire distribution area Q2, rated output voltage of the district distribution area U3, planned output electric quantity of the district distribution area Q3;
setting the electricity consumption of the terminal user in a certain time period as QΔ t, wherein Δ t is a certain time period of the electricity consumption of the user in one day, setting t = K + t (n + 1) -tn, wherein tn is a time node of a certain cycle in one day, and t (n + 1) is a later time node relative to tn, and setting: n =1, t1= 5; n =2, t2= 8; n =3, t3= 11; n =4, t4= 13; n =5, t5= 15; n =6, t6= 18; n =7, t7=20, when t (n + 1) cycles to t1= 5;
where K is an augmentation parameter, K =0 when tn is some of 5, 8, 11, 13, 15, 18; when tn is 20, t (n + 1) =5, when K = 24;
setting the power consumption of a terminal user in one day as Qtd, wherein Qtd = F + H Σ Q Δ t, F is a seasonal temperature coefficient, the power consumption influenced by the temperature in spring and autumn is relatively low, F is set as 0, the power consumption influenced by the temperature in summer and winter is relatively high, and F is set as 10; h is a production coefficient, production is affected by light and vigorous seasons, the power consumption in the light seasons is low, the power consumption in the vigorous seasons is high, the H in the light seasons is set to be 1, and the H in the vigorous seasons is set to be 1.5-2;
the end user's power usage is set to Qtm in a month, Qts in a quarter, and Qty in a year.
Preferably, in the second step, the specific classification manner of the signal receiving module for classifying the input signal includes: dividing according to the voltage and current uploaded by an electric energy meter and the current statistical power consumption; and in the second mode, parameters in each high-voltage and low-voltage area are divided, and the voltage, the current and the whole electricity consumption are divided as the same group of data.
Preferably, in the second step, the specific calculation method of the classified and stored information by the signal analysis module includes: the method comprises the steps of counting the daily power consumption of users in each time period, calculating the daily power consumption of each user, accumulating the power consumption of the users in each time period in a certain day to obtain Qtd, calculating the monthly power consumption of each user, specifically, superposing the daily power consumption Qtd of the users to obtain Qtm, calculating the quarterly power consumption of each user, specifically, accumulating the quarterly monthly power consumption Qtm of the users to obtain Qts, calculating the annual power consumption of each user, specifically, accumulating the quarterly power consumption Qtm of the users to obtain Qty, calculating the daily, monthly and quarterly power consumption of all the users in a chip area, comparing the obtained result with the planned power distribution amount, and when the result is higher than the planned value, the next planned power distribution ratio can be properly adjusted up, and when the result is lower than the planned value, the next planned power distribution ratio can be properly adjusted.
Preferably, in the second step, the output signal generated by the signal output module includes: when the next planned distribution ratio value needs to be increased, a signal can be sent to the corresponding distribution area to control the transmission voltage of the transformer or control the switch of the corresponding relay, so that the purpose of controlling the output of electric quantity is achieved.
Preferably, in the step one, the specific operation method is as follows: the electric energy meters, the first-level relays, the second-level relays, the third-level relays, the first-level transformers and the second-level transformers which are associated with the power transmission stations and the power distribution areas at all levels are connected with the centralized signal transmitter through signal lines, signals of the centralized signal transmitter are communicated with the centralized signal transmitter, and therefore the signals can be transmitted between the single electric appliance elements and the centralized signal transmitter; secondly, all the centralized signal transmitters are connected with a unified measurement and control center network, and the measurement and control center network is built by relying on a computer terminal.
Preferably, in the step one, all the related electrical components are intelligent electrical components, so that remote data transmission and control are facilitated, and a data source for reference is provided for the whole measurement and control center.
After the technical scheme is adopted, compared with the prior art, the invention has the following beneficial effects.
1. The invention monitors the power transmission and distribution conditions of each network point in the whole large power grid by constructing a measurement and control center network, integrates all power transmission and distribution information, compares the power transmission and distribution information with planned power transmission and distribution parameters, and improves a power transmission and distribution plan through comparison, thereby enabling the electric energy to realize optimized application to a greater extent;
2. by arranging the data of the whole measurement and control center, a visual image-text mode is formed, and the method has important reference significance for continuous improvement and scientific research of subsequent distribution point plans.
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention to its proper form. It is obvious that the drawings in the following description are only some embodiments, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 is a schematic diagram of the overall power transmission and distribution network structure of a large power grid.
It should be noted that the drawings and the description are not intended to limit the scope of the inventive concept in any way, but rather to illustrate it for those skilled in the art by reference to specific embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and the following embodiments are used for illustrating the present invention and are not intended to limit the scope of the present invention.
As shown in fig. 1, a large power grid area intelligent and emergency bidirectional power distribution method specifically includes the following steps:
step one, establishing a measurement and control center network, and connecting each power transformation output signal with a computer terminal through a centralized signal transmitter to form a power transmission and distribution network framework capable of carrying out signal transmission;
the specific operation method comprises the following steps: the electric energy meters, the first-level relays, the second-level relays, the third-level relays, the first-level transformers and the second-level transformers which are associated with the power transmission stations and the power distribution areas at all levels are connected with the centralized signal transmitter through signal lines, signals of the centralized signal transmitter are communicated with the centralized signal transmitter, and therefore the signals can be transmitted between the single electric appliance elements and the centralized signal transmitter; secondly, connecting each centralized signal transmitter with a unified measurement and control center network, wherein the measurement and control center network is established by relying on a computer terminal; all the electrical components involved in the step are intelligent electrical components, so that remote data transmission and control are facilitated, and a data source for reference is provided for the whole measurement and control center.
Step two, constructing a measurement and control center software system, converting each signal transmitted to a network center into a digital signal which can be processed, constructing a parameter setting module, a signal receiving module, a signal analysis module, a signal output module and a learning optimization module in the measurement and control center through software programming, and performing simulation test on each module; inputting an analog test signal through manual control, observing whether a feedback signal of a signal output module is consistent with manual control input information or not, if so, successfully testing, and completing the whole test process, so that the whole measurement and control center can be put into use;
in the whole measurement and control center software system, a parameter setting module is responsible for carrying out basic setting on parameters of all levels of electrical components; the signal receiving module is responsible for classifying and storing the signals transmitted back by the centralized signal transmitter; the signal analysis module is responsible for carrying out logic calculation comparison on the classified and stored information, comparing the information with a reference parameter and carrying out logic judgment on a comparison result; the signal output module is responsible for converting the logic judgment result into an executable feedback signal and carrying out feedback transmission on the executable feedback signal to each electric appliance execution element; the learning optimization module carries out statistical processing on data of the whole measurement and control center, converts the data in each module into a chart, and provides a scientific basis for continuous research for intelligent power distribution.
In this step, the basic parameter setting performed by the parameter setting module includes: rated output voltage of the power transmission station U1, planned output electric quantity of the power transmission station Q1, rated output voltage of the entire distribution area U2, planned output electric quantity of the entire distribution area Q2, rated output voltage of the district distribution area U3, planned output electric quantity of the district distribution area Q3;
setting the electricity consumption of the terminal user in a certain time period as QΔ t, wherein Δ t is a certain time period of the electricity consumption of the user in one day, setting t = K + t (n + 1) -tn, wherein tn is a time node of a certain cycle in one day, and t (n + 1) is a later time node relative to tn, and setting: n =1, t1= 5; n =2, t2= 8; n =3, t3= 11; n =4, t4= 13; n =5, t5= 15; n =6, t6= 18; n =7, t7=20, when t (n + 1) cycles to t1= 5;
where K is an augmentation parameter, K =0 when tn is some of 5, 8, 11, 13, 15, 18; when tn is 20, t (n + 1) =5, when K = 24;
setting the power consumption of a terminal user in one day as Qtd, wherein Qtd = F + H Σ Q Δ t, F is a seasonal temperature coefficient, the power consumption influenced by the temperature in spring and autumn is relatively low, F is set as 0, the power consumption influenced by the temperature in summer and winter is relatively high, and F is set as 10; h is a production coefficient, production is influenced by light and vigorous seasons, electricity consumption in the light seasons is low, electricity consumption in the vigorous seasons is high, H in the light seasons is set to be 1, and H in the vigorous seasons is set to be 1.5-2;
setting the power consumption of an end user in one month to be Qtm, setting the power consumption of the end user in one quarter to be Qts, and setting the power consumption of the end user in one year to be Qty;
in this step, the specific classification manner of the signal receiving module for classifying the input signal includes: dividing according to the voltage and current uploaded by an electric energy meter and the current statistical power consumption; dividing parameters in each high-voltage and low-voltage area, and dividing voltage, current and overall electricity consumption as the same group of data;
the specific calculation method of the classified and stored information by the signal analysis module comprises the following steps: the method comprises the steps of counting the electricity consumption of users every day and in each time period, calculating the daily electricity consumption of each user, accumulating the electricity consumption of the users in each time period in a certain day to obtain Qtd, calculating the monthly electricity consumption of each user, specifically, superposing the electricity consumption Qtd of the users every day to obtain Qtm, calculating the electricity consumption of each user in one quarter, specifically, accumulating the electricity consumption Qtm of the users in one quarter to obtain Qts, calculating the electricity consumption of each user in one year, specifically, accumulating the electricity consumption Qtm of the users in each quarter to obtain Qty, calculating the total electricity consumption of all users in a district every day, every month, every quarter and every year, comparing the obtained result with the planned distribution amount, and when the result is higher than the planned value, the next planned electric quantity distribution ratio can be properly increased, and when the result is lower than the planned value, the next planned electric quantity distribution ratio can be properly adjusted;
in this step, the output signal generated by the signal output module includes: when the next planned distribution ratio value needs to be increased, a signal can be sent to the corresponding distribution area to control the transmission voltage of the transformer or control the switch of the corresponding relay, so that the purpose of controlling the electric quantity output is achieved.
Step three, the measurement and control center is put into use, and signals transmitted by each electrical element are processed through each module of the measurement and control center, and the specific operation is as follows: the method comprises the steps of firstly setting corresponding basic parameters according to each electrical appliance element in a signal transmission network in a parameter setting module, then classifying received signals through a classifying module, analyzing and comparing the classified signals through a signal analyzing module to obtain a logic comparison result, converting the comparison result into executable feedback signals through a signal output module, and transmitting the executable feedback signals to each electrical appliance execution element to finish intelligent power distribution.
The invention forms a power transmission and distribution network architecture by establishing a measurement and control center network, then transmits and stores measurement and control signals of each power transmission and distribution area and carries out logic comparison, converts the comparison result into an electric signal which can be executed and feeds back to electric appliance execution elements in each power distribution area to complete power transmission and distribution control, and in the process, all the power transmission and distribution signals can be transmitted into the measurement and control center network in real time, and the information is counted into a chart form by a learning optimization module to find out a corresponding regularity conclusion, thereby facilitating further continuous improvement of a power transmission and distribution plan and simultaneously taking the information as reference data for scientific research.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A large power grid regional intelligent and emergency bidirectional power distribution method is characterized by comprising the following steps:
step one, establishing a measurement and control center network, and connecting each power transformation output signal with a computer terminal through a centralized signal transmitter to form a power transmission and distribution network framework capable of carrying out signal transmission;
secondly, a measurement and control center software system is constructed, signals transmitted to a network center are converted into processable digital signals, a parameter setting module, a signal receiving module, a signal analysis module, a signal output module and a learning optimization module are constructed in the measurement and control center, and simulation testing is carried out on the modules; inputting an analog test signal through manual control, observing whether a feedback signal of a signal output module is consistent with manual control input information or not, if so, successfully testing, and completing the whole test process, so that the whole measurement and control center can be put into use;
step three, the measurement and control center is put into use, and signals transmitted by each electrical element are processed through each module of the measurement and control center, and the specific operation is as follows: setting corresponding basic parameters according to each electrical appliance element in a signal transmission network in a parameter setting module, classifying received signals through a classification module, analyzing and comparing the classified signals through a signal analysis module to obtain a logic comparison result, converting the comparison result into an executable feedback signal through a signal output module, and transmitting the executable feedback signal to each electrical appliance execution element to finish intelligent power distribution;
in the second step, the parameter setting module is responsible for performing basic setting on parameters of each level of electrical components; the signal receiving module is responsible for classifying and storing the signals transmitted back by the centralized signal transmitter; the signal analysis module is responsible for carrying out logic calculation comparison on the classified and stored information, comparing the information with a reference parameter and carrying out logic judgment on a comparison result; the signal output module is responsible for converting the logic judgment result into an executable feedback signal and performing feedback transmission on the executable feedback signal to each electric appliance execution element; the learning optimization module carries out statistical processing on data of the whole measurement and control center, converts the data in each module into a chart and provides a basis for continuous research for intelligent power distribution;
the parameter basic setting performed by the parameter setting module comprises the following steps: rated output voltage of the power transmission station U1, planned output electric quantity of the power transmission station Q1, rated output voltage of the entire distribution area U2, planned output electric quantity of the entire distribution area Q2, rated output voltage of the district distribution area U3, planned output electric quantity of the district distribution area Q3;
setting the electricity consumption of the terminal user in a certain time period as QΔ t, wherein Δ t is a certain time period of the electricity consumption of the user in one day, setting t = K + t (n + 1) -tn, wherein tn is a time node of a certain cycle in one day, and t (n + 1) is a later time node relative to tn, and setting: n =1, t1= 5; n =2, t2= 8; n =3, t3= 11; n =4, t4= 13; n =5, t5= 15; n =6, t6= 18; n =7, t7=20, when t (n + 1) cycles to t1= 5;
where K is a supplementary parameter, K =0 when tn is some of 5, 8, 11, 13, 15, 18; when tn is 20, t (n + 1) =5, when K = 24;
setting the power consumption of a terminal user in one day as Qtd, wherein Qtd = F + H Σ Q Δ t, F is a seasonal temperature coefficient, the power consumption influenced by the temperature in spring and autumn is relatively low, F is set as 0, the power consumption influenced by the temperature in summer and winter is relatively high, and F is set as 10; h is a production coefficient, production is influenced by light and vigorous seasons, electricity consumption in the light seasons is low, electricity consumption in the vigorous seasons is high, H in the light seasons is set to be 1, and H in the vigorous seasons is set to be 1.5-2;
the power consumption of the end user in one month is set to Qtm, the power consumption of the end user in one quarter is set to Qts, and the power consumption of the end user in one year is set to Qty.
2. The intelligent and emergency bidirectional power distribution method for the large power grid area as recited in claim 1, wherein in the second step, the specific classification manner of the signal receiving module for classifying the input signals comprises: the method comprises the steps of firstly, dividing according to the voltage and current uploaded by an electric energy meter and the current statistical power consumption; and in the second mode, parameters in each high-voltage and low-voltage area are divided, and the voltage, the current and the whole electricity consumption are divided as the same group of data.
3. The large power grid regional intelligence and emergency bidirectional power distribution method according to claim 1, wherein in the second step, the specific calculation method of the classified and stored information by the signal analysis module includes: the method comprises the steps of counting the electricity consumption of users every day and in each time period, calculating the daily electricity consumption of each user, accumulating the electricity consumption of the users in each time period in a certain day to obtain Qtd, calculating the monthly electricity consumption of each user, specifically, superposing the electricity consumption Qtd of the users every day to obtain Qtm, calculating the electricity consumption of each user in one quarter, specifically, accumulating the electricity consumption Qtm of the users in one quarter to obtain Qts, calculating the electricity consumption of each user in one year, specifically, accumulating the electricity consumption Qtm of the users in each quarter to obtain Qty, calculating the total electricity consumption of all users in a district every day, every month, every quarter and every year, comparing the obtained result with the planned distribution amount, and when the result is higher than the planned value, the next planned power distribution ratio can be properly adjusted up, and when the result is lower than the planned value, the next planned power distribution ratio can be properly adjusted.
4. The large power grid area intelligent and emergency bidirectional power distribution method according to claim 1, wherein in the second step, the output signal generated by the signal output module includes: when the next planned distribution ratio value needs to be increased, a signal can be sent to the corresponding distribution area to control the transmission voltage of the transformer or control the switch of the corresponding relay, so that the purpose of controlling the electric quantity output is achieved.
5. The large power grid area intelligent and emergency bidirectional power distribution method according to claim 1, wherein in the first step, the specific operation method is as follows: the electric energy meters, the first-level relays, the second-level relays, the third-level relays, the first-level transformers and the second-level transformers which are associated with the power transmission stations and the power distribution areas at all levels are connected with the centralized signal transmitter through signal lines, signals of the centralized signal transmitter are communicated with the centralized signal transmitter, and therefore the signals can be transmitted between the single electric appliance elements and the centralized signal transmitter; secondly, all the centralized signal transmitters are connected with a unified measurement and control center network, and the measurement and control center network is built by relying on a computer terminal.
6. The large power grid regional intelligence and emergency bidirectional power distribution method according to claim 1, wherein in the step one, all the related electrical components are intelligent electrical components, so that remote data transmission and control are facilitated, and a data source for reference is provided for the whole measurement and control center.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010729362.XA CN112072637B (en) | 2020-07-27 | 2020-07-27 | Intelligent and emergency bidirectional power distribution method for large power grid area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010729362.XA CN112072637B (en) | 2020-07-27 | 2020-07-27 | Intelligent and emergency bidirectional power distribution method for large power grid area |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112072637A CN112072637A (en) | 2020-12-11 |
| CN112072637B true CN112072637B (en) | 2022-09-02 |
Family
ID=73656894
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010729362.XA Active CN112072637B (en) | 2020-07-27 | 2020-07-27 | Intelligent and emergency bidirectional power distribution method for large power grid area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112072637B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113036805B (en) * | 2021-03-26 | 2023-10-20 | 湖北华中电力科技开发有限责任公司 | Intelligent power-based power transformation system and power transformation method thereof |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106444709A (en) * | 2016-10-13 | 2017-02-22 | 珠海许继电气有限公司 | Automatic testing method and device of distribution intelligent function of power distribution terminal |
| CN107402332A (en) * | 2016-05-20 | 2017-11-28 | 中国电力科学研究院 | A kind of Intelligent power distribution terminal multi-epitope automatic checkout system and its detection method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105205231B (en) * | 2015-09-06 | 2018-11-09 | 中国电力科学研究院 | A kind of power distribution network Digital Simulation System based on DCOM |
-
2020
- 2020-07-27 CN CN202010729362.XA patent/CN112072637B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107402332A (en) * | 2016-05-20 | 2017-11-28 | 中国电力科学研究院 | A kind of Intelligent power distribution terminal multi-epitope automatic checkout system and its detection method |
| CN106444709A (en) * | 2016-10-13 | 2017-02-22 | 珠海许继电气有限公司 | Automatic testing method and device of distribution intelligent function of power distribution terminal |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112072637A (en) | 2020-12-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102570609B (en) | Resident intelligent energy management system suitable for intelligent power grid | |
| CN106707778B (en) | Intelligent optimization management system for household comprehensive energy based on model predictive control | |
| CN202443306U (en) | Intelligent energy efficiency integrated monitoring and management system for building | |
| CN109001528A (en) | A kind of non-intrusion type metering separate acquisition system | |
| CN105226826B (en) | Distributed intelligence management of power use method and system | |
| CN114285034B (en) | Day-ahead regulation and optimization method and system considering power supply and new energy fluctuation | |
| CN103033680A (en) | Power measuring system | |
| CN105226827B (en) | A kind of distributed intelligence management of power use method and system | |
| CN112072637B (en) | Intelligent and emergency bidirectional power distribution method for large power grid area | |
| Xiong et al. | Extension of IEC61850 with smart EV charging | |
| CN113723684A (en) | Device and method for load prediction and energy management of enterprise power users | |
| CN112350435A (en) | Virtual power plant management and control device based on micro-grid group and electric power controllable load | |
| Leopold et al. | Simulation-based methodology for optimizing energy community controllers | |
| CN206302165U (en) | Cooperative control device and system for distributed energy | |
| CN113780856B (en) | Power distribution network operation evaluation method considering influence of information system on real-time reconstruction | |
| CN115189472A (en) | Power grid planning integrated data platform management system | |
| Lukovic et al. | A system level model of possible integration of building management system in smartgrid | |
| CN204856192U (en) | Intelligent interaction terminal equipment with distributed power supply management | |
| CN110705925B (en) | Energy interconnection planning system for accessing power distribution network based on NSL0 reconstruction algorithm | |
| Poolo | A smart grid demand side management framework based on advanced metering infrastructure | |
| CN113505915A (en) | Method for optimizing maintenance plan of power distribution network containing distributed power supply | |
| Lamia et al. | Integration of Renewable Energies into the Smart Grid Electricity network | |
| Zhao et al. | Load trend prediction analysis based on lstm and sliding time window | |
| Pauli et al. | An Analysis on the Use of IoT Devices in the Integrated Energy Resources Planning | |
| CN114548485B (en) | Big data application system for power production |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 330096 No. 88, Minqiang Road, private science and Technology Park, Qingshanhu District, Nanchang City, Jiangxi Province Applicant after: STATE GRID JIANGXI ELECTRIC POWER COMPANY LIMITED Research Institute Applicant after: STATE GRID CORPORATION OF CHINA Address before: 330096 No.88 Minqiang Road, private science and Technology Park, high tech Zone, Nanchang City, Jiangxi Province Applicant before: STATE GRID JIANGXI ELECTRIC POWER COMPANY LIMITED Research Institute Applicant before: STATE GRID CORPORATION OF CHINA |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |