CN117521888A - Virtual power plant capacity optimal configuration method considering risk - Google Patents
Virtual power plant capacity optimal configuration method considering risk Download PDFInfo
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- CN117521888A CN117521888A CN202311469371.XA CN202311469371A CN117521888A CN 117521888 A CN117521888 A CN 117521888A CN 202311469371 A CN202311469371 A CN 202311469371A CN 117521888 A CN117521888 A CN 117521888A
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- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000004146 energy storage Methods 0.000 claims abstract description 29
- 238000005457 optimization Methods 0.000 claims abstract description 28
- 238000007781 pre-processing Methods 0.000 claims abstract description 8
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 230000002159 abnormal effect Effects 0.000 claims description 21
- 238000012544 monitoring process Methods 0.000 claims description 21
- 238000012545 processing Methods 0.000 claims description 18
- 238000004088 simulation Methods 0.000 claims description 16
- 238000001816 cooling Methods 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 12
- 230000000694 effects Effects 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 11
- 238000007726 management method Methods 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 8
- 230000005856 abnormality Effects 0.000 claims description 6
- 238000007599 discharging Methods 0.000 claims description 6
- 230000008439 repair process Effects 0.000 claims description 6
- 230000007547 defect Effects 0.000 claims description 4
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 238000003745 diagnosis Methods 0.000 claims description 3
- 239000012535 impurity Substances 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 2
- 230000017525 heat dissipation Effects 0.000 claims description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
- G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention relates to the technical field of virtual power plants, and discloses a virtual power plant capacity optimization configuration method considering risks, which comprises the following steps: s1, data acquisition and collection: collecting data related to the energy storage capacity of the virtual power plant by arranging a sensor, and transmitting the collected data downwards; s2, data preprocessing and analysis: receiving data acquired by a sensor, preprocessing the data, and transmitting the tidied data downwards; s3, risk judgment and solving: the method and the device have the advantages that the faults and risks generated by the capacity of the virtual power plant can be judged by setting the risk judgment solution, and corresponding solutions are provided, so that a novice worker can know how to solve the risk faults while receiving the risk reminding, and the normal operation of the virtual power plant is ensured.
Description
Technical Field
The invention relates to the technical field of virtual power plants, in particular to a virtual power plant capacity optimization configuration method considering risks.
Background
A virtual power plant is a system integrating multiple energy sources and power production facilities, aiming at providing a reliable power supply.
The capacity of the virtual power plant refers to the total power generation capacity or the total energy storage capacity of the virtual power plant, and the energy storage capacity is an important component in the virtual power plant, and refers to the amount of electric energy which can be stored by the energy storage system.
In the prior art, the faults are usually alarmed to remind workers to process the faults in time, but after the workers receive fault reminding, the specific problems of the faults still need to be judged by experience, so that some novice workers cannot process and maintain the faults according to the first time of experience after receiving the reminding, and the overall working efficiency of the virtual power plant is delayed.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a virtual power plant capacity optimizing configuration method considering risks, which solves the problem that faults occur in the process of energy storage of a virtual power plant, and the prior art usually alarms the faults to remind workers to process the faults in time, but the specific problems of the faults still need to be judged by experience after the workers receive fault reminding, so that the problems that some novice workers cannot process and maintain the faults by experience for the first time after receiving the reminding and delay the overall working efficiency of the virtual power plant are solved.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: a virtual power plant capacity optimization configuration method considering risks is characterized in that: the method comprises the following steps:
s1, data acquisition and collection: the sensor is arranged, data related to the energy storage capacity of the virtual power plant are collected, and the collected data are transmitted downwards, so that the risk prediction and optimization work can be conveniently carried out through the data;
s2, data preprocessing and analysis: the method comprises the steps of receiving data acquired by a sensor, preprocessing the data, removing impurities and fluctuation in the data, enabling the data to keep single, analyzing and classifying the data, dividing and planning different energy storage resource data in a virtual power plant respectively, and transmitting the tidied data downwards;
s3, risk judgment and solving: reading the data after finishing, comparing the data value with a preset standard to judge whether the data value has problems or not, and adopting different solutions to solve the faults according to different fault problems;
s4, case storage records: after the faults are judged and processed, the types of the faults are recorded through the storage equipment, and the solution scheme is recorded, so that the subsequent processing and observation are convenient;
s5, AI simulation optimization: firstly, extracting fault case data, pouring the extracted data into environment simulation, truly simulating various values of an abnormal site, simulating the occurrence of the abnormality and solving the abnormal solution, judging whether the abnormal solution has defects or not, and further improving the problem.
Preferably, step S3 includes:
s301, judging capacity energy storage faults: comparing the acquired numerical value with the standard parameter through presetting the standard parameter, so as to judge whether the virtual power plant has a fault problem or not, and setting a plurality of different standard numerical values, and judging the specific type and position of the fault through comparing the acquired numerical value with the acquired numerical value in sequence;
s302, capacity energy storage fault solving: after receiving the judging conclusion of the fault problem from the capacity energy storage fault judgment, selecting a corresponding solution according to the judging conclusion, and solving and processing the fault problem.
Preferably, step S301 includes:
s30101. fault determination of battery problem: monitoring the charge and discharge rate of the battery, detecting the voltage and the temperature of the battery, and judging that the capacity energy storage battery of the virtual power plant fails once the capacity of the battery suddenly drops, the charge time is shortened, or the temperature of the battery abnormally rises;
s30102. fault determination of battery management system: monitoring management software of the system, detecting whether abnormal alarm or error information exists or not, detecting battery charge-discharge balance at the same time, and judging that the battery management system has a fault problem when the battery cells are unevenly charged and discharged;
s30103. inverter fault determination: monitoring whether the output voltage and the frequency are stable or not, and judging that the inverter has a fault problem when the output voltage or the frequency is found to have large fluctuation;
s30104. cooling system failure determination: and monitoring the temperature of the energy storage system, and judging that the cooling system has a fault problem when the temperature is abnormally increased.
Preferably, step S301 includes:
s30105. connection problem fault judgment: checking whether the current is normally transmitted or not, and judging that the connection problem is fault when the situation that the current cannot be transmitted or circulated at a position is detected;
s30106. fault judgment of overvoltage and overcurrent: monitoring waveforms of voltage and current, detecting whether abnormality exists or not, and judging that overvoltage or overcurrent is caused when the voltage or current is detected to exceed a rated range;
s30107. communication failure judgment: monitoring a communication line and equipment of a system, and judging that the system cannot be normally connected with a network, so as to solve the problem of communication failure;
s30108. safety system fault determination: safety protection devices of the monitoring system, such as circuit breakers, fuses, determine a safety system fault problem when the safety device trips or blows.
Preferably, step S302 includes:
s30201, battery discharge optimization scheme: starting a discharging device, so that the discharging device can uniformly charge and discharge the storage battery arranged in the virtual power plant, and the balance effect of the battery is realized, thereby achieving the purposes of repairing and optimizing the energy storage battery;
s30202, a system diagnosis and repair scheme: updating or reinstalling software on the system to ensure the normal operation of the system and achieve the purpose of processing the fault problem of the battery management system;
s30203. standby inverter enablement scheme: by starting the standby inverter, the continuity of power supply is maintained, so that the virtual power plant can still keep operating before a worker changes and maintains the inverter, and the problem of inverter faults is solved;
s30204. repair or replacement of cooling device solution: through starting heat dissipation alarm device, make remind the staff in time to change cooling pump or fan, ensure cooling device's normal operating, prevent that battery or inverter from overheated condition from taking place.
Preferably, step S302 includes:
s30205. alert check joint protocol: by starting the wiring alarm device, a worker is reminded of carrying a wiring tool and reminding the position and the place of a specific joint fault, so that the worker can conveniently move to the site for reinstallation and fixation of a loose joint in the first time;
s30206, an overvoltage and overcurrent protection scheme: resetting protection parameters of the overvoltage protection and overcurrent protection device to achieve the purpose of solving the problem of overvoltage and overcurrent faults;
s30207. reconnection network scheme: detecting whether the network connection is normal or not, and restarting the system to connect the network so as to achieve the aim of solving the problem of communication failure;
s30208, resetting a safety protection device: by resetting or replacing damaged circuit breakers or fuses, normal operation of the safety function of the system is ensured, potential hazards are prevented, and the problem of failure of the safety protection device is solved.
Preferably, step S4 includes:
s401, fault case recording: recording and storing the problems and reasons of the faults, and comparing and recording and storing the fault solving schemes;
s402, fault case analysis: analyzing the generation of abnormal values in the fault values by reading the data of the fault case records, and analyzing the fault reasons and how the adaptive scheme solves the fault reasons;
s403, extracting fault case data: and various values in the fault cause are extracted, so that the method is more similar to the authenticity of an abnormal field case when AI simulation is performed later.
Preferably, step S5 includes:
s501, simulating a case environment: each numerical value in the fault case data is imported for simulation test, so that the authenticity in the test process is improved;
s502, testing different solutions: under the environment of abnormal faults, various different solutions are tried, and the efficiency of judging which solution is higher and the effect is better.
Preferably, step S5 includes:
s503, simulating a final result: and the final results generated by different schemes are inferred and judged, so that the effects of the different schemes are analyzed and judged according to the solved results, and a better fault solving scheme is obtained.
Preferably, step S5 includes:
s504, storing and recording simulation conclusion: the final result is stored and recorded, so that the processing efficiency and effect of the fault are improved by adopting the conclusion under the condition that the same fault appears next time;
s505, optimizing a subsequent judgment result: the accuracy of the next fault risk pre-judgment is improved by adopting a better optimization processing result, and the efficiency of the fault risk processing is also improved.
(III) beneficial effects
The invention provides a virtual power plant capacity optimization configuration method considering risks. The beneficial effects are as follows:
(1) When the virtual power plant capacity optimizing configuration method considering risks is used, the faults and risks generated by the virtual power plant capacity can be judged by setting the risk judgment solution, and corresponding solutions are provided, so that a novice worker can know how to solve the risk faults while receiving the risk reminding, and normal operation of the virtual power plant is ensured.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a flow chart of risk determination solution according to the present invention;
FIG. 3 is a flow chart of the capacity storage fault determination of the present invention;
FIG. 4 is a flow chart of the capacity storage fault resolution of the present invention;
FIG. 5 is a flow chart of a case-stored record according to the present invention;
FIG. 6 is a flow chart of the AI simulation optimization of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-6, the invention provides a virtual power plant capacity optimization configuration method considering risk, comprising the following steps:
s1, data acquisition and collection: the sensor is arranged, data related to the energy storage capacity of the virtual power plant are collected, and the collected data are transmitted downwards, so that the risk prediction and optimization work can be conveniently carried out through the data;
s2, data preprocessing and analysis: the method comprises the steps of receiving data acquired by a sensor, preprocessing the data, removing impurities and fluctuation in the data, enabling the data to keep single, analyzing and classifying the data, dividing and planning different energy storage resource data in a virtual power plant respectively, and transmitting the tidied data downwards;
s3, risk judgment and solving: reading the data after finishing, comparing the data value with a preset standard to judge whether the data value has problems or not, and adopting different solutions to solve the faults according to different fault problems;
s301, judging capacity energy storage faults: comparing the acquired numerical value with the standard parameter through presetting the standard parameter, so as to judge whether the virtual power plant has a fault problem or not, and setting a plurality of different standard numerical values, and judging the specific type and position of the fault through comparing the acquired numerical value with the acquired numerical value in sequence;
s30101. fault determination of battery problem: monitoring the charge and discharge rate of the battery, detecting the voltage and the temperature of the battery, and judging that the capacity energy storage battery of the virtual power plant fails once the capacity of the battery suddenly drops, the charge time is shortened, or the temperature of the battery abnormally rises;
s30102. fault determination of battery management system: monitoring management software of the system, detecting whether abnormal alarm or error information exists or not, detecting battery charge-discharge balance at the same time, and judging that the battery management system has a fault problem when the battery cells are unevenly charged and discharged;
s30103. inverter fault determination: monitoring whether the output voltage and the frequency are stable or not, and judging that the inverter has a fault problem when the output voltage or the frequency is found to have large fluctuation;
s30104. cooling system failure determination: monitoring the temperature of the energy storage system, and judging that the cooling system has a fault problem when the temperature is abnormally increased;
s30105. connection problem fault judgment: checking whether the current is normally transmitted or not, and judging that the connection problem is fault when the situation that the current cannot be transmitted or circulated at a position is detected;
s30106. fault judgment of overvoltage and overcurrent: monitoring waveforms of voltage and current, detecting whether abnormality exists or not, and judging that overvoltage or overcurrent is caused when the voltage or current is detected to exceed a rated range;
s30107. communication failure judgment: monitoring a communication line and equipment of a system, and judging that the system cannot be normally connected with a network, so as to solve the problem of communication failure;
s30108. safety system fault determination: monitoring safety protection devices of the system, such as a circuit breaker and a fuse, and judging that the safety protection device has a fault problem when the safety device trips or blows;
s302, capacity energy storage fault solving: after receiving a judging conclusion of the fault problem from capacity energy storage fault judgment, selecting a corresponding solution according to the judging conclusion, and solving and processing the fault problem;
s30201, battery discharge optimization scheme: starting a discharging device, so that the discharging device can uniformly charge and discharge the storage battery arranged in the virtual power plant, and the balance effect of the battery is realized, thereby achieving the purposes of repairing and optimizing the energy storage battery;
s30202, a system diagnosis and repair scheme: updating or reinstalling software on the system to ensure the normal operation of the system and achieve the purpose of processing the fault problem of the battery management system;
s30203. standby inverter enablement scheme: by starting the standby inverter, the continuity of power supply is maintained, so that the virtual power plant can still keep operating before a worker changes and maintains the inverter, and the problem of inverter faults is solved;
s30204. repair or replacement of cooling device solution: by starting the heat radiation alarm equipment, a reminding worker can timely replace the cooling pump or the fan, normal operation of the cooling equipment is ensured, and overheat of the battery or the inverter is prevented;
s30205. alert check joint protocol: by starting the wiring alarm device, a worker is reminded of carrying a wiring tool and reminding the position and the place of a specific joint fault, so that the worker can conveniently move to the site for reinstallation and fixation of a loose joint in the first time;
s30206, an overvoltage and overcurrent protection scheme: resetting protection parameters of the overvoltage protection and overcurrent protection device to achieve the purpose of solving the problem of overvoltage and overcurrent faults;
s30207. reconnection network scheme: detecting whether the network connection is normal or not, and restarting the system to connect the network so as to achieve the aim of solving the problem of communication failure;
s30208, resetting a safety protection device: the normal operation of the safety function of the system is ensured by resetting or replacing the damaged breaker or fuse, so that potential danger is prevented, and the problem of the fault of the safety protection device is solved;
s4, case storage records: after the faults are judged and processed, the types of the faults are recorded through the storage equipment, and the solution scheme is recorded, so that the subsequent processing and observation are convenient;
s401, fault case recording: recording and storing the problems and reasons of the faults, and comparing and recording and storing the fault solving schemes;
s402, fault case analysis: analyzing the generation of abnormal values in the fault values by reading the data of the fault case records, and analyzing the fault reasons and how the adaptive scheme solves the fault reasons;
s403, extracting fault case data: and each numerical value in the fault cause is extracted, so that the reality of an abnormal field case is more similar when the subsequent AI simulation is performed;
s5, AI simulation optimization: firstly, extracting fault case data, pouring the extracted data into environment simulation, truly simulating various values of an abnormal site, simulating the occurrence of the abnormality and solving the abnormal solution, judging whether the abnormal solution has defects or not, and further improving the problem;
s501, simulating a case environment: each numerical value in the fault case data is imported for simulation test, so that the authenticity in the test process is improved;
s502, testing different solutions: under the environment of abnormal faults, various different solutions are tried, and the efficiency of judging which solution is higher and the effect is better;
s503, simulating a final result: the final results generated by different schemes are inferred and judged, so that the effects of the different schemes are analyzed and judged according to the solved results, and a better fault solving scheme is obtained;
s504, storing and recording simulation conclusion: the final result is stored and recorded, so that the processing efficiency and effect of the fault are improved by adopting the conclusion under the condition that the same fault appears next time;
s505, optimizing a subsequent judgment result: the accuracy of the next fault risk pre-judgment is improved by adopting a better optimization processing result, and the efficiency of the fault risk processing is also improved.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A virtual power plant capacity optimization configuration method considering risks is characterized in that: the method comprises the following steps:
s1, data acquisition and collection: the sensor is arranged, data related to the energy storage capacity of the virtual power plant are collected, and the collected data are transmitted downwards, so that the risk prediction and optimization work can be conveniently carried out through the data;
s2, data preprocessing and analysis: the method comprises the steps of receiving data acquired by a sensor, preprocessing the data, removing impurities and fluctuation in the data, enabling the data to keep single, analyzing and classifying the data, dividing and planning different energy storage resource data in a virtual power plant respectively, and transmitting the tidied data downwards;
s3, risk judgment and solving: reading the data after finishing, comparing the data value with a preset standard to judge whether the data value has problems or not, and adopting different solutions to solve the faults according to different fault problems;
s4, case storage records: after the faults are judged and processed, the types of the faults are recorded through the storage equipment, and the solution scheme is recorded, so that the subsequent processing and observation are convenient;
s5, AI simulation optimization: firstly, extracting fault case data, pouring the extracted data into environment simulation, truly simulating various values of an abnormal site, simulating the occurrence of the abnormality and solving the abnormal solution, judging whether the abnormal solution has defects or not, and further improving the problem.
2. The virtual power plant capacity optimization configuration method considering risk according to claim 1, wherein the method comprises the following steps: the step S3 comprises the following steps:
s301, judging capacity energy storage faults: comparing the acquired numerical value with the standard parameter through presetting the standard parameter, so as to judge whether the virtual power plant has a fault problem or not, and setting a plurality of different standard numerical values, and judging the specific type and position of the fault through comparing the acquired numerical value with the acquired numerical value in sequence;
s302, capacity energy storage fault solving: after receiving the judging conclusion of the fault problem from the capacity energy storage fault judgment, selecting a corresponding solution according to the judging conclusion, and solving and processing the fault problem.
3. The virtual power plant capacity optimization configuration method considering risk according to claim 2, wherein the method comprises the following steps: step S301 includes:
s30101. fault determination of battery problem: monitoring the charge and discharge rate of the battery, detecting the voltage and the temperature of the battery, and judging that the capacity energy storage battery of the virtual power plant fails once the capacity of the battery suddenly drops, the charge time is shortened, or the temperature of the battery abnormally rises;
s30102. fault determination of battery management system: monitoring management software of the system, detecting whether abnormal alarm or error information exists or not, detecting battery charge-discharge balance at the same time, and judging that the battery management system has a fault problem when the battery cells are unevenly charged and discharged;
s30103. inverter fault determination: monitoring whether the output voltage and the frequency are stable or not, and judging that the inverter has a fault problem when the output voltage or the frequency is found to have large fluctuation;
s30104. cooling system failure determination: and monitoring the temperature of the energy storage system, and judging that the cooling system has a fault problem when the temperature is abnormally increased.
4. The virtual power plant capacity optimization configuration method considering risk according to claim 2, wherein the method comprises the following steps: step S301 includes:
s30105. connection problem fault judgment: checking whether the current is normally transmitted or not, and judging that the connection problem is fault when the situation that the current cannot be transmitted or circulated at a position is detected;
s30106. fault judgment of overvoltage and overcurrent: monitoring waveforms of voltage and current, detecting whether abnormality exists or not, and judging that overvoltage or overcurrent is caused when the voltage or current is detected to exceed a rated range;
s30107. communication failure judgment: monitoring a communication line and equipment of a system, and judging that the system cannot be normally connected with a network, so as to solve the problem of communication failure;
s30108. safety system fault determination: safety protection devices of the monitoring system, such as circuit breakers, fuses, determine a safety system fault problem when the safety device trips or blows.
5. The virtual power plant capacity optimization configuration method considering risk according to claim 2, wherein the method comprises the following steps: the step S302 includes:
s30201, battery discharge optimization scheme: starting a discharging device, so that the discharging device can uniformly charge and discharge the storage battery arranged in the virtual power plant, and the balance effect of the battery is realized, thereby achieving the purposes of repairing and optimizing the energy storage battery;
s30202, a system diagnosis and repair scheme: updating or reinstalling software on the system to ensure the normal operation of the system and achieve the purpose of processing the fault problem of the battery management system;
s30203. standby inverter enablement scheme: by starting the standby inverter, the continuity of power supply is maintained, so that the virtual power plant can still keep operating before a worker changes and maintains the inverter, and the problem of inverter faults is solved;
s30204. repair or replacement of cooling device solution: through starting heat dissipation alarm device, make remind the staff in time to change cooling pump or fan, ensure cooling device's normal operating, prevent that battery or inverter from overheated condition from taking place.
6. The virtual power plant capacity optimization configuration method considering risk according to claim 2, wherein the method comprises the following steps: the step S302 includes:
s30205. alert check joint protocol: by starting the wiring alarm device, a worker is reminded of carrying a wiring tool and reminding the position and the place of a specific joint fault, so that the worker can conveniently move to the site for reinstallation and fixation of a loose joint in the first time;
s30206, an overvoltage and overcurrent protection scheme: resetting protection parameters of the overvoltage protection and overcurrent protection device to achieve the purpose of solving the problem of overvoltage and overcurrent faults;
s30207. reconnection network scheme: detecting whether the network connection is normal or not, and restarting the system to connect the network so as to achieve the aim of solving the problem of communication failure;
s30208, resetting a safety protection device: by resetting or replacing damaged circuit breakers or fuses, normal operation of the safety function of the system is ensured, potential hazards are prevented, and the problem of failure of the safety protection device is solved.
7. The virtual power plant capacity optimization configuration method considering risk according to claim 1, wherein the method comprises the following steps: the step S4 comprises the following steps:
s401, fault case recording: recording and storing the problems and reasons of the faults, and comparing and recording and storing the fault solving schemes;
s402, fault case analysis: analyzing the generation of abnormal values in the fault values by reading the data of the fault case records, and analyzing the fault reasons and how the adaptive scheme solves the fault reasons;
s403, extracting fault case data: and various values in the fault cause are extracted, so that the method is more similar to the authenticity of an abnormal field case when AI simulation is performed later.
8. The virtual power plant capacity optimization configuration method considering risk according to claim 1, wherein the method comprises the following steps: the step S5 comprises the following steps:
s501, simulating a case environment: each numerical value in the fault case data is imported for simulation test, so that the authenticity in the test process is improved;
s502, testing different solutions: under the environment of abnormal faults, various different solutions are tried, and the efficiency of judging which solution is higher and the effect is better.
9. The virtual power plant capacity optimization configuration method considering risk according to claim 1, wherein the method comprises the following steps: the step S5 comprises the following steps:
s503, simulating a final result: and the final results generated by different schemes are inferred and judged, so that the effects of the different schemes are analyzed and judged according to the solved results, and a better fault solving scheme is obtained.
10. The virtual power plant capacity optimization configuration method considering risk according to claim 1, wherein the method comprises the following steps: the step S5 comprises the following steps:
s504, storing and recording simulation conclusion: the final result is stored and recorded, so that the processing efficiency and effect of the fault are improved by adopting the conclusion under the condition that the same fault appears next time;
s505, optimizing a subsequent judgment result: the accuracy of the next fault risk pre-judgment is improved by adopting a better optimization processing result, and the efficiency of the fault risk processing is also improved.
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