CN112732443A - Energy storage power station state evaluation and operation optimization system based on edge calculation - Google Patents
Energy storage power station state evaluation and operation optimization system based on edge calculation Download PDFInfo
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Abstract
The invention discloses an energy storage power station state evaluation and operation optimization system based on edge calculation, which comprises energy storage power station equipment, data communication acquisition equipment, an edge calculation device and a cloud service platform, wherein the energy storage power station equipment comprises a power supply unit, a data communication acquisition unit and a cloud service platform; the energy storage power station equipment comprises a battery module, a battery management system, an energy storage converter and an energy storage energy management system; the data communication acquisition equipment acquires the operating data of the energy storage power station equipment and transmits the acquired data to the edge computing device in real time, the edge computing device performs relevant data analysis on site and transmits an analysis result to the cloud service platform through the data communication acquisition equipment, and the cloud service platform performs relevant data storage and further data optimization analysis. By constructing the system structure, the rapid comprehensive assessment and fault early warning of the energy storage power station and key components thereof can be realized, an operation scheme support is provided for the refined control management of the energy storage power station, and the pressure of cloud and local real-time transmission of a large amount of data and communication is reduced.
Description
Technical Field
The invention belongs to the technical field of intelligent energy consumption, and particularly relates to an energy storage power station state evaluation and operation optimization system based on edge calculation.
Background
With the popularization and application of information communication technologies such as 'big cloud thing moving intelligence' and the rapid development of energy storage power stations in quality and quantity, 'three-in-one' (energy source flow, business flow and data flow) becomes the main strategic direction of the development of energy storage power stations at present. Aiming at the problems that the energy storage system has large monitoring data acquisition amount and higher data precision requirements, and faster computing capacity and corresponding control strategy implementation all provide more challenges and requirements for the energy storage power station system.
When the scale of the energy storage system is large and a control strategy is complex, the operation monitoring data, the storage data and the communication data of the system cannot be managed in a local storage mode, and the traditional centralized data management and communication mode is not tried out.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to solve the technical problem of the prior art, and provides an energy storage power station state evaluation and operation optimization system based on edge calculation, which realizes comprehensive evaluation and fault early warning of an energy storage power station and key components thereof in a mode of cooperative processing of a cloud end, an edge end and a device end, and provides an operation scheme support for refined control and management of the energy storage power station.
In order to solve the technical problem, the invention discloses an energy storage power station state evaluation and operation optimization system based on edge calculation, which comprises energy storage power station equipment, data communication acquisition equipment, an edge calculation device and a cloud service platform, wherein the energy storage power station equipment comprises a power supply unit, a data communication acquisition unit and a cloud service platform;
the method comprises the following steps that one energy storage power station corresponds to one data communication acquisition device and one edge computing device, and under the comprehensive energy scene with more than two energy storage power stations, the operation data of each energy storage power station is uploaded to the same cloud service platform through the corresponding data communication acquisition device;
the energy storage power station equipment comprises an energy storage unit battery, a bidirectional converter for converting direct current into alternating current, a Control unit PCS (Power Control System), a battery Management system BMS (Battery Management System) and an energy Management system EMS (energy Management System);
the data communication acquisition equipment is used for acquiring the operating data of the energy storage power station, is deployed at the side of the energy storage power station, acquires and forwards the operating data of the bidirectional converter, the control unit PCS and the battery management system BMS in real time to the edge computing device, acquires the data including the voltage, the current, the power and the temperature of the battery module and sends the data to the cloud service platform according to the specified frequency;
the edge computing device is used for evaluating the health state of the battery based on data acquired by the data communication acquisition equipment, embedding an energy storage operation auxiliary decision algorithm, computing the optimal charging and discharging strategy of the energy storage equipment in real time and uploading the computing result to a cloud service platform through the data communication acquisition equipment;
the cloud service platform receives the operation data of the energy storage power station, the battery health state evaluation result and a primary analysis result of the system operation economy, wherein the primary analysis result of the system operation economy refers to a calculation result obtained by the edge calculation device calculating the optimal charging and discharging strategy of the energy storage equipment; the cloud service platform further performs fault early warning analysis on the energy storage power station and decision on an operation strategy of the energy storage power station based on the three parts of data, and pushes the strategy to an Energy Management System (EMS) of the energy storage power station through a data communication interface so as to realize information interaction with energy storage power station equipment.
In one implementation, the battery management system BMS includes a 3-layer architecture: the battery module BMS, the battery cluster BMS and the battery system BMS, the voltage, the current, the power and the temperature operating parameter of battery module level, battery cluster level and battery system level are collected respectively to 3 layers of framework BMS to with data real-time propelling movement to data communication collection equipment.
In one implementation, the evaluation of the state of health of the battery is based on a charging and discharging voltage-current curve of the battery module and a battery equivalent circuit model, and the remaining capacity soh (state of health), the internal resistance and the battery terminal voltage of the battery are estimated, and the battery states of different battery modules are compared to further judge the operation state of the battery system of the energy storage power station.
In one implementation manner, the operation state of the battery system is the battery health state balance degree of different battery modules, the evaluation indexes are the terminal voltage and the battery residual capacity SoH of each battery module, based on the detection data of the battery modules, including the charging and discharging voltage and current curves, the estimation of the battery residual capacity SoH of different modules is performed by adopting an internal resistance estimation algorithm, and if the residual capacity of a certain battery module is found to be lower than the residual capacity of other battery modules and exceeds a threshold value T, the battery module needs to be replaced to ensure the operation efficiency and the overall service life of the whole battery system.
In one implementation manner, the operation strategy of the energy storage power station takes the optimal operation economy of the energy storage power station as an objective function, meets the power demand of a load supplied by energy storage power station equipment and the output limit of a battery, and provides the optimal operation strategy of the energy storage power station by combining with a local electricity price curve of the energy storage power station.
In one implementation mode, the energy storage power station fault early warning analysis is used for drawing a capacity attenuation curve and a voltage change curve of each battery module based on the residual capacity SoH and the terminal voltage of the battery, and performing fault maintenance pre-judgment on the battery modules according to the capacity attenuation curve and the voltage change curve.
In one implementation, the edge computing device has a fast response speed and a fast computing speed, and can quickly respond to load changes and embed various intelligent algorithms to realize battery health state evaluation of the energy storage power station and different functions and corresponding optimal operation strategy development of the energy storage power station on a user side or a power grid.
In one implementation, the intelligent algorithm includes neural network based battery residual capacity SoH estimation, load prediction, and integer hybrid linear/nonlinear energy storage operation optimization.
In one implementation mode, the cloud service platform comprises a battery data analysis module, a strategy generation and pushing module, an energy storage power station maintenance module and an energy storage power station fault early warning module;
the battery data analysis module is used for carrying out balance and operation efficiency analysis among the battery modules based on the battery operation historical data;
the strategy generation and pushing module comprises a battery pack balanced charge-discharge strategy and an optimal charge-discharge strategy for economic operation of the energy storage power station and pushes the strategies to an energy management system EMS of the energy storage power station, so that the optimal charge-discharge strategy of the battery is realized;
the energy storage power station maintenance module correspondingly maintains the battery module influencing the operation efficiency of the system or the battery module which is attenuated too fast based on the detection of the charging and discharging curve of the battery module, and the maintenance comprises the recombination of a battery core in the battery module;
the energy storage power station fault early warning module is used for carrying out pre-judgment and maintenance on battery faults through a big data algorithm based on a large number of historical states of battery residual capacity SoH.
In one implementation mode, the cloud service platform pushes the operation strategy of the energy storage power station to an energy management system EMS of the energy storage power station through a data communication interface, and the data communication interface uses an RS484 port and a Modbus transmission protocol.
Has the advantages that:
1. on the basis of a traditional energy storage grid-connected framework, a data acquisition communication unit is arranged on the side of an energy storage power station and is responsible for acquiring operation data of a local energy storage power station, the data are pushed to an edge computing device and uploaded to a cloud service platform, an edge computing terminal carries out battery module health state assessment and related operation strategy calculation and release, the cloud service platform carries out fault pre-judgment on the energy storage power station, all operation data of the system are uploaded to the cloud service platform according to a certain frequency to be stored and related big data analysis is carried out, the operation and maintenance of the energy storage power station are used, the consumption of communication resources is reduced, the pressure of real-time transmission of a large amount of data and communication between the cloud and the local is reduced, the operation efficiency and the management efficiency of the whole system are improved, and the problem related to the operation data of the energy storage power station is.
2. The system provided by the invention can realize rapid comprehensive evaluation and fault early warning of the energy storage power station and key components thereof, and provides an operation scheme support for refined control management of the energy storage power station.
Drawings
The foregoing and/or other advantages of the invention will become further apparent from the following detailed description of the invention when taken in conjunction with the accompanying drawings.
FIG. 1 is a structural diagram of an energy storage power station state evaluation and operation optimization system based on edge calculation according to the present invention;
Detailed Description
Fig. 1 is a structural diagram of an energy storage power station state evaluation and operation optimization system based on edge computing according to the present invention, which includes an energy storage power station device, a data communication acquisition device, an edge computing device, and a cloud service platform;
the method comprises the following steps that one energy storage power station corresponds to one data communication acquisition device and one edge computing device, and under the comprehensive energy scene with more than two energy storage power stations, the operation data of each energy storage power station is uploaded to the same cloud service platform through the corresponding data communication acquisition device;
the energy storage power station equipment comprises an energy storage unit battery, a bidirectional converter and control unit PCS for converting direct current into alternating current, a battery management system BMS and an energy management system EMS;
the data communication acquisition equipment is used for acquiring the operating data of the energy storage power station, is deployed at the side of the energy storage power station, acquires and forwards the operating data of the bidirectional converter, the control unit PCS and the battery management system BMS in real time to the edge computing device, acquires the data including the voltage, the current, the power and the temperature of the battery module and sends the data to the cloud service platform according to the specified frequency;
the edge computing device is used for evaluating the health state of the battery based on data acquired by the data communication acquisition equipment, embedding an energy storage operation auxiliary decision algorithm, computing the optimal charging and discharging strategy of the energy storage equipment in real time and uploading the computing result to a cloud service platform through the data communication acquisition equipment;
the cloud service platform receives the operation data of the energy storage power station, the battery health state evaluation result and a primary analysis result of the system operation economy, wherein the primary analysis result of the system operation economy refers to a calculation result obtained by the edge calculation device calculating the optimal charging and discharging strategy of the energy storage equipment; the cloud service platform further performs fault early warning analysis on the energy storage power station and decision on an operation strategy of the energy storage power station based on the three parts of data, and pushes the strategy to an Energy Management System (EMS) of the energy storage power station through a data communication interface so as to realize information interaction with energy storage power station equipment.
In this embodiment, the battery management system BMS includes a 3-layer architecture: the battery module BMS, the battery cluster BMS and the battery system BMS, the voltage, the current, the power and the temperature operating parameter of battery module level, battery cluster level and battery system level are collected respectively to 3 layers of framework BMS to with data real-time propelling movement to data communication collection equipment.
In this embodiment, the evaluation of the state of health of the battery is based on a charging and discharging voltage-current curve of the battery module and a battery equivalent circuit model, and is used for estimating the remaining capacity soh (state of health), the internal resistance and the battery terminal voltage of the battery, comparing the battery states of different battery modules, and further judging the operation state of the battery system of the energy storage power station.
In this embodiment, the operation state of the battery system is the battery health state balance degree of different battery modules, the evaluation indexes are the terminal voltage and the battery residual capacity SoH of each battery module, the estimation of the battery residual capacity SoH of different modules is performed by using an internal resistance estimation algorithm based on the detection data of the battery modules, including the charging and discharging voltage and current curves, and if the residual capacity of a certain battery module is lower than the residual capacity of other battery modules and exceeds the threshold T, the battery module needs to be replaced to ensure the operation efficiency and the overall service life of the whole battery system. In this embodiment, the value range of the threshold T is 2% -5% of the total capacity of the battery module.
In this embodiment, the operation strategy of the energy storage power station takes the optimal operation economy of the energy storage power station as a target function, and simultaneously meets the power demand of the load supplied by the energy storage power station equipment and the output limit of the battery, and gives the optimal operation strategy of the energy storage power station by combining with the electricity price curve of the location of the energy storage power station.
In this embodiment, the energy storage power station fault early warning analysis is to draw a capacity attenuation curve and a voltage change curve for each battery module based on the remaining capacity SoH and the terminal voltage of the battery, and to perform the fault repair prejudgment on the battery modules according to the capacity attenuation curve and the voltage change curve.
In this embodiment, the edge calculation device has a fast response speed and a fast calculation speed, and can quickly respond to load changes and embed various intelligent algorithms to evaluate the battery health state of the energy storage power station and develop different functions and corresponding optimal operation strategies of the energy storage power station on the user side or on the power grid.
In this embodiment, the intelligent algorithm includes a neural network-based battery residual capacity SoH estimation, load prediction, and integer hybrid linear/nonlinear energy storage operation optimization.
In this embodiment, the cloud service platform includes a battery data analysis module, a policy generation and pushing module, an energy storage power station maintenance module, and an energy storage power station fault early warning module;
the battery data analysis module is used for carrying out balance and operation efficiency analysis among the battery modules based on the battery operation historical data;
the strategy generation and pushing module comprises a battery pack balanced charge-discharge strategy and an optimal charge-discharge strategy for economic operation of the energy storage power station and pushes the strategies to an energy management system EMS of the energy storage power station, so that the optimal charge-discharge strategy of the battery is realized;
the energy storage power station maintenance module correspondingly maintains the battery module influencing the operation efficiency of the system or the battery module which is attenuated too fast based on the detection of the charging and discharging curve of the battery module, and the maintenance comprises the recombination of a battery core in the battery module;
the energy storage power station fault early warning module is used for carrying out pre-judgment and maintenance on battery faults through a big data algorithm based on a large number of historical states of battery residual capacity SoH.
In this embodiment, the cloud service platform pushes the energy storage power station operation strategy to an energy management system EMS of the energy storage power station through a data communication interface, and the data communication interface uses an RS484 port and a Modbus transmission protocol.
The invention provides an energy storage power station state evaluation and operation optimization system based on edge calculation, and a plurality of methods and ways for implementing the technical scheme are provided, the above description is only a preferred embodiment of the invention, and it should be noted that, for a person skilled in the art, a plurality of improvements and embellishments can be made without departing from the principle of the invention, and the improvements and embellishments should also be regarded as the protection scope of the invention. All the components not specified in the present embodiment can be realized by the prior art.
Claims (10)
1. An energy storage power station state evaluation and operation optimization system based on edge calculation is characterized by comprising energy storage power station equipment, data communication acquisition equipment, an edge calculation device and a cloud service platform;
the method comprises the following steps that one energy storage power station corresponds to one data communication acquisition device and one edge computing device, and under the comprehensive energy scene with more than two energy storage power stations, the operation data of each energy storage power station is uploaded to the same cloud service platform through the corresponding data communication acquisition device;
the energy storage power station equipment comprises a battery module, a bidirectional energy storage converter and control unit PCS for converting direct current into alternating current, a battery management system BMS and an energy management system EMS;
the data communication acquisition equipment is used for acquiring the operating data of the energy storage power station, is deployed at the side of the energy storage power station, acquires and forwards the operating data of the energy storage converter, the control unit PCS and the battery management system BMS in real time to the edge computing device, acquires the data including the voltage, the current, the power and the temperature of the battery module and sends the data to the cloud service platform according to the specified frequency;
the edge computing device is used for evaluating the health state of the battery based on data acquired by the data communication acquisition equipment, embedding an energy storage operation auxiliary decision algorithm, computing the optimal charging and discharging strategy of the energy storage equipment in real time and uploading the computing result to a cloud service platform through the data communication acquisition equipment;
the cloud service platform receives the operation data of the energy storage power station, the battery health state evaluation result and a primary analysis result of the system operation economy, wherein the primary analysis result of the system operation economy refers to a calculation result obtained by the edge calculation device calculating the optimal charging and discharging strategy of the energy storage equipment; the cloud service platform further performs fault early warning analysis on the energy storage power station and decision on an operation strategy of the energy storage power station based on the three parts of data, and pushes the strategy to an Energy Management System (EMS) of the energy storage power station through a data communication interface so as to realize information interaction with energy storage power station equipment.
2. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 1, wherein:
the battery management system BMS comprises a 3-layer framework: the battery module BMS, the battery cluster BMS and the battery system BMS, the voltage, the current, the power and the temperature operating parameter of battery module level, battery cluster level and battery system level are collected respectively to 3 layers of framework BMS to with data real-time propelling movement to data communication collection equipment.
3. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 2, wherein:
the evaluation of the health state of the battery is based on a charging and discharging voltage current curve of a battery module and a battery equivalent circuit model, the residual capacity SoH, the internal resistance and the terminal voltage of the battery are estimated, the battery states of different battery modules are compared, and the running state of a battery system of an energy storage power station is further judged.
4. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 3, wherein:
the operation state of the battery system is the battery health state balance degree of different battery modules, the evaluation indexes are terminal voltage and battery residual capacity SoH of each battery module, based on battery module detection data including charging and discharging voltage and current curves, the estimation of the battery residual capacity SoH of different modules is carried out by adopting an internal resistance estimation algorithm, and if the fact that the residual capacity of a certain battery module is lower than the residual capacity of other battery modules and exceeds a threshold value T is found, the battery module needs to be replaced to ensure the operation efficiency and the whole service life of the whole battery system.
5. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 1, wherein:
the operation strategy of the energy storage power station takes the optimal economical efficiency of the energy storage power station as a target function, simultaneously meets the power requirement of the load supplied by the energy storage power station equipment and the output limit of the battery, and provides the optimal operation strategy of the energy storage power station by combining the electricity price curve of the location of the energy storage power station.
6. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 1, wherein:
and the energy storage power station fault early warning analysis is used for drawing a capacity attenuation curve and a voltage change curve of each battery module based on the residual capacity SoH and the terminal voltage of the battery, and performing fault maintenance pre-judgment on the battery modules according to the capacity attenuation curve and the voltage change curve.
7. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 1, wherein:
the edge computing device has higher response speed and computing speed, can quickly respond to load change and is embedded with various intelligent algorithms to realize the evaluation of the battery health state of the energy storage power station and the development of different functions and corresponding optimal operation strategies of the energy storage power station on a user side or a power grid.
8. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 7, wherein:
the intelligent algorithm comprises battery residual capacity SoH estimation, load prediction and integer mixed linear/nonlinear energy storage operation optimization based on a neural network.
9. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 1, wherein:
the cloud service platform comprises a battery data analysis module, a strategy generation and pushing module, an energy storage power station maintenance module and an energy storage power station fault early warning module;
the battery data analysis module is used for carrying out balance and operation efficiency analysis among the battery modules based on the battery operation historical data;
the strategy generation and pushing module comprises a battery pack balance charge-discharge strategy, an optimal charge-discharge strategy for economic operation of the energy storage power station and an Energy Management System (EMS) for pushing the strategy to the energy storage power station so as to realize the optimal charge-discharge strategy of the battery;
the energy storage power station maintenance module correspondingly maintains the battery module influencing the operation efficiency of the system or the battery module which is attenuated too fast based on the detection of the charging and discharging curve of the battery module, and the maintenance comprises the recombination of a battery core in the battery module;
the energy storage power station fault early warning module is used for carrying out pre-judgment and maintenance on battery faults through a big data algorithm based on a large number of historical states of battery residual capacity SoH.
10. The energy storage power station state evaluation and operation optimization system based on edge computing of claim 1, wherein:
the cloud service platform pushes the operation strategy of the energy storage power station to an energy management system EMS of the energy storage power station through a data communication interface, and the data communication interface uses an RS484 port and a Modbus transmission protocol.
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