CN111969628B - Solving method of optimal control strategy of energy storage power station, storage medium and equipment - Google Patents

Solving method of optimal control strategy of energy storage power station, storage medium and equipment Download PDF

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CN111969628B
CN111969628B CN202010624993.5A CN202010624993A CN111969628B CN 111969628 B CN111969628 B CN 111969628B CN 202010624993 A CN202010624993 A CN 202010624993A CN 111969628 B CN111969628 B CN 111969628B
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energy storage
power station
storage power
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interval
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CN111969628A (en
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蒋科
苏麟
郑锋
张诗滔
钱康
姜华
蔡博戎
孟高军
闫安心
史洋
鹿峪宁
张曌
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Nanjing Institute of Technology
China Energy Engineering Group Jiangsu Power Design Institute Co Ltd
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China Energy Engineering Group Jiangsu Power Design Institute Co Ltd
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    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/042—Backward inferencing
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
    • H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
    • H02J7/005—Detection of state of health [SOH]
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
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Abstract

The invention discloses a method for solving an optimal control strategy of an energy storage power station, which comprises the following steps: when the energy storage power station is in a critical state of charge, solving the control strategy of the energy storage power station by adopting a chess-playing algorithm to obtain the control strategy of the current state of the energy storage power station; in the process of playing chess, if the constraint condition set is exceeded, the playing algorithm is stopped, and the energy storage power station stops running; the critical charge state is a critical charge value of a charge state interval corresponding to the energy storage power station executing the lowest total cost control strategy and a charge state interval corresponding to the battery protection strategy; the control strategy includes a lowest total cost control strategy and a battery protection strategy. The method can solve the control strategy executed when the energy storage power station is in the critical state of charge, so that the energy storage power station obtains the optimal control strategy.

Description

Solving method of optimal control strategy of energy storage power station, storage medium and equipment
Technical Field
The invention relates to a solving method, a storage medium and equipment of an optimal control strategy of an energy storage power station, and belongs to the field of energy storage power station control.
Background
In recent years, with the increase of power demand, the scale of a power system is gradually enlarged, the complexity of a power grid is also increased, and users pay more attention to the reliability and the power quality of power supply. Transient imbalance of electrical energy can cause many unstable problems that affect the normal operation of the load, and even when severe, can cause system disruption, causing severe economic losses. Energy storage technology can provide an effective and simple solution to this problem. The application market of the energy storage system is wide, and the energy storage system is realized from personal and household energy storage systems to high-capacity energy storage power stations and is the application range of the high-capacity energy storage system; and the technical advantage of energy storage makes the device irreplaceable in solving the problems of urban power shortage and huge peak load regulation pressure of a power grid, solving the large-scale grid-connection problem of clean energy power generation and applying to the rapid development of electric automobile charging facilities.
Each energy storage power station consists of a plurality of battery packs and converters, each battery pack consists of a plurality of batteries, and a data monitoring system is required to uniformly acquire, monitor, analyze and predict the batteries. The data monitoring object of the energy storage power station has the characteristics of large number of batteries, large information amount, system state change along with operation and the like, panoramic analysis and prediction are needed, meanwhile, the real-time power requirements of scheduling at all levels are met, and the safe and economic operation of the energy storage power station determines a centralized management, unified coordination and real-time regulation and control system mode.
Disclosure of Invention
The invention provides a method for solving an optimal control strategy of an energy storage power station, which can solve the control strategy executed when the energy storage power station is in a critical state of charge, so that the energy storage power station obtains the optimal control strategy.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a method for solving an optimal control strategy of an energy storage power station comprises the following steps: when the energy storage power station is in a critical state of charge, solving the control strategy of the energy storage power station by adopting a chess-playing algorithm to obtain the control strategy of the current state of the energy storage power station; in the process of playing chess, if the constraint condition set is exceeded, the playing algorithm is stopped, and the energy storage power station stops running; the critical charge state is a critical charge value of a charge state interval corresponding to the energy storage power station executing the lowest total cost control strategy and a charge state interval corresponding to the battery protection strategy; the control strategy includes a lowest total cost control strategy and a battery protection strategy.
Further, the step of solving the control strategy of the energy storage power station by adopting the playing algorithm comprises the following steps: the participants obtain the result of the situation from the initial situation according to the rules until the final situation appears, and then the game is finished; and outputting the final chess playing rules in the final situation as the operation strategy of the energy storage power station.
Further, the playing algorithm is a gobang playing algorithm and is represented by a four-tuple W:
W＝(Q，P，G，J) (3)
wherein Q is the set of the players, Q ═ Q { Q }1,Q2}，Q1The total cost C of the energy storage power station; q2The health degree SOH of the energy storage power station; p is the set of effective situations in the game, G is the game rule, and J is the set of the game results of the effective situations in the game.
Further, the playing rules G include G12And G21；G12To appear Q1Lead Q2The rules of playing chess at the moment of local time, at the moment, the SOH of the energy storage power station is greater than the SOHminIf so, the energy storage power station executes a minimum total cost control strategy; g21To appear Q2Lead Q1The rules of playing chess at the moment, the SOH of the energy storage power station is less than or equal to the SOHminAt the moment, the energy storage power station stops runningAnd executing a battery protection strategy.
Further, the set of constraints includes a voltage of the energy storage power station, a current of the energy storage power station, and a temperature of the energy storage power station.
A computer readable storage medium storing one or more programs, characterized in that: the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods of claims 1-6.
A computing device, characterized by: comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-6.
According to the method, the time control strategy is solved under the critical state of charge of the energy storage power station, so that the running cost of the power station is reduced while the reliable running of the power station is ensured and the service life of a battery is prolonged. And the method is simple in calculation, easy to operate and easy to popularize.
Drawings
Fig. 1 is a flowchart of a method for solving an optimal control strategy of an energy storage power station according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the evolution process of the playing state of the gobang playing algorithm in the embodiment of the present invention;
fig. 3 is a schematic diagram of charge interval division according to an embodiment of the present invention.
Detailed Description
For a better understanding of the nature of the invention, its description is further set forth below in connection with the specific embodiments and the drawings.
The invention provides a method for solving an optimal control strategy of an energy storage power station, which specifically comprises the following steps as shown in figure 1:
the method comprises the steps of monitoring the state of charge (SOC) of the energy storage power station by using a data monitoring system, and dividing the working state of the energy storage power station into five intervals. As shown in fig. 1, the SOC of 20% to 80% is interval one, the SOC of 80% to 90% is interval two, and the SOC of 10% to 20% is interval three; the SOC is in the range of four when the SOC is between 90% and 100%, and in the range of five when the SOC is between 0% and 10%.
When the SOC is in the interval one, the operation of the energy storage power station meets the condition that the operation cost is the lowest.
When the SOC is in the interval two and the interval three, the operation of the energy storage power station meets the condition that the service life of the battery is longest.
And step two, establishing a target function of the cost of the energy storage power station and a function of the health degree of the battery.
1. The total cost of the energy storage power station is mainly considered as operation and maintenance cost, loss cost and fixed cost, and the objective function of the cost is as follows:
minC＝Cfix+Closs+Cf (1)
wherein C is the total cost of the energy storage power station, CfixFor operation and maintenance costs, ClossTo lose cost, CfFor a fixed cost.
Fuzzy processing is carried out on the objective function of the cost of the energy storage power station according to a membership function, wherein the membership function is as follows:
Figure BDA0002566287490000051
in the formula: f. ofiIs the ith objective function value; a isiThe objective function value after fuzzification; f. ofmaxAnd fminIs the maximum and minimum of the objective function.
2. Battery life is reflected in the degree of health (SOH) of the battery. SOH is a battery performance state, i.e., a degree of health, reflected by a battery capacity, and is calculated by equation (3):
Figure BDA0002566287490000052
wherein, CbatBattery system for energy storage power stationCurrent capacity of Cbat,0For the initial capacity, C, of the battery system of the energy storage plant1Is the capacity loss of the battery system of the energy storage power station.
And fuzzifying the health degree of the battery by adopting the membership function.
After the energy storage power station is put into operation, a battery system of the energy storage power station can be charged or discharged according to power scheduling. During the charging and discharging process of the battery, the SOH will gradually decay until the SOH drops to a certain value
Figure BDA0002566287490000053
And then, the battery system is considered to be incapable of continuously completing the scheduling task and needs to be replaced. Wherein the content of the first and second substances,
Figure BDA0002566287490000054
the SOH lower limit value of the ith battery system.
And step three, solving the control strategy of the energy storage power station in the critical charge state by adopting a playing algorithm. Optionally, a gobang playing algorithm is adopted for solving. Wherein the critical states of charge include: the SOC is at the boundary of the first interval and the second interval, or the SOC is at the boundary of the first interval and the third interval.
1. As shown in fig. 2, the gobang playing algorithm specifically includes:
the playing algorithm can be represented by a quadruple W as shown in formula (3).
W＝(Q，P，G，J) (3)
Wherein Q is the set of participants, P is the set of effective situations in playing, G is the rules of playing, and J is the set of results of playing.
Set Q of playing participants ═ { Q ═ Q1,Q2}. Wherein Q1Represents the total cost C of the energy storage power station; q2Representing the health SOH of the energy storage plant.
Set of active facets P ═ P0，p1，p2，……，pn}. Wherein p is0Representing the initial situation, pnIs a pair of two partiesAnd (5) the final situation of chess ending.
Rule G ═ G of playing12,G21}，G12Represents the occurrence of Q1Lead Q2The temporary local time game rule of (1) the SOH of the energy storage power station is greater than the SOHminIf so, the energy storage power station executes a minimum total cost control strategy; g21To appear Q2Lead Q1The rules of playing chess at the moment, the SOH of the energy storage power station is less than or equal to the SOHminAnd at the moment, the energy storage power station stops running, and a battery protection strategy is executed to protect the service life of the battery.
The set of the results of the chess is recorded as J ═ J0(p0)，J1(p1)，…，Ji(pi)，…，Jn(pn)}. Wherein, Ji(pi) Is piAnd (5) a result of the situation.
2. Constraint conditions of a gobang playing algorithm.
The constraint condition of the gobang playing algorithm is the safety performance index of the energy storage power station, and the energy storage power station stops running once the constraint condition is exceeded in the playing process. Optionally, the constraint condition is sent to the block chain, so that a distributed data storage function is realized, and the data is guaranteed to be non-tamper-able.
In the process of playing chess, the safety performance indexes of the energy storage power station are monitored in real time, and the safety of the energy storage power station is ensured when playing chess.
Defining a constraint condition set as Y ═ V, I, T }, wherein V is the voltage of the energy storage power station, I is the current of the energy storage power station, and T is the temperature of the energy storage power station, then the constraint condition objective function is:
Yi min≤Y≤Yi max(4)
wherein: y isi minAs a lower limit of the constraint, Yi maxIs the upper limit of the constraint.
3. And when the state of charge (SOC) of the energy storage power station is at the junction of the first interval and the second interval or at the junction of the first interval and the third interval, carrying out a gobang playing algorithm.
As shown in FIG. 3, the playing participant Q1、Q2From the initial play situation p0Initially, a playing strategy for maximizing the benefit of the energy storage power station is established according to a playing rule G until a final situation p appearsnIf yes, the game is ended. In the final situation pnAnd outputting the final chess playing rules as an operation strategy of the energy storage power station, namely controlling the energy storage power station to meet the aim of minimizing the operation cost, or closing the energy storage power station to operate for battery protection.
The invention is explained by taking an example of solving an optimal control strategy of a certain energy storage power station.
Of a first battery system of the energy storage plant
Figure BDA0002566287490000071
At 50%, i.e., when the SOH of the battery system of the energy storage power station decays to 50%, the battery system is considered to be unable to continue operating.
And when the SOC of the energy storage power station is at the boundary of the first interval and the second interval or the SOC is at the boundary of the first interval and the third interval, carrying out a game playing algorithm.
Set of its effective facets P ═ P0，p1，p2，……，pn}
Initial situation p0The method comprises the following steps: at the moment, the SOH value of the energy storage power station is 85 percent and is greater than the SOHminIf so, it is determined as Q1Lead Q2In the temporary situation, the playing rule is G12Result of game J0(p0)＝G12。
Until final situation pnThe method comprises the following steps: at this time, the SOH value of the energy storage power station is 45 percent and is less than the SOHminIf so, it is determined as Q2Lead Q1In the temporary situation, the playing rule is G21Result of game Jn(pn)＝G21。
In the final situation pnOutputting final playing rule G21The method is used as an operation strategy of the energy storage power station, namely the energy storage power station closes the energy storage power station to operate so as to carry out battery protection.
In the process of playing the chess,and monitoring the safety performance index of the energy storage power station in real time. The lower limit of the safety performance index of the energy storage power station is Yi min0.4kV, 10A, 10 ℃ } with an upper limit of Yi max1kV, 50A, 50 ℃. And when the real-time monitoring value exceeds the upper limit or the lower limit, the playing is stopped, and the energy storage power station is stopped.
A computer readable storage medium storing one or more programs, characterized in that: the one or more programs include instructions which, when executed by a computing device, cause the computing device to perform the method described above.
A computing device, characterized by: comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing the above-described methods.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (3)

1. A method for solving an optimal control strategy of an energy storage power station is characterized by comprising the following steps:
when the energy storage power station is in a critical state of charge, solving the control strategy of the energy storage power station by adopting a chess-playing algorithm to obtain the control strategy of the current state of the energy storage power station; in the process of playing chess, if the constraint condition set is exceeded, the playing algorithm is stopped, and the energy storage power station stops running;
the critical charge state is a critical charge value of a charge state interval corresponding to the energy storage power station executing the lowest total cost control strategy and a charge state interval corresponding to the battery protection strategy;
the control strategy comprises a lowest total cost control strategy and a battery protection strategy;
the state of charge interval corresponding to the energy storage power station executing the lowest total cost control strategy is interval one, and the state of charge SOC is 20% -80%; the SOC interval corresponding to the execution of the battery protection strategy comprises an interval two and an interval three, and the SOC of the interval two is 80-90%; the SOC of the third interval is 10-20%;
the method for solving the control strategy of the energy storage power station by adopting the playing algorithm comprises the following steps:
the participants obtain the result of the situation from the initial situation according to the rules until the final situation appears, and then the game is finished;
outputting a final chess playing rule in a final situation to serve as an operation strategy of the energy storage power station;
wherein the critical states of charge include: the SOC is positioned at the junction of the interval I and the interval II, or the SOC is positioned at the junction of the interval I and the interval III;
the playing algorithm is a gobang playing algorithm and is represented by adopting a four-tuple W:
W＝(Q，P，G，J) (3)
wherein Q is the set of participants in the game, Q ═ { Q ═ Q1,Q2}，Q1The total cost C of the energy storage power station; q2The health degree SOH of the energy storage power station; p is a set of effective situations in the playing, G is a playing rule, and J is a set of playing results of the effective situations in the playing;
set of active facets P ═ P0，p1，p2，……，pn}; wherein p is0Representing the initial situation, pnThe final situation of the end of the chess playing of the two parties;
the playing rules G comprise G12And G21；G12To appear Q1Lead Q2The rules of playing chess at the moment of local time, at the moment, the SOH of the energy storage power station is greater than the SOHminIf so, the energy storage power station executes a minimum total cost control strategy; g21To appear Q2Lead Q1The rules of playing chess at the moment, the SOH of the energy storage power station is less than or equal to the SOHminAt the moment, the energy storage power station stops running and executes a battery protection strategy;
the set of the results of the chess is recorded as J ═ J0(p0)，J1(p1)，…，Ji(pi)，…，Jn(pn) }; wherein, Ji(pi) Is piA result of the game;
the constraint condition of the gobang playing algorithm is the safety performance index of the energy storage power station, and the energy storage power station stops running once the constraint condition is exceeded in the playing process;
defining a constraint condition set as Y ═ V, I, T }, wherein V is the voltage of the energy storage power station, I is the current of the energy storage power station, and T is the temperature of the energy storage power station, then the constraint condition objective function is:
Figure FDA0003620732670000031
wherein: y isi minAs a lower limit of the constraint, Yi maxIs the upper limit of the constraint;
when the state of charge (SOC) of the energy storage power station is at the junction of the first interval and the second interval or at the junction of the first interval and the third interval, carrying out a gobang game playing algorithm;
player participant Q1、Q2From the initial play situation p0Starting to make a playing strategy for maximizing the benefit of the energy storage power station according to the playing rule G until the final situation p appearsnIf yes, the game is finished; in the final situation pnAnd outputting the final chess playing rules as an operation strategy of the energy storage power station, namely controlling the energy storage power station to meet the aim of minimizing the operation cost, or closing the energy storage power station to operate for battery protection.
2. A computer readable storage medium storing one or more programs, characterized in that: the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform the method of claim 1.
3. A computing device, characterized by: comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing the method of claim 1.
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