Battery energy storage system energy management method and system

Abstract

The invention discloses an energy management method and system for a battery energy storage system. The method comprises the following steps: dividing a charge state interval according to the technical characteristics of an energy storage battery and an energy storage cost model; dynamically adjusting the charge state interval and the charge and discharge quantity through the real-time first state data; establishing a first optimization mechanism comprising the charge state constraint so as to perform optimal configuration on the energy storage battery; and a resource allocation mechanism is introduced into the first optimization mechanism to compensate the energy storage battery deviating from the charge state interval, and the energy storage battery is encouraged to recover to the optimal state interval. Optimized configuration and service are provided for the energy storage battery, so that the operation of the energy storage battery is more efficient, and the service life of the energy storage battery is prolonged; the state of charge of the energy storage battery can be adjusted in time through the compensation process, the state of charge is prevented from deviating from the optimal interval, and the reliability of the system is improved.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to an energy management method and system for a battery energy storage system. Background Art

[0002] With the rapid development of the new energy industry, especially the large-scale access of renewable energy such as solar energy and wind energy to the power grid, battery energy storage systems, as an important energy storage technology, play a key role in solving the intermittent and volatile nature of new energy, improving the stability of the power grid, and achieving peak load shifting. Battery energy storage systems can store excess electrical energy and release it when needed, thereby effectively balancing the supply and demand of the power grid and improving energy efficiency. The energy management system (EMS) is a core component of the battery energy storage system. It is like a brain, responsible for monitoring, controlling and optimizing the operation of the energy storage system. EMS can ensure the safe, efficient and stable operation of the energy storage system by monitoring the status of the batteries, environmental conditions and energy flow in the energy storage facilities in real time.

[0003] However, despite the important role played by EMS in battery energy storage systems, existing technologies still face the following problems and challenges: (1) Inaccurate SOC management: Traditional EMS often adopts a simple limit management strategy in SOC (state of charge) management, that is, when the SOC reaches the set upper or lower limit, it actively reduces the charging and discharging power or stops the operation. This method cannot ensure that the energy storage battery operates within the optimal SOC range, thus affecting the battery life and the overall performance of the energy storage system. (2) Inflexible energy scheduling: Traditional EMS lacks flexibility in energy scheduling and cannot respond and adjust quickly according to real-time changes in energy demand and system status, resulting in limited effectiveness of the energy storage system in terms of peak shaving and valley filling and smoothing fluctuations. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides an energy management method and system for a battery energy storage system to solve the problem that the energy management system in the existing battery energy storage system is not sophisticated and flexible enough in SOC management and energy scheduling, resulting in the inability to ensure that the battery operates in the optimal state and fails to effectively respond to real-time changing energy demands.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides an energy management method for a battery energy storage system, comprising: dividing the state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model; dynamically adjusting the state of charge interval and the charge and discharge amount through real-time first state data; establishing a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery; introducing a resource allocation mechanism in the first optimization mechanism to compensate the energy storage battery that deviates from the state of charge interval, and encourage it to return to the optimal state interval.

[0008] As a preferred solution of the energy management method of the battery energy storage system described in the present invention, the division of the state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model includes:

[0009] According to the technical characteristics of the energy storage battery and the energy storage cost model, the state of charge interval is divided into a first state of charge interval, a second state of charge interval and a third state of charge interval, and each state of charge interval corresponds to a different charging and discharging strategy.

[0010] As a preferred solution of the energy management method for the battery energy storage system of the present invention, the dynamically adjusting the state of charge interval by real-time first state data comprises:

[0011] When the energy storage battery is at a peak load, the upper limit of the first state of charge interval is increased, and the energy storage battery is encouraged to discharge; when the market price of the energy storage battery is high, the range of the first state of charge interval is narrowed to reduce over-discharge; when the energy storage battery is at a low load, the lower limit of the third state of charge interval is lowered, and the energy storage battery is encouraged to charge.

[0012] As a preferred solution of the energy management method of the battery energy storage system described in the present invention, dynamically adjusting the charge and discharge amount through real-time first state data includes:

[0013] When the charge and discharge amount is dynamically adjusted through the real-time first state data, the first state data is energy cost, power cost and temperature cost, the energy cost is related to the charge and discharge amount of the energy storage battery, the power cost is related to the charge and discharge power of the energy storage battery, and the temperature cost is related to the temperature of the energy storage battery itself;

[0014] When the state of charge is high and the predicted market price is low, the bid price is dynamically lowered in real time to increase the discharge capacity of the energy storage battery; when the state of charge is low and the predicted market price is high, the bid price is dynamically increased in real time to increase the charge capacity of the energy storage battery.

[0015] As a preferred solution of the energy management method of the battery energy storage system described in the present invention, wherein: the establishment of a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery includes:

[0016] When the energy storage battery is in the first state of charge interval, it indicates that the battery power is sufficient. At this time, the system limits the discharge amount of the energy storage battery, and the expression is:

[0017] When the energy storage battery is in the third state of charge interval, it indicates that the battery power is insufficient. At this time, the system limits the charging amount of the energy storage battery, and the expression is:

[0018] Among them, SOC represents the current state of the energy storage battery. high and SOC low They represent the thresholds of the first state of charge interval and the third state of charge interval, respectively, discharge (SOC) and x charge (SOC) represents the upper limit of the discharge amount and charge amount related to the state of charge.

[0019] As a preferred solution of the energy management method of the battery energy storage system of the present invention, wherein: the introduction of the resource allocation mechanism to compensate the energy storage battery deviating from the state of charge range includes:

[0020] The compensation process includes charging compensation and discharging compensation;

[0021] When the state of charge is lower than the lower limit of the third state of charge range, the energy storage battery is charged through market transactions or scheduling instructions; when the state of charge is higher than the upper limit of the first state of charge range, the energy storage battery is discharged through market transactions or scheduling instructions.

[0022] As a preferred solution of the energy management method of the battery energy storage system of the present invention, wherein: each state of charge interval corresponds to a different charging and discharging strategy including:

[0023] When the state of charge of the energy storage battery is in the first state of charge interval, the charge and discharge strategy is to discharge and charge in small amounts to maintain the state of charge of the energy storage battery within a first threshold range;

[0024] When the state of charge of the energy storage battery is in the second state of charge range, the charge and discharge strategy is to flexibly adjust the charge and discharge according to market demand and system status;

[0025] When the state of charge of the energy storage battery is in the third state of charge interval, the charge and discharge strategy is charging and discharging in small amounts to maintain the state of charge of the energy storage battery within the first threshold range.

[0026] In a second aspect, the present invention provides an energy management system for a battery energy storage system, comprising:

[0027] A state interval division module is used to divide the state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model;

[0028] A dynamic adjustment module, used for dynamically adjusting the state of charge interval and the charge and discharge amount according to the real-time first state data;

[0029] A constraint management module, used to establish a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery;

[0030] The incentive compensation module is used to introduce a resource allocation mechanism into the first optimization mechanism to compensate the energy storage battery that deviates from the charge state range, and encourage it to return to the optimal state range.

[0031] In a third aspect, the present invention provides a computing device, comprising:

[0032] Memory and processor;

[0033] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the battery energy storage system energy management method are implemented.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the battery energy storage system energy management method.

[0035] Compared with the prior art, the present invention has the following beneficial effects: the present invention dynamically adjusts the target range of the state of charge according to the state of the energy storage battery, so that the energy storage system can better adapt to market changes, and the electrochemical energy storage cost model established takes into account multiple factors such as the discharge depth, rate, and working environment temperature of the energy storage battery, thereby improving the flexibility of the system, enabling the system to make optimal decisions based on real-time data and predicted information, thereby improving the intelligence level of the system; and, the present invention provides optimized configuration and services for the energy storage battery, making the operation of the energy storage battery more efficient, and by associating the charging and discharging strategy with the state of charge range, adjusting the charging and discharging behavior according to the range in which the state of charge is located, thereby helping to extend the service life of the energy storage battery; in addition, the present invention encourages the energy storage battery to return to the optimal state of charge range by introducing a resource allocation mechanism, thereby helping to maintain the stability of the system, and at the same time, through the compensation process, the state of charge of the energy storage battery can be adjusted in time to avoid its deviation from the optimal range, thereby improving the reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0037] Figure 1 The figure is a schematic diagram of the overall process logic of a battery energy storage system energy management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0039] Example 1

[0040] Reference Figure 1 As an embodiment of the present invention, a battery energy storage system energy management method is provided, such as Figure 1 The specific steps shown include:

[0041] S100: Divide the state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model;

[0042] S200: dynamically adjusting the state of charge interval and the charge and discharge amount according to the real-time first state data;

[0043] S300: Establishing a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery;

[0044] S400: Introducing a resource allocation mechanism in the first optimization mechanism to compensate the energy storage battery that deviates from the state of charge range, and encouraging it to return to the optimal state range;

[0045] It should be noted that the present invention dynamically adjusts the target range of the state of charge according to the state of the energy storage battery, so that the energy storage system can better adapt to market changes, and the established electrochemical energy storage cost model takes into account multiple factors such as the discharge depth, rate, and working environment temperature of the energy storage battery, thereby improving the flexibility of the system, enabling the system to make optimal decisions based on real-time data and predicted information, thereby improving the intelligence level of the system; and the present invention provides optimized configuration and services for the energy storage battery, making the operation of the energy storage battery more efficient, and by associating the charging and discharging strategy with the state of charge range, adjusting the charging and discharging behavior according to the range in which the state of charge is located, thereby helping to extend the service life of the energy storage battery; in addition, the present invention encourages the energy storage battery to return to the optimal state of charge range by introducing a resource allocation mechanism, thereby helping to maintain the stability of the system, and at the same time, through the compensation process, the state of charge of the energy storage battery can be adjusted in time to avoid it deviating from the optimal range, thereby improving the reliability of the system.

[0046] In the embodiment of the present application, the above step S100 includes the following sub-steps A1-A2;

[0047] In A1: the state of charge interval is divided into a first state of charge interval, a second state of charge interval and a third state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model;

[0048] In A2: Each state of charge interval corresponds to a different charging and discharging strategy;

[0049] Specifically, the technical characteristics of energy storage batteries include: battery performance curve, dynamic response capability, temperature sensitivity and safety protection mechanism, and the energy storage cost model includes: initial investment cost, operation and maintenance cost, energy loss cost and opportunity cost;

[0050] In an optional embodiment, the calculation expression of the technical characteristics of the energy storage battery is:

[0051]

[0052] Among them, SOC target is the target range of the state of charge, that is, the state of charge level that the energy storage battery is expected to maintain, E battery is the current energy of the energy storage battery, E max is the maximum energy of the energy storage battery, P battery is the power output of the energy storage battery, P demand is the load demand of the energy storage battery, C battery is the cost of the energy storage battery, N cycles is the cycle life of the energy storage battery, which is related to the state of charge range, μ is the charging efficiency of the energy storage battery, T is the temperature of the energy storage battery, and T ref is the reference temperature of the energy storage battery, KT is the temperature compensation coefficient of the energy storage battery, ν is the discharge efficiency of the energy storage battery, i is the number of times the safety protection mechanism is triggered, and λ1, λ2 and λ3 are all weight coefficients used to balance the priorities between different factors of the energy storage battery.

[0053] In an optional embodiment, the calculation expression of the energy storage cost model is:

[0054]

[0055] C EL =C EL (P charge (t),P discharge (t),η charge ,η discharge )

[0056] C opp =P market (t)*(P discharge (t)*η discharge -P charge (t) / η charge )

[0057] Among them, C init is the initial investment cost, C OM is the operation and maintenance cost, which is related to the loss and aging rate of the energy storage battery. EL is the energy loss cost, which is related to the energy loss during the charging and discharging process, C opp is the opportunity cost, which is related to the timing of charging and discharging operations of energy storage batteries in the electricity market. charge is the charging power of the energy storage battery, P discharge is the discharge power of the energy storage battery, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, t is the working time of the energy storage battery, r is the discount rate, which is used to discount future costs to current value, P market (t) is the market electricity price at time t, and SOC(t) is the SOC interval value at time t.

[0058] In an optional embodiment, the state of charge interval is divided into a first state of charge interval, a second state of charge interval and a third state of charge interval; the first state of charge interval refers to an interval in which the state of charge of the energy storage battery is relatively high, such as 70% to 100%. In order to prevent safety hazards and shortened battery life caused by overcharging, the main strategy in this interval is to limit charging and give priority to discharging to maintain the state of charge of the battery at a more reasonable level, so that energy can continue to be effectively stored in subsequent use; the second state of charge interval refers to an interval in which the state of charge of the energy storage battery is at an intermediate level, such as 30% to 70%. In this interval, the energy storage system can flexibly adjust the charging and discharging strategy according to actual needs, and it is possible to charge or discharge to achieve the purpose of peak shaving and valley filling, that is, charging when the grid load is low and discharging during peak hours; the third state of charge interval refers to an interval in which the state of charge of the energy storage battery is relatively low, such as 0 to 30%. In this interval, the energy storage system mainly adopts a charging strategy to improve the state of charge of the battery, avoid damage caused by deep discharge of the battery, and prepare to provide energy support for peak hours or emergencies.

[0059] Specifically, each state of charge interval corresponds to different charging and discharging strategies including:

[0060] When the state of charge of the energy storage battery is in the first state of charge interval, the charge and discharge strategy is to discharge and charge in small amounts to maintain the state of charge of the energy storage battery within the first threshold range;

[0061] When the state of charge of the energy storage battery is in the second state of charge range, the charging and discharging strategy is to flexibly adjust the charging and discharging according to market demand and system status;

[0062] When the state of charge of the energy storage battery is in the third state of charge interval, the charge and discharge strategy is charging and discharging a small amount to maintain the state of charge of the energy storage battery within the first threshold range;

[0063] Exemplarily, for the first state of charge interval, the first threshold range can be set to 80% to 95%. When the state of charge of the battery rises to around 95%, the system should stop charging, and when the state of charge drops to around 80%, a small amount of charging can be allowed to ensure that the state of charge does not drop too low but can still continue to discharge; for the third state of charge interval, the first threshold range can be set to 5% to 20%. When the state of charge of the battery drops to around 5%, the system should start the charging process, and when the state of charge rises to around 20%, a small amount of discharging can be allowed to ensure that the state of charge does not drop too high but can still continue to charge.

[0064] In the embodiment of the present application, the above step S200 includes the following sub-steps B1-B2;

[0065] In B1: dynamically adjusting the state of charge interval through real-time first state data;

[0066] In B2: dynamically adjusting the charge and discharge amount through the real-time first state data;

[0067] In an optional embodiment, the first state data is the discharge depth, rate, working environment temperature, energy cost, power cost, and temperature cost of the energy storage battery, wherein the energy cost is related to the charge and discharge quantity of the energy storage battery, the power cost is related to the charge and discharge power of the energy storage battery, and the temperature cost is related to the temperature of the energy storage battery itself;

[0068] Specifically, the dynamic adjustment of the state of charge interval includes: when the energy storage battery is at a peak load, increasing the upper limit of the first state of charge interval and encouraging the energy storage battery to discharge; when the market price of the energy storage battery is high, narrowing the range of the first state of charge interval to reduce excessive discharge; when the energy storage battery is at a low load, lowering the lower limit of the third state of charge interval and encouraging the energy storage battery to charge.

[0069] Specifically, the dynamic adjustment of the charge and discharge amount includes: when the state of charge is high and the predicted market price is low, the bid price is dynamically reduced in real time to increase the discharge amount of the energy storage battery; when the state of charge is low and the predicted market price is high, the bid price is dynamically increased in real time to increase the charge amount of the energy storage battery.

[0070] It should be noted that the above step S200 dynamically adjusts the target range of the state of charge according to the state of the energy storage battery, so that the energy storage system can better adapt to market changes, and the established electrochemical energy storage cost model takes into account multiple factors such as the discharge depth, rate, and working environment temperature of the energy storage battery, thereby improving the flexibility of the system, enabling the system to make optimal decisions based on real-time data and predictive information, and improving the intelligence level of the system.

[0071] In an optional embodiment, the first optimization mechanism may employ a mixed integer linear programming method;

[0072] In another optional embodiment, the first optimization mechanism may adopt a dynamic programming method;

[0073] It should be noted that both the mixed integer linear programming method and the dynamic programming method can effectively solve the energy storage battery optimization configuration problem with state of charge constraints, wherein the mixed integer linear programming method is applicable to problems requiring discrete decisions, while the dynamic programming method is applicable to continuous decision problems with time series characteristics. This embodiment uses the dynamic programming method to optimize the configuration of energy storage batteries.

[0074] In the embodiment of the present application, the above step S300 includes the following sub-steps C1-C3;

[0075] In C1: Set the optimization goal of maximizing market benefits as max x,y =f(x,y), where x is the decision variable of electric energy trading, y is the decision variable of auxiliary services, and f(x,y) is the market benefit function. Set constraints in the decision variables of electric energy trading and auxiliary services: g(x,y)≤0;

[0076] In C2: When the energy storage battery is in the first state of charge interval, it means that the battery power is sufficient. At this time, the system limits the discharge amount of the energy storage battery. The expression is:

[0077] In C3: When the energy storage battery is in the third state of charge interval, it indicates that the battery power is insufficient. At this time, the system limits the charging amount of the energy storage battery. The expression is:

[0078] Among them, SOC represents the current state of the energy storage battery. high and SOC low represent the thresholds of the first state of charge interval and the third state of charge interval respectively, and Indicates the upper limit of the discharge and charge amount related to the state of charge.

[0079] It should be noted that the above step S300 provides optimized configuration and services for the energy storage battery, making the operation of the energy storage battery more efficient. By associating the charging and discharging strategy with the state of charge interval, the charging and discharging behavior is adjusted according to the state of charge interval, which helps to extend the service life of the energy storage battery.

[0080] In the embodiment of the present application, the above step S400 includes the following sub-steps D1-D2;

[0081] In D1: the compensation process includes charging compensation. When the state of charge is lower than the lower limit of the third state of charge interval, the energy storage battery is charged through market transactions or dispatch instructions;

[0082] In D2: the compensation process includes discharge compensation. When the state of charge is higher than the upper limit of the first state of charge range, the energy storage battery is discharged through market transactions or dispatch instructions;

[0083] It should be noted that the above step S400 encourages the energy storage battery to recover to the optimal state of charge range by introducing a resource allocation mechanism, which helps to maintain the stability of the system. At the same time, through the compensation process, the state of charge of the energy storage battery can be adjusted in time to avoid it deviating from the optimal range, thereby improving the reliability of the system.

[0084] The above is a schematic scheme of a battery energy storage system energy management method of this embodiment. It should be noted that the technical scheme of the battery energy storage system energy management system and the technical scheme of the battery energy storage system energy management method described above belong to the same concept, and the details of the technical scheme of the battery energy storage system energy management system not described in detail in this embodiment can be referred to the description of the technical scheme of the battery energy storage system energy management method described above.

[0085] This embodiment also provides a battery energy storage system energy management system, including a state interval division module, a dynamic adjustment module, a constraint management module and an incentive compensation module;

[0086] Specifically, the state interval division module is used to divide the state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model;

[0087] Specifically, the dynamic adjustment module is used to dynamically adjust the state of charge interval and the charge and discharge amount through the real-time first state data;

[0088] Specifically, the constraint management module is used to establish a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery;

[0089] Specifically, the incentive compensation module is used to introduce a resource allocation mechanism into the first optimization mechanism to compensate the energy storage battery that deviates from the state of charge range, and encourage it to return to the optimal state range.

[0090] The above-mentioned unit modules may be embedded in or independent of the processor in the computer device in the form of hardware, or may be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0091] This embodiment also provides a computing device, which includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a battery energy storage system energy management method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0092] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method proposed in the above embodiment is implemented.

[0093] The storage medium proposed in this embodiment and the method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0094] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0095] Example 2

[0096] Based on the previous embodiment, this embodiment provides an application example of a battery energy storage system energy management method and system, in order to verify and illustrate the technical effects adopted in this method.

[0097] In this embodiment, the state of charge of the battery is divided into three intervals: high, medium and low according to the technical characteristics of the energy storage battery, such as the battery performance curve, dynamic response capability, temperature sensitivity, etc., and the cost model, including the initial investment cost, operation and maintenance cost, energy loss cost and opportunity cost. Among them, the high state of charge interval: [0.6, 0.9], encourages discharge and a small amount of charging; the medium state of charge interval: [0.4, 0.6], flexible charging and discharging according to market demand and system status; the low state of charge interval: [0.1, 0.4], encourages charging and a small amount of discharging.

[0098] Set up a monitoring and acquisition mechanism for external parameters such as market supply and demand, electricity price fluctuations, etc., and monitor the current state of the energy storage battery in real time, including state of charge, power output, load demand, etc., as well as the external market environment, including market supply and demand, electricity price fluctuations, etc. Dynamically adjust the state of charge target range based on the monitored data. Increase the upper limit of the high state of charge range to 1.0 during peak load to encourage battery discharge; reduce the range of the high state of charge range to [0.75,1] when the market price is high to reduce excessive discharge. When the state of charge is high and the predicted market price is low, dynamically reduce the bid price in real time to increase the discharge of the energy storage battery; when the state of charge is low and the predicted market price is high, dynamically increase the bid price in real time to increase the charge of the energy storage battery.

[0099] A first optimization mechanism including state of charge constraints is established to optimize the configuration of energy storage batteries; a resource allocation mechanism is introduced into the first optimization mechanism to compensate energy storage batteries that deviate from the state of charge interval and encourage them to return to the optimal state interval;

[0100] This embodiment carried out field experiments, and the experimental results showed that: the average service life of the energy storage battery was extended by about 20%, thanks to the effective implementation of the state of charge constraint and incentive compensation mechanism; the economic benefits of the system were increased by about 15%, which was mainly due to the dynamic adjustment of the state of charge target range and the optimization of the bidding price strategy; the stability and reliability of the system were significantly improved, and no system failure or power outage caused by improper charging and discharging of the energy storage battery occurred.

[0101] Therefore, it can be seen from the above that the present invention enables the energy storage battery to better adapt to market changes and improve the economic benefits and flexibility of the system by dynamically adjusting the state of charge range and the bidding price; by establishing a state of charge constraint and incentive compensation mechanism, the excessive charging and discharging behavior of the energy storage battery is reduced, the loss and aging rate of the battery are reduced, and the service life of the battery is extended; by optimizing the charging and discharging strategy of the energy storage battery and improving its optimal configuration and service capabilities in different markets, the stability and reliability of the system are enhanced.

[0102] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0103] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0104] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0105] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0106] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0107] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0108] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A battery energy storage system energy management method, characterized in that: include: Divide the state of charge range according to the technical characteristics of the energy storage battery and the energy storage cost model; Dynamically adjust the state of charge interval and the charge and discharge amount according to the real-time first state data; Establishing a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery; A resource allocation mechanism is introduced into the first optimization mechanism to compensate the energy storage batteries that deviate from the state of charge range, and encourage them to return to the optimal state range.

2. The battery energy storage system energy management method according to claim 1, characterized in that: The state of charge intervals divided according to the technical characteristics of the energy storage battery and the energy storage cost model include: According to the technical characteristics of the energy storage battery and the energy storage cost model, the state of charge interval is divided into a first state of charge interval, a second state of charge interval and a third state of charge interval, and each state of charge interval corresponds to a different charging and discharging strategy.

3. The battery energy storage system energy management method according to claim 2, characterized in that: The dynamically adjusting the state of charge interval by using the real-time first state data includes: When the energy storage battery is at a peak load, the upper limit of the first state of charge interval is increased, and the energy storage battery is encouraged to discharge; when the market price of the energy storage battery is high, the range of the first state of charge interval is narrowed to reduce over-discharge; when the energy storage battery is at a low load, the lower limit of the third state of charge interval is lowered, and the energy storage battery is encouraged to charge.

4. The battery energy storage system energy management method according to claim 3, characterized in that: Dynamically adjusting the charge and discharge amount through real-time first state data includes: When the charge and discharge amount is dynamically adjusted through the real-time first state data, the first state data is energy cost, power cost and temperature cost, the energy cost is related to the charge and discharge amount of the energy storage battery, the power cost is related to the charge and discharge power of the energy storage battery, and the temperature cost is related to the temperature of the energy storage battery itself; When the state of charge is high and the predicted market price is low, the bid price is dynamically lowered in real time to increase the discharge capacity of the energy storage battery; when the state of charge is low and the predicted market price is high, the bid price is dynamically increased in real time to increase the charge capacity of the energy storage battery.

5. The battery energy storage system energy management method according to claim 4, characterized in that: The establishing of a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery includes: When the energy storage battery is in the first state of charge interval, it indicates that the battery power is sufficient. At this time, the system limits the discharge amount of the energy storage battery, and the expression is: When the energy storage battery is in the third state of charge interval, it indicates that the battery power is insufficient. At this time, the system limits the charging amount of the energy storage battery, and the expression is: Among them, SOC represents the current state of the energy storage battery. high and SOC low represent the thresholds of the first state of charge interval and the third state of charge interval respectively, and Indicates the upper limit of the discharge and charge amount related to the state of charge.

6. The battery energy storage system energy management method according to claim 5, characterized in that: The introducing of a resource allocation mechanism to compensate the energy storage battery deviating from the state of charge range includes: The compensation process includes charging compensation and discharging compensation; When the state of charge is lower than the lower limit of the third state of charge range, the energy storage battery is charged through market transactions or scheduling instructions; when the state of charge is higher than the upper limit of the first state of charge range, the energy storage battery is discharged through market transactions or scheduling instructions.

7. The battery energy storage system energy management method according to claim 2, characterized in that: Each state of charge interval corresponds to a different charging and discharging strategy including: When the state of charge of the energy storage battery is in the first state of charge interval, the charge and discharge strategy is to discharge and charge in small amounts to maintain the state of charge of the energy storage battery within a first threshold range; When the state of charge of the energy storage battery is in the second state of charge range, the charge and discharge strategy is to flexibly adjust the charge and discharge according to market demand and system status; When the state of charge of the energy storage battery is in the third state of charge interval, the charge and discharge strategy is charging and discharging in small amounts to maintain the state of charge of the energy storage battery within the first threshold range.

8. A system using the battery energy storage system energy management method according to any one of claims 1 to 7, characterized in that: include: A state interval division module is used to divide the state of charge interval according to the technical characteristics of the energy storage battery and the energy storage cost model; A dynamic adjustment module, used for dynamically adjusting the state of charge interval and the charge and discharge amount according to the real-time first state data; A constraint management module, used to establish a first optimization mechanism including a state of charge constraint to optimize the configuration of the energy storage battery; The incentive compensation module is used to introduce a resource allocation mechanism into the first optimization mechanism to compensate the energy storage battery that deviates from the charge state range, and encourage it to return to the optimal state range.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the battery energy storage system energy management method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the battery energy storage system energy management method according to any one of claims 1 to 7.

Images