Energy storage converter collaborative optimization control method and system and energy storage converter

Abstract

The invention discloses a collaborative optimization control method and system for an energy storage converter and the energy storage converter, and relates to the field of energy storage optimization, and the method comprises the steps: receiving a total output power instruction of an electric energy management system through the energy storage converter; constructing an optimization problem based on the total output power instruction by taking the minimum battery charge state difference value of a battery module in the battery system as a target; and solving the optimization problem, determining the output current of each battery module in the battery system, and performing optimization control on the battery system according to the output current of each battery module. The problem of an unbalanced state in the battery system is improved, and the health level and the available capacity of the battery system are improved.

Description

Technical Field

[0001] The present application relates to the field of energy storage optimization, and in particular to a collaborative optimization control method and system for an energy storage converter and an energy storage converter. Background Art

[0002] With the access of a large number of renewable energy sources represented by wind power and photovoltaic power to the power grid, these renewable energy sources are highly intermittent and highly volatile, which brings great challenges and impacts to the stable operation of the power grid. How to effectively balance the power fluctuations on the load side and the power generation side has become an urgent problem to be solved. Battery energy storage systems play an important role in the actual application scenarios of peak shaving and valley filling of power systems due to their high energy density, flexible layout, good controllability and many other advantages.

[0003] Since the battery outputs a DC voltage, it cannot be directly connected to the AC power grid which has strict requirements on frequency and phase. Therefore, the working architecture of the battery energy storage system is mainly that the battery is connected to the power grid after the inverter. At the same time, the battery energy storage system outputs active power to the power grid under the power command of the Energy Management System (EMS). The inverter controls the output current on the battery side according to the power command of the EMS. Since the current control mode is mostly unidirectional passive control, as the working time increases, the differences in indicators such as charge state and temperature of different battery modules on the battery side will further expand, thereby causing a "short board effect", which greatly increases safety hazards. Summary of the invention

[0004] The purpose of this application is to provide a collaborative optimization control method and system for an energy storage inverter, and an energy storage inverter, which can improve the problem of internal imbalance of the battery system and enhance the health level and available capacity of the battery system.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for collaborative optimization control of an energy storage converter, comprising:

[0007] receiving a total output power instruction from an electric energy management system through an energy storage converter;

[0008] Based on the total output power command, an optimization problem is constructed with the goal of minimizing the difference in battery state of charge of battery modules in the battery system;

[0009] The optimization problem is solved to determine the output current of each battery module in the battery system, and the battery system is optimized and controlled according to the output current of each battery module.

[0010] Optionally, the energy storage converter collaborative optimization control method further includes: determining in real time whether there are battery modules in the battery system that cannot meet the set constraints; if so, reconstructing the battery modules in the battery system and rebuilding the optimization problem.

[0011] Optionally, the battery modules in the battery system are reconstructed, specifically including: removing the battery modules in the battery system that cannot meet the set constraints, so that all battery modules connected to the energy storage inverter and in working state meet the set constraints.

[0012] Optionally, the optimization problem is:

[0013]

[0014] 0≤I i ≤I max , i∈N;

[0015]

[0016] Where N is the number of battery modules in the battery system, SOC i is the battery charge state after the i-th battery module has worked for Δt time, P i is the active power output by the ith battery module, P total is the total output power of the battery system, determined based on the total output power instruction, I i is the output current of the ith battery module, I max is the upper limit of the current of the battery module, SOC i0 is the initial battery charge state of the ith battery module, Q is the total capacity of the battery module, and Δt is the working time of the battery module.

[0017] Optionally, the set constraints include upper and lower limit constraints of battery state of charge, upper and lower limit constraints of output current, and upper and lower limit constraints of output voltage.

[0018] Optionally, the battery system is optimized and controlled according to the output current of each battery module, specifically including: taking the output current of each battery module as a reference value, and stabilizing the output current and output power of each battery module at the reference value through a control link in the battery system.

[0019] In a second aspect, the present application provides a collaborative optimization control system for an energy storage converter, comprising: an electric energy management system, an energy storage converter and a battery system; the battery system comprises a plurality of battery modules;

[0020] The electric energy management system is used to send a total output power instruction to the energy storage converter;

[0021] The energy storage inverter is used to construct an optimization problem based on the total output power instruction, with the goal of minimizing the difference in battery state of charge of each battery module in the battery system, and solve the optimization problem to determine the output current of each battery module in the battery system, so as to optimize the control of the battery system.

[0022] Optionally, the energy storage converter is also used to determine in real time whether there are battery modules in the battery system that cannot meet the set constraints. If so, the battery modules in the battery system are reconstructed and the optimization problem is reconstructed.

[0023] In a third aspect, the present application provides an energy storage converter, comprising:

[0024] An instruction receiving module, used for receiving a total output power instruction of the electric energy management system;

[0025] A problem construction module, for constructing an optimization problem based on the total output power instruction with the goal of minimizing the difference in battery state of charge of battery modules in the battery system;

[0026] A problem solving module, used to solve the optimization problem and determine the output current of each battery module in the battery system;

[0027] The control module is used to optimize and control the battery system according to the output current of each battery module.

[0028] Optionally, the energy storage converter further includes:

[0029] The reconstruction module is used to determine in real time whether there are battery modules in the battery system that cannot meet the set constraints. If so, the battery modules in the battery system are reconstructed and the optimization problem is rebuilt.

[0030] Optionally, the optimization problem is:

[0031]

[0032] 0≤I i ≤I max , i∈N;

[0033]

[0034] Where N is the number of battery modules in the battery system, SOC i is the battery charge state after the i-th battery module has worked for Δt time, P i is the active power output by the ith battery module, P total is the total output power of the battery system, determined based on the total output power instruction, I i is the output current of the ith battery module, Imax is the upper limit of the current of the battery module, SOC i0 is the initial battery charge state of the ith battery module, Q is the total capacity of the battery module, and Δt is the working time of the battery module.

[0035] Optionally, the reconstruction module includes:

[0036] An interrupt signal receiving submodule, used to receive an interrupt signal sent by the battery system; the interrupt signal indicates that there is a battery module in the battery system that cannot meet the set constraints;

[0037] The reconstruction instruction issuing submodule is used to issue a reconstruction instruction to the battery system according to the interrupt signal, so that the battery system reconstructs the battery module according to the reconstruction instruction and reconstructs the optimization problem through the problem construction module.

[0038] Optionally, the reconstruction instruction is: removing the battery modules in the battery system that cannot meet the set constraints, so that all battery modules connected to the energy storage inverter and in working state meet the set constraints.

[0039] According to the specific embodiments provided in this application, this application has the following technical effects:

[0040] The present application provides a collaborative optimization control method, system and energy storage inverter for an energy storage inverter. Through information transmission between the battery system and the energy storage inverter, the output current of each battery module in the battery system is adjusted in real time. Under the premise of satisfying the total output power instruction of the power management system, the problem of internal imbalance of the battery system is effectively improved, and the health level and available capacity of the battery system are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic diagram of a process flow of a collaborative optimization control method for an energy storage converter provided in one embodiment of the present application;

[0043] Figure 2 Another schematic diagram of a flow chart of a collaborative optimization control method for an energy storage converter provided in one embodiment of the present application;

[0044] Figure 3 This is a schematic diagram of the transmission process of a power instruction in an embodiment of the present application;

[0045] Figure 4 A schematic diagram of the transmission process of a battery system reconstruction instruction in one embodiment of the present application;

[0046] Figure 5 A schematic diagram of the functional modules of an energy storage converter provided in one embodiment of the present application.

[0047] Reference numerals: 301 - power management system, 302 - energy storage converter, 303 - battery system, 304 - battery management system, 305 - transformer, 306 - power grid. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] The current grid-connected control of battery systems belongs to the passive transmission of power by batteries. Physical quantities such as the voltage and charge state of each battery module in the battery system cannot be transmitted to the inverter to achieve topological adjustment within the battery system. Power can only be output at a fixed current, resulting in increasing differences within the battery modules and a significantly enhanced "short board effect", which seriously affects the safety and operating performance of the battery system.

[0050] The present application realizes information transmission between the battery side and the inverter, so that the battery system can accept the reconstruction instructions from the inverter to realize the optimization and adjustment of the topology structure inside the battery system, which can effectively avoid the "short board effect". At the same time, the inverter can change the power distribution of different battery modules according to the topology structure on the battery system side, and realize the power optimization distribution of each battery module on the basis of meeting the total output power instruction of the EMS.

[0051] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0052] In an exemplary embodiment, Figures 1 to 4 As shown, a collaborative optimization control method for an energy storage converter is provided, comprising the following steps 101 to 104.

[0053] Step 101, receiving the total output power instruction of the power management system 301 through the energy storage converter 302. The energy storage converter 302 is respectively connected to the power management system 301 and the battery module in the battery system 303. Furthermore, the energy storage converter 302 is also connected to the power grid 306 through the transformer 305, so as to supply power to the power grid 306 through the battery system 303.

[0054] Step 102 , based on the total output power instruction, an optimization problem is constructed with the goal of minimizing the difference in battery state of charge of the battery modules in the battery system 303 .

[0055] The control of the energy storage converter 302 is based on PQ decoupling control, that is, power is controlled by decoupling active power and reactive power. The reference values ​​of active power and reactive power are as follows:

[0056] P ref =U P I d_ref ;

[0057] Q ref =U P I q_ref ;

[0058] Among them, P ref is the reference value of active power, Q ref is the reference value of reactive power, U P is the line voltage at the point of common coupling (PCC), I d_ref is the active reference current, I q_ref is the reactive reference current.

[0059] At the same time, the active power P output by the battery system 303 through the energy storage converter 302 can be expressed as:

[0060] P=u d ·i d +u q ·i q ;

[0061] Among them, u d is the direct axis component of the three-phase voltage after Parker transformation, u q is the quadrature axis component of the three-phase voltage after Parker transformation, i d is the direct axis component of the three-phase current after Parker transformation, i q It is the quadrature-axis component obtained after the three-phase current undergoes Park transformation.

[0062] By adding u q Set to 0, the above formula can be simplified to:

[0063] P=ud ·i d .

[0064] Thus, a mathematical relationship between the battery output power and the energy storage converter 302 output power is established.

[0065] In an exemplary embodiment, the sum of the squares of the differences in SOC of each battery module is used as the objective function, and the output power and output current are used as constraints to construct an optimization problem:

[0066]

[0067] 0≤I i ≤I max , i∈N;

[0068]

[0069] Where N is the number of battery modules in the battery system, SOC i is the battery charge state after the i-th battery module has worked for Δt time, P i is the active power output by the ith battery module, P total is the total output power of the battery system, determined based on the total output power instruction, I i is the output current of the ith battery module, I max is the upper limit of the current of the battery module, SOC i0 is the initial battery charge state of the ith battery module, Q is the total capacity of the battery module, and Δt is the working time of the battery module.

[0070] Step 103 , solving the optimization problem, determining the output current of each battery module in the battery system 303 , and optimizing and controlling the battery system 303 according to the output current of each battery module.

[0071] In an exemplary embodiment, the output current of each battery module is used as a reference value, and the output current and output power of each battery module are stabilized at the reference value through the control link in the battery system 303.

[0072] The relationship between the active power, output current and output voltage of the battery module is: i =V output_i I i ; Among them, V output_i is the output voltage of the i-th battery module.

[0073] In the overall architecture, the energy storage converter 302 receives the total output power from the EMS and transmits power instructions to different battery modules on the digital energy storage side. An optimization problem is constructed with minimizing the difference in the state of charge (SOC) of the battery on the energy storage side as the objective function. The output power of different battery modules is determined by the solution of the optimization problem, thereby effectively improving the imbalance between battery modules.

[0074] Step 104 , determining in real time whether there are battery modules in the battery system 303 that cannot meet the set constraints, if so, reconstructing the battery modules in the battery system 303 and rebuilding the optimization problem.

[0075] In an exemplary embodiment, the set constraints include upper and lower limit constraints of battery state of charge, upper and lower limit constraints of output current, and upper and lower limit constraints of output voltage.

[0076] In an exemplary embodiment, the process of reconstructing the battery modules in the battery system 303 includes: removing the battery modules in the battery system 303 that cannot meet the set constraints, so that all battery modules connected to the energy storage inverter 302 and in working state meet the set constraints.

[0077] In order to better understand the technical solution of the present application, the communication process between the energy storage converter 302 and the battery system 303 is introduced below.

[0078] like Figure 3 As shown, the process of transmitting power instructions to the battery module through the energy storage inverter 302 is as follows: ① The power management system 301 issues a power instruction to the energy storage inverter 302; ② The energy storage inverter 302 allocates power between the battery modules by constructing an optimization problem based on the total output power instruction of the power management system 301 and the number of available battery modules in the battery system 303, the voltage size and charge state of each battery module, etc., determines the output current of each battery module, and transmits the output current as a control signal to the battery system 303; ③ In the battery system 303, the battery management system 304 controls each battery module to transmit power to the energy storage inverter 302 according to the control signal, and then supplies power to the power grid 306 through the transformer 305.

[0079] like Figure 4As shown, the process of the battery system 303 transmitting instructions to the energy storage inverter 302 is as follows: ① When there are battery modules in the battery system 303 that cannot currently meet the corresponding constraints, such as upper and lower limit constraints such as SOC, current, and voltage, each battery module in the battery system 303 can no longer continue to work with the current power distribution status, and then sends an interrupt signal to the energy storage inverter 302; ② The energy storage inverter 302 receives the interrupt signal and issues a reconstruction instruction to the battery system 303; ③ The battery system 303 reconstructs the internal topology according to the reconstruction instruction until the constraints are met.

[0080] After the battery system 303 receives the reconstruction instruction from the energy storage converter 302, it performs internal topology reconstruction and sorting, removes the battery modules that cannot meet the constraints at present, and ensures that all battery modules connected to the energy storage converter 302 and in working state meet various constraints. Since the topological structure and working module combination of the battery system 303 have changed at this time, the original power allocation instruction of the energy storage converter 302 is not compatible with the current battery module, so the energy storage converter 302 needs to reconstruct the power allocation optimization problem according to the changed battery system 303 topology and battery module, and update the output power and output current of each battery module.

[0081] The embodiment of the present application also provides an energy storage converter 302 applied to the above energy storage converter collaborative optimization control method, wherein the energy storage converter 302 is connected to the battery modules in the power management system 301 and the battery system 303, respectively. Figure 5 As shown, the energy storage converter 302 includes: an instruction receiving module 501 , a problem building module 502 , a problem solving module 503 , a control module 504 and a reconstruction module 505 .

[0082] The instruction receiving module 501 is used to receive the total output power instruction of the power management system 301 .

[0083] The problem construction module 502 is used to construct an optimization problem based on the total output power instruction with the goal of minimizing the battery state of charge difference value of the battery modules in the battery system 303.

[0084] The problem solving module 503 is used to solve the optimization problem and determine the output current of each battery module in the battery system 303 .

[0085] The control module 504 is used to optimize and control the battery system 303 according to the output current of each battery module.

[0086] The reconstruction module 505 is used to determine in real time whether there are battery modules in the battery system 303 that cannot meet the set constraints. If so, the battery modules in the battery system 303 are reconstructed and the optimization problem is reconstructed.

[0087] In an exemplary embodiment, the reconstruction module 505 includes: an interrupt signal receiving submodule and a reconstruction instruction issuing submodule.

[0088] The interrupt signal receiving submodule is used to receive an interrupt signal sent by the battery system 303. The interrupt signal indicates that there is a battery module in the battery system 303 that cannot meet the set constraints.

[0089] The reconstruction instruction issuing submodule is used to issue a reconstruction instruction to the battery system 303 according to the interrupt signal, so that the battery system 303 reconstructs the battery module according to the reconstruction instruction and reconstructs the optimization problem through the problem construction module.

[0090] The reconfiguration instruction is: remove the battery modules in the battery system 303 that cannot meet the set constraints, so that all the battery modules connected to the energy storage converter 302 and in working state meet the set constraints.

[0091] Based on the same inventive concept, the embodiment of the present application also provides an energy storage converter collaborative optimization control system for implementing the energy storage converter collaborative optimization control method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more energy storage converter collaborative optimization control system embodiments provided below can refer to the limitations of the energy storage converter collaborative optimization control method above, and will not be repeated here.

[0092] In an exemplary embodiment, a coordinated optimization control system for energy storage converters is provided, comprising: an electric energy management system 301, an energy storage converter 302, and a battery system 303. The battery system 303 comprises a plurality of battery modules.

[0093] The energy storage converter 302 is connected to the power management system 301 and each battery module in the battery system 303 respectively.

[0094] The power management system 301 is used to send a total output power instruction to the energy storage converter 302 .

[0095] The energy storage inverter 302 is used to construct an optimization problem based on the total output power instruction, with the goal of minimizing the difference in battery state of charge of each battery module in the battery system 303, and solve the optimization problem to determine the output current of each battery module in the battery system 303, so as to optimize and control the battery system 303, and determine in real time whether there is a battery module in the battery system 303 that cannot meet the set constraints. If so, the battery modules in the battery system 303 are reconstructed and the optimization problem is reconstructed.

[0096] Different from the traditional fixed series-parallel battery energy storage solution, this application uses a dynamically reconfigurable battery system topology, which can achieve the improvement of the overall performance of the battery system and the effective protection of intrinsic safety by adjusting the battery system topology. At the same time, most of the current battery energy storage system architectures are still connected to the grid after the battery is connected through the energy storage inverter, that is, the battery system passively accepts instructions from the EMS and passively sends power to the grid through the energy storage inverter. In this process, since there is only energy-level control and power transmission, the imbalance of the battery modules in the battery system in terms of charge state, heat dissipation, and temperature will gradually increase during the operation of the battery system, ultimately affecting the life and performance of the battery system, and bringing potential hidden dangers to the stable operation of the battery energy storage system. Based on the dynamically reconfigurable battery topology, this application proposes a collaborative optimization control strategy between the battery system and the energy storage inverter. The output power of each battery module in the battery system is adjusted in real time through information transmission between the two. Under the premise of satisfying the EMS total output power instruction unchanged, the unbalanced state inside the battery system can be effectively improved. At the same time, when the battery module no longer meets the constraints such as output voltage and state of charge, the relevant signal is transmitted to the energy storage inverter, and the energy storage inverter issues a reconstruction signal. The battery system reconstructs and sorts the topology according to the reconstruction instruction, which effectively improves the health level and available capacity of the battery system.

[0097] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0098] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0099] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A collaborative optimization control method for an energy storage converter, characterized in that: include: receiving a total output power instruction from an electric energy management system through an energy storage converter; Based on the total output power command, an optimization problem is constructed with the goal of minimizing the difference in battery state of charge of battery modules in the battery system; The optimization problem is solved to determine the output current of each battery module in the battery system, and the battery system is optimized and controlled according to the output current of each battery module.

2. The energy storage converter collaborative optimization control method according to claim 1, characterized in that: Also includes: Determine in real time whether there are battery modules in the battery system that cannot meet the set constraints. If so, reconstruct the battery modules in the battery system and rebuild the optimization problem.

3. The energy storage converter collaborative optimization control method according to claim 2, characterized in that: Reconstruct the battery modules in the battery system, including: The battery modules in the battery system that cannot meet the set constraints are removed, so that all battery modules connected to the energy storage converter and in working state meet the set constraints.

4. The energy storage converter collaborative optimization control method according to claim 1, characterized in that: The optimization problem is: 0≤I i ≤I max ,i∈N; Where N is the number of battery modules in the battery system, SOC i is the battery charge state after the i-th battery module has worked for Δt time, P i is the active power output by the ith battery module, P total is the total output power of the battery system, determined based on the total output power instruction, I i is the output current of the ith battery module, I max is the upper limit of the current of the battery module, SOC i0 is the initial battery charge state of the ith battery module, Q is the total capacity of the battery module, and Δt is the working time of the battery module.

5. The energy storage converter collaborative optimization control method according to claim 1, characterized in that: The setting constraints include upper and lower limit constraints of battery state of charge, upper and lower limit constraints of output current, and upper and lower limit constraints of output voltage.

6. The energy storage converter collaborative optimization control method according to claim 1, characterized in that: The battery system is optimized and controlled according to the output current of each battery module, specifically including: The output current of each battery module is used as a reference value, and the output current and output power of each battery module are stabilized at the reference value through the control link in the battery system.

7. A collaborative optimization control system for an energy storage converter, characterized in that: The energy storage converter collaborative optimization control system includes: an electric energy management system, an energy storage converter and a battery system; the battery system includes a plurality of battery modules; The electric energy management system is used to send a total output power instruction to the energy storage converter; The energy storage inverter is used to construct an optimization problem based on the total output power instruction, with the goal of minimizing the difference in battery state of charge of each battery module in the battery system, and solve the optimization problem to determine the output current of each battery module in the battery system, so as to optimize the control of the battery system.

8. The energy storage converter collaborative optimization control system according to claim 7, characterized in that: The energy storage converter is also used to determine in real time whether there are battery modules in the battery system that cannot meet the set constraints. If so, the battery modules in the battery system are reconstructed and the optimization problem is rebuilt.

9. An energy storage converter, applied to the energy storage converter collaborative optimization control method according to any one of claims 1 to 6, characterized in that: The energy storage converter comprises: An instruction receiving module, used for receiving a total output power instruction of the electric energy management system; A problem construction module, for constructing an optimization problem based on the total output power instruction with the goal of minimizing the difference in battery state of charge of battery modules in the battery system; A problem solving module, used to solve the optimization problem and determine the output current of each battery module in the battery system; The control module is used to optimize and control the battery system according to the output current of each battery module.

10. The energy storage converter according to claim 9, characterized in that: The energy storage converter also includes: The reconstruction module is used to determine in real time whether there are battery modules in the battery system that cannot meet the set constraints. If so, the battery modules in the battery system are reconstructed and the optimization problem is rebuilt.

11. The energy storage converter according to claim 10, characterized in that: The reconstruction module includes: An interrupt signal receiving submodule, used to receive an interrupt signal sent by the battery system; the interrupt signal indicates that there is a battery module in the battery system that cannot meet the set constraints; The reconstruction instruction issuing submodule is used to issue a reconstruction instruction to the battery system according to the interrupt signal, so that the battery system reconstructs the battery module according to the reconstruction instruction and reconstructs the optimization problem through the problem construction module.

12. The energy storage converter according to claim 10, characterized in that: The reconstruction instruction is: remove the battery modules in the battery system that cannot meet the set constraints, so that all battery modules connected to the energy storage converter and in working state meet the set constraints.

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