WO2024060053A1 - 储能系统的控制方法和储能系统 - Google Patents

储能系统的控制方法和储能系统 Download PDF

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WO2024060053A1
WO2024060053A1 PCT/CN2022/120139 CN2022120139W WO2024060053A1 WO 2024060053 A1 WO2024060053 A1 WO 2024060053A1 CN 2022120139 W CN2022120139 W CN 2022120139W WO 2024060053 A1 WO2024060053 A1 WO 2024060053A1
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energy storage
storage sub
module
soc
parameter
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PCT/CN2022/120139
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English (en)
French (fr)
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陈梦佳
余东旭
卢艳华
缪鸿杰
余勇铮
梁李柳元
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宁德时代新能源科技股份有限公司
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Priority to PCT/CN2022/120139 priority Critical patent/WO2024060053A1/zh
Publication of WO2024060053A1 publication Critical patent/WO2024060053A1/zh

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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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries

Definitions

  • the present application relates to the field of energy storage, and in particular, to a control method and energy storage system for an energy storage system.
  • the energy storage system in the flexible DC transmission system mainly realizes energy storage by connecting energy storage sub-modules in series to form ultra-high voltage.
  • the switching strategy of the energy storage sub-module will affect the utilization rate of the energy storage system.
  • This application provides a control method and energy storage system for an energy storage system, which can control the working status of the energy storage sub-module in the energy storage system based on multiple state parameters, thereby improving the utilization rate and reliability of the system.
  • a control method for an energy storage system comprising N energy storage sub-modules, N being a positive integer greater than 1, the method comprising: obtaining state parameters of each of the N energy storage sub-modules, the state parameters comprising: remaining battery power (State of Charge, SOC), and at least one of battery health (State of Health, SOH), IGBT junction temperature and battery temperature; and controlling the working state of the N energy storage sub-modules according to the state parameters of each of the energy storage sub-modules, the working state comprising an on state and a off state.
  • the SOC, as well as the SOH and IGBT junctions of each of the N energy storage sub-modules are first obtained.
  • the state of each energy storage sub-module is controlled based on at least one of the SOC of each energy storage sub-module and at least one of SOH, IGBT junction temperature and battery temperature. In this way, the state of the energy storage sub-module is controlled based on the SOC of each energy storage sub-module, as well as at least one of SOH, IGBT junction temperature and battery temperature.
  • the loss balance between each energy storage sub-module can be achieved to avoid Due to the imbalance of SOC or SOH of the energy storage sub-module, the available capacity of the energy storage system decreases.
  • the low battery temperature module can be called in time to avoid the impact of a single energy storage sub-module on the charge and discharge current of the entire energy storage system. Overall Improve the utilization rate and reliability of energy storage systems.
  • controlling the states of N energy storage sub-modules includes: obtaining the weight coefficient of each parameter in the state parameters; according to the weight coefficient of each energy storage sub-module.
  • the state parameter and the weight coefficient of each parameter in the state parameter control the state of the N energy storage sub-modules.
  • SOC, SOH, IGBT junction temperature and battery temperature are all very important for improving the stability and reliability of the system, but their importance is different.
  • the N energy storage sub-modules are controlled according to the state parameter of each energy storage sub-module and the weight coefficient of each parameter in the state parameter.
  • the state includes: determining the quantized value of each parameter in the state parameter according to each parameter in the state parameter; controlling the quantized value and weight coefficient of each parameter in the state parameter according to the state parameter. The status of N energy storage sub-modules.
  • the state parameters and corresponding weight coefficients are combined to control the state of the energy storage sub-module, which can further improve the utilization rate and reliability of the system; specific quantitative values are used to measure the state of each energy storage sub-module. parameters, which is conducive to precise control of the status of each energy storage sub-module.
  • determining the quantified value of each parameter in the state parameters includes: determining the value of each energy storage sub-module when the energy storage system is charging.
  • the SOH, IGBT junction temperature and battery temperature of the module are the lowest.
  • Score SOH(x) , Score temp-IGBT(x) and Score temp-bat(x) are the SOH, IGBT junction temperature and battery temperature of the Xth energy storage sub-module. Quantitative value of temperature.
  • Score SOH(x) Score temp-IGBT(x) and Score temp-bat(x) are used to measure the state parameters SOH, IGBT junction temperature and the lowest temperature of the battery of the energy storage sub-module, and then control The status of each energy storage sub-module is helpful to improve the accuracy of inputting and cutting out energy storage sub-modules of the energy storage system.
  • controlling the states of N energy storage sub-modules according to the quantized value and weight coefficient of each parameter in the state parameters includes: according to each of the The quantified value and weight coefficient of each parameter in the state parameter of the energy storage sub-module is determined to determine the comprehensive quantified value P(x) of each energy storage sub-module; according to the quantified value of each energy storage sub-module P(x), select the n energy storage sub-modules with the largest P(x) among the N energy storage sub-modules to be in the input state, and the remaining energy storage among the N energy storage sub-modules The submodule is in the cut-out state.
  • the SOC, SOH, IGBT junction temperature and the lowest battery temperature of each energy storage sub-module are collected, and these state parameters are normalized, and the comprehensive quantified value P(x ) Perform balanced cut-in and cut-out sequencing of energy storage sub-modules.
  • This control state method reduces the time complexity of the control algorithm, improves the response efficiency of the energy storage system, and is conducive to long-term stable operation of the system.
  • the P(x) is:
  • Weight SOC , Weight health , and Weight temp-bat are the weight coefficients of the SOC, SOH and IGBT junction temperature of the energy storage sub-module and the lowest temperature of the battery.
  • the junction temperature of SOC, SOH, IGBT is normalized to the lowest temperature of the battery, and the comprehensive quantified value P(x) is used to perform balanced cut-in and cut-out ordering of the energy storage sub-modules, which reduces the time complexity of the control algorithm. , which improves the response efficiency of the energy storage system and is conducive to the long-term stable operation of the system.
  • the sum of the weight coefficients of the state parameters of each energy storage sub-module is 1, and the weight coefficient of the SOC is greater than or equal to 0.7.
  • the weight coefficient can be used to reflect the importance of each state parameter to the energy storage system; further, the sum of the weight coefficients corresponding to all state parameters of each energy storage sub-module is 1, where the weight coefficient corresponding to the SOC Greater than or equal to 0.7, in this way, when controlling the state of the energy storage sub-module, the SOC, which plays an important role in the stable control of the energy storage system, can be considered, thus ensuring the long-term stable and reliable operation of the system to the greatest extent.
  • the method further includes: determining the coefficient of variation of each parameter of each energy storage sub-module based on each parameter of each energy storage sub-module; the coefficient of variation, and adjust the weight coefficient.
  • the state parameters of the energy storage sub-modules are combined with the weight coefficients, and the order of comprehensive quantified values is used to determine the state of the energy storage sub-modules, which can reduce the time complexity of the control algorithm and improve the system response efficiency.
  • dynamically adjusting the weight coefficient and recalculating the comprehensive quantitative value is beneficial to the long-term stable operation of the energy storage system.
  • the adjustment of the weight coefficient includes: determining whether the variation coefficient of each parameter of each energy storage sub-module is greater than the variation coefficient threshold of the system; when the variation coefficient If it is greater than the variation coefficient threshold, adjust the weight coefficient of the state parameter.
  • the weight coefficient corresponding to the state parameter is changed, otherwise the weight coefficient corresponding to the state parameter remains unchanged.
  • the coefficient of variation changes significantly, then change the weight coefficient of the corresponding state parameter. This will not only facilitate the long-term stable operation of the system, but also improve the efficiency of the energy storage system.
  • controlling the working states of N energy storage sub-modules according to the state parameters of each energy storage sub-module includes: IGBTs in the energy storage sub-modules.
  • the energy storage sub-module is controlled to be in a cut-out state.
  • the energy storage sub-module will have an adverse impact on the system, so it should be removed from the energy storage system in time. Cut out at work.
  • an energy storage system including: N energy storage sub-modules, where N is a positive integer greater than 1; and a controller configured to obtain each of the N energy storage sub-modules.
  • the state parameters of the energy sub-module, the state parameters include: the remaining battery power SOC and the battery health SOH, IGBT junction temperature and battery temperature at least one parameter, according to the state parameters of each energy storage sub-module, Control the working status of N energy storage sub-modules, and the working status includes an input state and a cut-out state.
  • the controller is configured to: obtain the weight coefficient of each parameter in the state parameters; according to the state parameters of each energy storage sub-module and the state parameters The weight coefficient of each parameter controls the state of the N energy storage sub-modules.
  • the controller is configured to: determine a quantified value of each parameter in the status parameters based on each parameter in the status parameters; The quantified value of a parameter and the weight coefficient control the status of N energy storage sub-modules.
  • the controller is used to: determine the comprehensive quantized value P(x) of each energy storage submodule according to the quantized value and weight coefficient of each parameter in the state parameters of each energy storage submodule; and according to the P(x) of each energy storage submodule, select the n energy storage submodules with the largest P(x) among the N energy storage submodules as the put-in state, and the remaining energy storage submodules among the N energy storage submodules as the cut-out state.
  • the P(x) is:
  • Weight SOC , Weight health , and Weight temp-bat are the weight coefficients of the SOC, SOH and IGBT junction temperature of the energy storage sub-module and the lowest temperature of the battery.
  • the sum of the weight coefficients of the state parameters of each energy storage sub-module is 1, and the weight coefficient of the SOC is greater than or equal to 0.7.
  • the controller is configured to: determine each parameter of each energy storage sub-module based on each parameter of the state parameters of each energy storage sub-module.
  • the coefficient of variation ; adjust the weight coefficient according to the coefficient of variation.
  • the controller is configured to: determine whether the variation coefficient of each parameter of each energy storage sub-module is greater than a variation coefficient threshold of the energy storage system; when the variation coefficient is greater than In the case of the variation coefficient threshold, adjust the weight coefficient of the state parameter.
  • the controller is also configured to: when the IGBT junction temperature of the energy storage sub-module is greater than the IGBT junction temperature threshold of the energy storage system, control the energy storage sub-module For the cut-out state.
  • a device for controlling an energy storage system including a processor and a memory.
  • the memory is used to store a computer program.
  • the processor is used to call the computer program so that the device implements the first aspect. method in any possible implementation.
  • a readable storage medium stores a computer program.
  • the computing device When the computer program is executed by a computing device, the computing device enables the computing device to implement any possible implementation manner in the first aspect. method in.
  • FIG. 1 is a schematic diagram of the energy storage system applied in this application.
  • FIG. 2 is a schematic structural diagram of an energy storage submodule according to an embodiment of the present application.
  • FIG. 3 is a schematic structural diagram of an energy storage submodule according to another embodiment of the present application.
  • Figure 4 is a schematic flow chart of a control method for an energy storage system according to an embodiment of the present application.
  • Figure 5 is a schematic flow chart of a control method for an energy storage system according to another embodiment of the present application.
  • FIG. 6 is a schematic block diagram of an energy storage system according to an embodiment of the present application.
  • FIG. 7 is a schematic block diagram of an energy storage system control device according to an embodiment of the present application.
  • an embodiment means that a particular feature, structure or characteristic described in connection with the embodiment may be included in at least one embodiment of the application.
  • the appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.
  • connection can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, an indirect connection through an intermediate medium, or an internal connection between two components.
  • connection can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, an indirect connection through an intermediate medium, or an internal connection between two components.
  • connection can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, an indirect connection through an intermediate medium, or an internal connection between two components.
  • Flexible DC transmission is a new generation of DC transmission technology. It is structurally composed of a converter station and a DC transmission line (usually a DC cable).
  • the converter station is composed of a converter and converter transformer equipment. Composed of flow impedance equipment, etc.
  • the converter in flexible DC transmission is a voltage source converter. Its biggest feature is the use of turn-off devices and high-frequency modulation technology. .
  • Flexible DC transmission has the advantages of being able to supply power to passive networks, without commutation failure, without communication between converter stations, and with the ease of constructing a multi-terminal DC system.
  • the application of energy storage systems in flexible DC transmission systems has important research significance.
  • the application of energy storage systems in flexible DC transmission systems has the following three main functions: (1) Flexible DC transmission is an effective way to integrate new energy into the grid. By applying the energy storage system to the flexible DC transmission system, the inherent disadvantages of new energy can be effectively suppressed. The adverse effects of fluctuations on the power grid; (2) Applying energy storage systems to flexible DC transmission systems can reduce the power impact of faults on the power grid and improve the stability and security of the power system; (3) Power surplus is a threat to flexible DC transmission systems The safe operation of the power transmission system is an important issue. The application of energy storage systems to store surplus power can ensure the system's fault prevention capabilities and improve the operational reliability of the flexible DC transmission system.
  • embodiments of the present application provide an energy storage system control method and an energy storage system, which can control the working status of the energy storage sub-module in the energy storage system according to multiple states, thereby improving the utilization rate and reliability of the system. sex.
  • FIG. 1 is a schematic diagram of the energy storage system applied in this application.
  • the energy storage system 10 includes N energy storage sub-modules 11, where N is a positive integer greater than 1, and each of the N energy storage sub-modules 11 can be arranged in series.
  • FIG. 2 is a schematic structural diagram of an energy storage submodule according to one embodiment of the present application
  • FIG. 3 is a schematic structural diagram of an energy storage submodule according to another embodiment of the present application.
  • the energy storage sub-module is composed of a power module 211 and a battery module 212.
  • the battery module 212 connected to the power module is charging or Discharge state; when the power module 211 is in the cut-out state, the battery module 212 connected to the power module 211 is in a resting state.
  • FIG 4 is a schematic flow chart of a control method for an energy storage system according to an embodiment of the present application.
  • the energy storage system includes N energy storage sub-modules, where N is a positive integer greater than 1.
  • the energy storage system may be the energy storage system shown in Figure 1.
  • the method 400 includes:
  • the state parameters include: SOC, and at least one parameter among SOH, IGBT junction temperature and battery temperature;
  • S420 Control the working status of N energy storage sub-modules according to the status parameters of each energy storage sub-module.
  • the working status includes the input status and the cut-out status.
  • SOH represents the battery capacity, health, and performance status, that is, the percentage of the battery's fully charged capacity relative to its rated capacity.
  • the health of a newly shipped battery is 100%, and that of a completely scrapped battery is 0%.
  • IGBT is a composite fully controlled voltage-driven power semiconductor device composed of a bipolar junction transistor (BJT) and an insulated gate field effect transistor (Metal Oxide Semiconductor, MOS), and has both ( Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) has the advantages of high input impedance and power transistor (Giant Transistor, GTR) in terms of low conduction voltage drop.
  • the IGBT junction temperature represents the actual operating temperature of the IGBT, which has a certain impact on the stability of the energy storage system.
  • the battery temperature is the operating temperature of the battery module in the energy storage sub-module, including typical temperatures such as the lowest temperature of the battery and the highest temperature of the battery. Since the battery temperature will change during the operation of the energy storage system, you can collect the battery temperature value during the operation of the system, cache the battery temperature value in the system, and update it in real time; or in the energy storage system Set the temperature collection conditions, for example, only collect when it is lower than a certain value. In short, this application has no special requirements on the collection method of each state parameter. For convenience of explanation, it is collectively referred to as obtaining the value of the state parameter.
  • N energy storage sub-modules form an energy storage system, so the available battery capacity of the N energy storage sub-modules constitutes the available capacity of the energy storage system.
  • the SOC gap between energy storage sub-modules is too large, the system will always give priority to the energy storage sub-module with a larger SOC and shelve the energy storage sub-module with a lower SOC. Over time, the available capacity of the energy storage system will decrease. Reduce the utilization rate of the energy storage system.
  • the system always selects energy storage sub-modules with high battery health, or always selects energy storage sub-modules with low battery health, it will also cause the available capacity of the energy storage system to decrease.
  • the energy storage sub-module will affect the stability of the energy storage system; and when the battery temperature in the battery module is too low, the energy storage sub-module will The operating current of the energy submodule will become smaller. If the energy storage sub-module is not called in time, the operating current of the series-connected energy storage system will become smaller, affecting the work of the energy storage system.
  • the SOC of each of the N energy storage sub-modules, as well as the SOH, IGBT junction temperature and battery are first obtained. At least one item of temperature is used to control the state of each energy storage sub-module. In this way, the state of the energy storage sub-module is controlled based on the SOC of each energy storage sub-module, as well as at least one of SOH, IGBT junction temperature and battery temperature.
  • the loss balance between each energy storage sub-module can be achieved to avoid Due to the imbalance of SOC or SOH of the energy storage sub-module, the available capacity of the energy storage system decreases; on the other hand, the low-temperature module can be called immediately to avoid the impact of a single sub-module on the charge and discharge current of the entire energy storage system, thereby improving the overall Energy storage system utilization and reliability.
  • the weight coefficient of each parameter in the state parameter is obtained; according to the state parameter of each energy storage sub-module and the weight coefficient of each parameter in the state parameter, the N energy storage sub-modules are controlled. state.
  • the quantized value of each parameter in the state parameter is determined according to each parameter in the state parameter; the N energy storage sub-units are controlled according to the quantized value and weight coefficient of each parameter in the state parameter.
  • the status of the module is determined according to each parameter in the state parameter; the N energy storage sub-units are controlled according to the quantized value and weight coefficient of each parameter in the state parameter.
  • combining state parameters and corresponding weight coefficients to control the state of the energy storage sub-module can further improve the utilization and reliability of the system.
  • the quantized value is to convert the numerical value of the state parameter into a value that can be calculated.
  • each state parameter of the energy storage sub-module when the energy storage system is charging, energy storage submodules with lower SOC should be given priority for investment; when the energy storage system is discharging, energy storage submodules with higher SOC should be given priority. Make an investment. In this way, SOC balance among all energy storage sub-modules can be achieved in different states of the energy storage system.
  • the energy storage system calls different energy storage sub-modules in the charging state and discharging state, so that each energy storage system can be realized.
  • the SOC balance between sub-modules avoids the decrease in the available capacity of the energy storage system caused by the SOC imbalance of the energy storage sub-modules, thereby improving the utilization of the system.
  • the corresponding quantified values of SOH, IGBT junction temperature and battery temperature, Score SOH(x) , Score temp-IGBT(x) and Score temp-bat(x), may be obtained simultaneously or at least one of them may be obtained.
  • Score SOH(x) is used to measure the state parameters SOH, IGBT junction temperature and battery minimum temperature of the energy storage sub-module, and then control each The status of the energy storage sub-module is conducive to improving the accuracy of inputting and cutting out the energy storage sub-module of the energy storage system.
  • the comprehensive quantified value P(x) of each energy storage sub-module is determined based on the quantized value and weight coefficient of each parameter in the state parameter of each energy storage sub-module; according to each energy storage sub-module P(x) of the module, select the n energy storage sub-modules with the largest P(x) among the N energy storage sub-modules as the input state, and the remaining energy storage sub-modules among the N energy storage sub-modules as the cut-out state.
  • the SOC, SOH, IGBT junction temperature and minimum battery temperature of each energy storage submodule are collected and normalized, and the comprehensive quantitative value P(x) is used to perform balanced switching in and out sorting of the energy storage submodules.
  • This control state method reduces the time complexity of the control algorithm, improves the response efficiency of the energy storage system, and is conducive to the long-term stable operation of the system.
  • P(x) is:
  • Weight SOC , Weight health and Weight temp-bat are the weight coefficients of the SOC, SOH and IGBT junction temperature of the energy storage sub-module and the lowest temperature of the battery.
  • the SOC, SOH, IGBT junction temperature and the lowest temperature of the battery are normalized, and the specific comprehensive quantitative value P(x) is used to perform balanced cut-in and cut-out ordering of the energy storage sub-modules, which reduces the time complexity of the control algorithm. , which improves the response efficiency of the energy storage system and is conducive to the long-term stable operation of the system.
  • the sum of the weight coefficients of the state parameters of each energy storage sub-module is 1, and the weight coefficient of the SOC is greater than or equal to 0.7.
  • the value of the weight coefficient is used to reflect the importance of the state parameters to the energy storage system. importance of the system.
  • the sum of the weight coefficients of the state parameters of each energy storage sub-module is limited to 1, which facilitates calculation and statistics and analysis of changes in the weight coefficients of the energy storage system during the calculation process.
  • the weight coefficient can be used to reflect the importance of each state parameter to the energy storage system; further, the sum of the weight coefficients corresponding to all state parameters of each energy storage sub-module is 1, among which the weight coefficient corresponding to SOC is greater than or equal to 0.7, so that when controlling the state of the energy storage sub-module, the SOC, which plays an important factor in the stable control of the energy storage system, can be considered, which can ensure the long-term stable and reliable operation of the system to the greatest extent.
  • weight coefficient of SOC mentioned above is 0.7 is just an example.
  • the weight coefficient corresponding to SOC can also be 0.6, 0.5 and other values, as long as the weight coefficient corresponding to SOC is in the sum of the weight coefficients corresponding to all state parameters. The largest proportion is sufficient. This application has no special restrictions on the specific weight coefficient value of SOC.
  • the variation coefficient of each parameter of each energy storage sub-module is determined based on each parameter of each energy storage sub-module; the weight coefficient is adjusted based on the variation coefficient.
  • the coefficient of variation (Coefficient of Variation, CV) is when it is necessary to compare the degree of dispersion of two sets of data. If the measurement scales of the two sets of data are too different, or the data dimensions are different, the measurement scales can be eliminated. and the influence of dimension, which is the ratio of the standard deviation of the original data to the mean of the original data. CV has no dimensions, so objective comparisons can be made. CV is the absolute value that reflects the degree of data dispersion. Its data size is not only affected by the dispersion of variable values, but also by the average level of variable values.
  • Combining the state parameters of the energy storage submodule with the weight coefficient and using the ranking of the comprehensive quantized values to determine the state of the energy storage submodule can reduce the time complexity of the control algorithm and improve the system response efficiency.
  • the weight coefficient is dynamically adjusted and the comprehensive quantitative value is recalculated, which is beneficial to the long-term stable operation of the energy storage system.
  • the coefficient of variation threshold of the energy storage system can be set manually at the beginning of the program, and the coefficient of variation can be 10 or 20, which is not limited in this application.
  • a larger coefficient of variation of a certain weight coefficient indicates that the weight coefficient changes greatly during the operation of the energy storage system, which will have a greater impact on the calculation results. Therefore, for state parameters with large variation coefficients, the weight coefficient can be adjusted with an increase or decrease of 0.1. For example, for a smaller weight coefficient, you can increase it by 0.1; for a larger weight coefficient, you can decrease it by 0.1.
  • the specific adjustment range and adjustment objects are mainly based on the actual operation of the energy storage system. For example, a weight coefficient with a small value can be increased or decreased by 0.05. This application does not impose any restrictions on this.
  • the energy storage submodule when the IGBT junction temperature of the energy storage submodule is greater than the IGBT junction temperature threshold of the energy storage system, the energy storage submodule is controlled to be in a cut-out state.
  • the energy storage sub-module will have an adverse impact on the system, so it should be cut out of the energy storage system in time.
  • the safety of the energy storage system can be maintained by controlling the energy storage sub-module whose IGBT junction temperature is greater than the IGBT junction temperature threshold of the energy storage system to the cut-out state.
  • control method of the energy storage system can be set to start when the energy storage sub-module to be invested changes, or can be set to start at a fixed period. This application does not place any restrictions on the starting conditions of the control method.
  • FIG. 5 is a flow chart of a control method for an energy storage system according to yet another embodiment of the present application. Similar steps between this embodiment and the foregoing embodiments can be referred to the foregoing embodiments, and will not be described again for the sake of simplicity.
  • Step S501 start.
  • Step S502 Determine the number n of energy storage sub-modules that need to be invested.
  • Step S503 obtain SOC, SOH, IGBT junction temperature and battery temperature.
  • Step S504 Obtain the weight coefficients of each state parameter: Weight SOC , Weight health , and Weight temp-bat .
  • Step S505 determine whether Temp IGBT(x) is greater than the IGBT junction temperature threshold MAX temp-IGBT(x) .
  • Step S506 if Temp IGBT(x) is greater than MAX temp-IGBT(x) , the energy storage sub-module is in the cut-out state.
  • Step S507 if Temp IGBT(x) is not greater than MAX temp-IGBT(x) , obtain cache Temp bat(x) .
  • Step S508 Determine the SOC, SOH, IGBT junction temperature and the lowest temperature quantified value of the battery.
  • Step S509 calculating the comprehensive quantitative value P(x) of each energy storage submodule.
  • Step S510 sort according to P(x).
  • Step S511 determine that the first n energy storage submodules of P(x) are in the activated state.
  • Step S512 count the coefficients of variation of all energy storage sub-modules.
  • Step S513 determine whether the coefficient of variation is greater than the coefficient of variation of the energy storage system.
  • Step S514 if the coefficient of variation is greater than the coefficient of variation of the energy storage system, adjust the weight coefficient to keep the sum of the weight coefficients at 1 and Weight SOC > 0.7.
  • Step S515 If the coefficient of variation is not greater than the coefficient of variation of the energy storage system, determine whether the system exits.
  • Step S5166 if you exit the system, end.
  • FIG. 6 is a schematic block diagram of an energy storage system according to an embodiment of the present application.
  • the energy storage system 10 includes: N energy storage sub-modules 11, N is a positive integer greater than 1; a controller 12, used to obtain each of the N energy storage sub-modules 11
  • the state parameters of 11 include: remaining battery power SOC and battery health SOH, IGBT junction temperature and battery temperature. According to the state parameters of each energy storage sub-module, N energy storage sub-modules 11 are controlled.
  • the working state includes the input state and the cut-out state.
  • the controller 12 is used to: obtain the weight coefficient of each parameter in the state parameters; control N according to the state parameters of each energy storage sub-module and the weight coefficient of each parameter in the state parameters. The status of each energy storage sub-module.
  • the controller 12 is configured to: determine the quantized value of each parameter in the state parameters according to each parameter in the state parameters; and determine the quantized value and weight coefficient of each parameter in the state parameters according to , control the status of N energy storage sub-modules.
  • the controller 12 is configured to: determine the comprehensive quantified value P(x) of each energy storage sub-module based on the quantized value and weight coefficient of each parameter in the state parameter of each energy storage sub-module; According to the P(x) of each energy storage sub-module, select the n energy storage sub-modules with the largest P(x) among the N energy storage sub-modules as the input state, and the remaining energy storage sub-modules among the N energy storage sub-modules For the cut-out state.
  • P(x) is:
  • Weight SOC , Weight health and Weight temp-bat are the weight coefficients of the SOC, SOH and IGBT junction temperature of the energy storage sub-module and the lowest temperature of the battery.
  • the sum of the weight coefficients of the state parameters of each energy storage sub-module is 1, and the weight coefficient of the SOC is greater than or equal to 0.7.
  • the controller 12 is configured to: determine the coefficient of variation of each parameter of each energy storage submodule according to each parameter of the state parameters of each energy storage submodule; adjust according to the coefficient of variation. weight coefficient.
  • the controller 12 is used to: determine whether the variation coefficient of each parameter of each energy storage sub-module is greater than the variation coefficient threshold of the energy storage system; when the variation coefficient is greater than the variation coefficient threshold, adjust the state The weight coefficient of the parameter.
  • the controller 12 is configured to: when the IGBT junction temperature of the energy storage submodule is greater than the IGBT junction temperature threshold of the energy storage system, control the energy storage submodule to be in a cut-out state.
  • the device 70 for controlling the energy storage system includes a processor 71 and a memory 72.
  • the memory 72 is used to store computer programs, and the processor 71 is used to call the computer program, so that the device 70 can implement various aspects of the present application. Example methods.
  • An embodiment of the present application also provides a readable storage medium.
  • the readable storage medium stores a computer program, which when executed by a computing device causes the computing device to implement the methods of various embodiments of the present application.

Abstract

本申请提供一种储能系统的控制方法和储能系统。该储能系统包括N个储能子模块，N为大于1的正整数，该储能系统的控制方法包括：获取N个所述储能子模块中的每个所述储能子模块的状态参数，所述状态参数包括：电池剩余电量SOC以及电池健康度SOH、IGBT结温和电池温度中的至少一项参数；根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，所述工作状态包括投入状态和切出状态。本申请实施例提供的技术方案，能够实现根据多个状态参数控制储能系统中的储能子模块的工作状态，进而提高系统的利用率和可靠性。

Description

储能系统的控制方法和储能系统 技术领域
本申请涉及储能领域，尤其涉及一种储能系统的控制方法和储能系统。
背景技术
为加强柔性直流输电系统的有效功率调节能力，充分发挥柔性直流输电系统参与电网调节的作用，在柔性直流输电系统中应用储能系统具有重要的研究意义。
柔性直流输电系统中的储能系统主要通过储能子模块串联形成特高压的方式实现储能。储能子模块的投切策略会影响储能系统的利用率。
因此，如何提高系统的利用率，是一个亟需解决的问题。
发明内容
本申请提供了一种储能系统的控制方法和储能系统，能够实现根据多个状态参数控制储能系统中的储能子模块的工作状态，进而提高系统的利用率和可靠性。
第一方面，提供了一种储能系统的控制方法，所述储能系统包括N个储能子模块，N为大于1的正整数，所述方法包括：获取N个所述储能子模块中的每个所述储能子模块的状态参数，所述状态参数包括：电池剩余电量(State of Charge,SOC)，以及电池健康度(State of Health,SOH)、IGBT结温和电池温度中的至少一项参数；根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，所述工作状态包括投入状态和切出状态。
本申请实施例中，在储能系统中的N个储能子模块的状态未确定的情况下，先获取N个储能子模块中的每个储能子模块的SOC，以及SOH、IGBT结温和电池温度中的至少一项，再根据每个储能子模块的SOC，以及SOH、IGBT结温和电池温度中的至少一项，来控制每个储能子模块的状态。这样根据每个储能子模块的SOC，以及SOH、IGBT结温和电池温度中的至少一项来控制储能子模块的状态，一方面可以实 现每个储能子模块之间的损耗均衡，避免因储能子模块的SOC或SOH不均衡导致储能系统的可用容量下降，另一方面可以及时调用电池温度过低模块，避免因单个储能子模块影响整个储能系统的充放电电流，总体上提高储能系统的利用率和可靠性。
在一种可能的实施方式中，所述控制N个所述储能子模块的状态，包括：获取所述状态参数中的每一项参数的权重系数；根据每个所述储能子模块的所述状态参数和所述状态参数中的每一项参数的权重系数，控制N个所述储能子模块的状态。
本申请实施例中，SOC、SOH、IGBT结温和电池温度对于提高系统的稳定性和可靠性都非常重要，但是其重要的程度有所不同。用权重系数来体现每个状态参数对于储能系统的重要性，并将状态参数和相应的权重系数结合，一起控制储能子模块的状态，可以提高被投入和切出的储能子模块的准确性，进一步提高储能系统的利用率和可靠性。
在一种可能的实施方式中，所述根据每个所述储能子模块的所述状态参数和所述状态参数中的每一项参数的权重系数，控制N个所述储能子模块的状态，包括：根据所述状态参数中的每一项参数，确定所述状态参数中的每一项参数的量化值；根据所述状态参数中的每一项参数的量化值和权重系数，控制N个所述储能子模块的状态。
本申请实施例中，将状态参数和对应的权重系数结合起来控制储能子模块的状态，可进一步提高系统的利用率和可靠性；用具体的量化值来衡量每个储能子模块的状态参数，这样有利于精准控制每个储能子模块的状态。
在一种可能的实施方式中，所述确定所述状态参数中的每一项参数的量化值，包括：在所述储能系统处于充电的情况下，确定每个所述储能子模块的SOC量化值为Score SOC(x)＝100-SOC(x)；或在所述储能系统处于放电的情况下，确定每个所述储能子模块的SOC的所述量化值为Score SOC(x)＝SOC(x)；其中，SOC(x)为第X个所述储能子模块的SOC；Score SOC(x)为第X个所述储能子模块的SOC的量化值。
本申请实施例中，用具体的量化值来衡量储能子模块的每个状态参数，进而控制每个储能子模块的状态，有利于提高储能系统投入和切出储能子模块的准确性。通过在储能系统的充电状态和放电状态下，赋予其中状态参数SOC不同的量化值，这样储能系统在充电状态和放电状态下调用不同的储能子模块，可以实现每个储能子模块之间的SOC均衡，避免因储能子模块的SOC不均衡而导致的储能系统的可用容量下 降，进而提高系统的利用率。
在一种可能的实施方式中，所述确定所述状态参数中的每一项参数的量化值，包括以下至少一项：确定每个所述储能子模块的SOH的量化值为Score SOH(x)＝SOH(x)；确定每个所述储能子模块的IGBT结温的量化值为Score temp- IGBT(x)＝100-Temp IGBT(x)；确定每个所述储能子模块的电池温度的量化值为Score temp- bat(x)＝100-Temp bat(x)；其中，SOH(x)、Temp IGBT(x)和Temp bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温，Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温的量化值。
本申请实施例中，用具体的Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)来衡量储能子模块的状态参数SOH、IGBT结温和电池最低温，进而控制每个储能子模块的状态，有利于提高储能系统投入和切出储能子模块的准确性。
在一种可能的实施方式中，其特征在于，所述根据所述状态参数中每一项参数的量化值和权重系数，控制N个所述储能子模块的状态，包括：根据每个所述储能子模块的所述状态参数中每一项参数的量化值和权重系数，确定每个所述储能子模块的综合量化值P(x)；根据每个所述储能子模块的P(x)，选择N个所述储能子模块中所述P(x)最大的n个所述储能子模块为投入状态，N个所述储能子模块中剩余的所述储能子模块为切出状态。
本申请实施例中，在储能系统的运行过程中，采集每个储能子模块的SOC、SOH、IGBT结温和电池最低温，并将这些状态参数归一化，用综合量化值P(x)对储能子模块进行均衡切入和切出排序。这样的控制状态方式降低了控制算法的时间复杂度，提升了储能系统的响应效率，有利于系统长期稳定运行。
在一种可能的实施方式中，所述P(x)为：
P(x)＝Weight SOC*Score SOC(x)+Weight health*(Score temp-IGBT(x)+Score SOH(x))+Weight temp-bat*Score temp-bat(x)；
其中，Weight SOC、Weight health、Weight temp-bat为所述储能子模块的SOC、SOH与IGBT结温和电池最低温的权重系数。
本申请实施例中，将SOC、SOH、IGBT结温和电池最低温归一化，用综合量化值P(x)对储能子模块进行均衡切入和切出排序，降低了控制算法的时间复杂度，提升了储能系统的响应效率，有利于系统长期稳定运行。
在一种可能的实施方式中，每个所述储能子模块的所述状态参数的权重系数的和为1，所述SOC的权重系数大于或等于0.7。
本申请实施例中，用权重系数可以体现每个状态参数对于储能系统的重要性；进一步地，每个储能子模块的所有状态参数对应的权重系数总和为1，其中SOC对应的权重系数大于等于0.7，这样可以在控制储能子模块的状态时，着重考虑对储能系统稳定控制起着重要因素的SOC，这样可以最大程度上保证系统长期稳定可靠的运行。
在一种可能的实施方式中，所述方法还包括：根据每个所述储能子模块的每一项参数，确定每个所述储能子模块的每一项参数的变异系数；根据所述变异系数，调节所述权重系数。
本申请实施例中，将储能子模块的状态参数与权重系数结合，用综合量化值的排序来决定储能子模块的状态，可以降低控制算法的时间复杂度和提升系统响应效率。在系统的运行中，动态调整权重系数并重新计算综合量化值，有利于储能系统长期的稳定运行。
在一种可能的实施方式中，所述调节所述权重系数包括：判断每个所述储能子模块的每一项参数的变异系数是否大于所述系统的变异系数阈值；在所述变异系数大于所述变异系数阈值的情况下，调节所述状态参数的权重系数。
本申请实施例中，若某个状态参数的变异系数大于储能系统的变异系数阈值，则改变该状态参数对应的权重系数，否则该状态参数对应的权重系数不变。通过对变异系数后进行判断后，若变异系数有较大的变化，再改变相应状态参数的权重系数，这样既有利于系统长期稳定的运行，又可以提高储能系统效率。
在一种可能的实施方式中，所述根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，包括：在所述储能子模块的IGBT结温大于所述储能系统的IGBT结温阈值的情况下，控制所述储能子模块为切出状态。
本申请实施例中，若某个储能子模块的IGBT结温大于储能系统的IGBT结温阈值，那么该储能子模块会对系统产生不利影响，所以应该及时将其从储能系统的工作中切出。通过将IGBT结温大于储能系统IGBT结温阈值的储能子模块控制为切出状态，可以维护储能系统的安全。
第二方面，提供了一种储能系统，包括：N个储能子模块，N为大于1的正 整数；控制器，用于获取N个所述储能子模块中的每个所述储能子模块的状态参数，所述状态参数包括：电池剩余电量SOC以及电池健康度SOH、IGBT结温和电池温度中的至少一项参数，根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，所述工作状态包括投入状态和切出状态。
在一种可能的实施方式中，所述控制器用于：获取所述状态参数中的每一项参数的权重系数；根据每个所述储能子模块的所述状态参数和所述状态参数中的每一项参数的权重系数，控制N个所述储能子模块的状态。
在一种可能的实施方式中，所述控制器用于：根据所述状态参数中的每一项参数，确定所述状态参数中的每一项参数的量化值；根据所述状态参数中的每一项参数的量化值和所述权重系数，控制N个所述储能子模块的状态。
在一种可能的实施方式中，所述控制器用于：在所述储能系统处于充电的情况下，确定每个所述储能子模块的SOC的量化值为Score SOC(x)＝100-SOC(x)；或在所述储能系统处于放电的情况下，确定每个所述储能子模块的SOC的所述量化值为Score SOC(x)＝SOC(x)；其中，SOC(x)为第X个所述储能子模块的SOC；Score SOC(x)为第X个所述储能子模块的SOC的量化值。
在一种可能的实施方式中，所述控制器用于以下至少一项：确定每个所述储能子模块的SOH的量化值为Score SOH(x)＝SOH(x)；确定每个所述储能子模块的IGBT结温的量化值为Score temp-IGBT(x)＝100-Temp IGBT(x)；确定每个所述储能子模块的电池温度的量化值为Score temp-bat(x)＝100-Temp bat(x)；其中，SOH(x)、Temp IGBT(x)和Temp bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温，Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温的量化值。
在一种可能的实施方式中，所述控制器用于：根据每个所述储能子模块的所述状态参数中每一项参数的量化值和权重系数，确定每个所述储能子模块的综合量化值P(x)；根据每个所述储能子模块的P(x)，选择N个所述储能子模块中所述P(x)最大的n个所述储能子模块为投入状态，N个所述储能子模块中剩余的所述储能子模块为切出状态。
在一种可能的实施方式中，所述P(x)为：
P(x)＝Weight SOC*Score SOC(x)+Weight health*(Score temp-IGBT(x)+Score SOH(x))+Weight temp-bat*Score temp-bat(x)；
其中，Weight SOC、Weight health、Weight temp-bat为所述储能子模块的SOC、SOH与IGBT结温和电池最低温的权重系数。
在一种可能的实施方式中，每个所述储能子模块的所述状态参数的权重系数的和为1，所述SOC的权重系数大于或等于0.7。
在一种可能的实施方式中，所述控制器用于：根据每个所述储能子模块的所述状态参数中的每一项参数，确定每个所述储能子模块的每一项参数的变异系数；根据所述变异系数，调节所述权重系数。
在一种可能的实现方式中，所述控制器用于：判断每个所述储能子模块的每一项参数的变异系数是否大于所述储能系统的变异系数阈值；在所述变异系数大于所述变异系数阈值的情况下，调节所述状态参数的所述权重系数。
在一种可能的实现方式中，所述控制器还用于：在所述储能子模块的IGBT结温大于所述储能系统的IGBT结温阈值的情况下，控制所述储能子模块为切出状态。
第三方面，提供了一种储能系统控制的装置，包括处理器和存储器，所述存储器用于存储计算机程序，所述处理器用于调用所述计算机程序，使所述装置实现第一方面中任意一种可能的实施方式中的方法。
第四方面，提供了一种可读存储介质，所述可读存储介质存储有计算机程序，所述计算机程序被计算设备执行时使得所述计算设备实现第一方面中任意一种可能的实施方式中的方法。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，显而易见地，下面所描述的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据附图获得其他的附图。
图1是本申请应用的储能系统的示意图；
图2是本申请一实施例的储能子模块的结构示意图；
图3是本申请另一实施例的储能子模块的结构示意图；
图4是本申请一实施例的储能系统的控制方法的示意性流程图；
图5是本申请另一实施例的储能系统的控制方法的示意性流程图；
图6是本申请一实施例的储能系统的示意性框图；
图7是本申请一实施例的储能系统控制的装置的示意性框图。
具体实施方式
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除非另有定义，本申请所使用的所有的技术和科学术语与属于本申请的技术领域的技术人员通常理解的含义相同；本申请中在申请的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本申请；本申请的说明书和权利要求书及上述附图说明中的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。本申请的说明书和权利要求书或上述附图中的术语“第一”、“第二”等是用于区别不同对象，而不是用于描述特定顺序或主次关系。
在本申请中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的个个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本申请所描述的实施例可以与其它实施例相结合。
在本申请的描述中，需要说明的是，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”、“附接”、“设置”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是直接相连，也可以通过中间媒介间接相连，可以是两个元件内部的连通。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本申请中的具体含义。
本申请中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本申请中字符“/”，一般表示前后关联对象是一种“或”的关系。
柔性直流输电是新一代的直流输电技术，其在结构上是由换流站和直流输电线路(通常为直流电缆)构成，而换流站又是由换流器和换流变压设备，换流阻抗设备等组成。与基于相控换相技术的电流源换流器型高压直流输电不同，柔性直流输电中的换流器为电压源换流器，其最大的特点在于采用了可关断器件和高频调制技术。柔性直流输电具有可向无源网络供电、不会出现换相失败、换流站间无需通信以及易于构成多端直流系统等优点。
为加强柔性直流输电系统的有功功率调节能力，充分发挥柔性直流输电系统参与电网支撑的作用，在柔性直流输电系统中应用储能系统具有重要的研究意义。在柔性直流输电系统中运用储能系统主要有以下三点作用：(1)柔性直流输电是新能源并网的有效方式，通过将储能系统应用于柔性直流输电系统可以有效抑制新能源固有的波动对电网的不利影响；(2)通过将储能系统应用于柔性直流输电系统可降低故障对电网造成的功率冲击，提高电力系统的稳定性和安全性；(3)功率盈余是威胁柔性直流输电系统安全运行的重要问题，通过应用储能系统存储盈余功率，可保障系统故障防御能力，提高柔性直流输电系统的运行可靠性。
而随着在柔性直流输电系统中加入储能单元，储能单元的SOC的均衡成为系统稳定控制的重要因素。因此越来越多的人在研究如何在柔性直流输电系统中达到SOC的均衡。但是为保证储能系统长期稳定可靠地运行，储能单元的其他因素，例如SOH、IGBT开关器件的损耗也需要最大程度地降低。
鉴于此，本申请实施例提供了一种储能系统的控制方法和储能系统，能够实现根据多个状态控制储能系统中的储能子模块的工作状态，进而提高系统的利用率和可靠性。
图1是本申请应用的储能系统的示意图。如图1所示，该储能系统10包括N个储能子模块11，N为大于1的正整数，N个储能子模块11中的每个储能子模块可串联排列。
图2是本申请一实施例的储能子模块的结构示意图，图3是本申请另一实施例的储能子模块的结构示意图。如图2和图3所示，储能子模块由功率模块211和电池模块212组成，储能子模块中的功率模块211为投入状态时，与功率模块相接的电池模块212即为充电或放电状态；当功率模块211为切出状态时，与功率模块211相接的电池模块212即为静置状态。
图4是本申请一实施例的储能系统的控制方法的示意性流程图。该储能系统包括N个储能子模块，N为大于1的正整数。例如，该储能系统可以是如图1所示的储能系统。如图4所示，该方法400包括：
S410，获取N个所述储能子模块中的每个储能子模块的状态参数，状态参数包括：SOC，以及SOH、IGBT结温和电池温度中的至少一项参数；
S420，根据每个储能子模块的状态参数，控制N个储能子模块的工作状态。
其中，工作状态包括投入状态和切出状态。
本申请实施例中，SOC是电池使用一段时间或长期搁置不用与其完全充电状态的容量的比值，通常用百分数表示。其取值范围为0～1，当SOC＝0时，表示电池放电完全，当SOC＝1时表示电池完全充满。
本申请实施例中，SOH表示电池容量、健康度、性能状态，即电池满充容量相对额定容量的百分比，新出厂电池健康度为100％，完全报废则为0％。
本申请实施例中，IGBT是由双极型三极管(Bipolar Junction Transistor，BJT)和绝缘栅型场效应管(Metal Oxide Semiconductor,MOS)组成的复合全控型电压驱动式功率半导体器件，兼有(Metal-Oxide-Semiconductor Field-Effect Transistor,MOSFET)金氧半场效晶体管的高输入阻抗和电力晶体管(Giant Transistor,GTR)的低导通压降两方面的优点。IGBT结温表示IGBT的实际工作温度，其对储能系统的稳定性有着一定的影响。
本申请实施例中，电池温度即为储能子模块中的电池模块工作时的温度，包括电池最低温、电池最高温等典型温度。因电池温度在储能系统的工作过程中会有所变化，因此可以在系统工作过程中，采集电池温度数值后，将电池温度数值缓存于系统中，并进行实时更新；或者在储能系统中设定温度采集条件，例如低于某个值才进行采集。总之，本申请对每个状态参数的采集方式无特别要求，为了方便说明，即统一称为获取状态参数的值。
一方面，N个储能子模块组成储能系统，因此N个储能子模块的电池可用容量组成储能系统的可用容量。当储能子模块间的SOC差距过大时，系统总是优先选择SOC较大的储能子模块，将SOC较低的储能子模块搁置，久而久之将会造成储能系统的可用容量下降，使储能系统的利用率降低。另外，当系统总是选择电池健康度高，或者总是选择电池健康度低的储能子模块时，也会造成储能系统的可用容量下降。
另一方面，若储能子模块中的功率模块中的IGBT结温过高时，该储能子模块会影响储能系统工作的稳定性；而电池模块中的电池温度过低时，该储能子模块的工作电流会变小。若不及时调用该储能子模块，则会导致串联的储能系统的工作电流变小，影响储能系统的工作。
上述方案中，在储能系统中的N个储能子模块的状态未确定的情况下，先获取N个储能子模块中的每个储能子模块的SOC，以及SOH、IGBT结温和电池温度中的至少一项，来控制每个储能子模块的状态。这样根据每个储能子模块的SOC，以及SOH、IGBT结温和电池温度中的至少一项来控制储能子模块的状态，一方面可以实现每个储能子模块之间的损耗均衡，避免因储能子模块的SOC或SOH不均衡导致储能系统的可用容量下降；另一方面可以即时调用温度过低模块，避免因单个子模块影响整个储能系统的充放电电流，从整体上提高储能系统的利用率和可靠性。
在一些实施例中，获取状态参数中的每一项参数的权重系数；根据每个储能子模块的状态参数和状态参数中的每一项参数的权重系数，控制N个储能子模块的状态。
为了显示若干量数在总量中所具有的重要程度，分别给予若干量数不同的比例系数。在本申请实施例中，为了显示SOC、SOH、IGBT结温和电池温度对储能系统稳定运行的重要程度，给予这4个状态参数对应的权重系数。
上述方案中，SOC、SOH、IGBT结温和电池温度对于提高储能系统的稳定性和可靠性都非常重要，但是其重要的程度有所不同。用权重系数来体现每个状态参数对于储能系统的重要性，并将状态参数和相应的权重系数结合，一起控制储能子模块的状态，可以提高被投入和切出的储能子模块的准确性，进一步提高储能系统的利用率和可靠性。
在一些实施例中，根据状态参数中的每一项参数，确定状态参数中的每一项参数的量化值；根据状态参数中每一项参数的量化值和权重系数，控制N个储能子模块的状态。
如前文所述，将状态参数和对应的权重系数结合来控制储能子模块的状态，可进一步提高系统的利用率和可靠性。
上述方案中，用具体的量化值来衡量每个储能子模块的状态参数，这样有利于精准控制每个储能子模块的状态。
在一些实施例中，在储能系统处于充电的情况下，确定每个储能子模块的SOC量化值为Score SOC(x)＝100-SOC(x)；或，在储能系统处于放电的情况下，确定每个储能子模块的SOC的量化值为Score SOC(x)＝SOC(x)；其中，SOC(x)为第X个储能子模块的SOC；Score SOC(x)为第X个储能子模块的SOC的量化值。
本申请实施例中，量化值，即将状态参数的数值转换为可以进行运算的量值。
用具体的量化值来衡量储能子模块的每个状态参数，进而控制每个储能子模块的状态，有利于提高储能系统投入和切出的储能子模块的准确性。而对于SOC这个状态参数来说，在储能系统处于充电时，应优先选择SOC较低的储能子模块进行投入；在储能系统处于放电时，应优先选择SOC较高的储能子模块进行投入。这样可以在储能系统的不同状态下，实现所有储能子模块之间SOC均衡。
上述方案中，通过在储能系统充电状态和放电状态下，赋予状态参数SOC不同的量化值，储能系统在充电状态下和放电情况下调用不同的储能子模块，可以实现每个储能子模块之间的SOC均衡，避免因储能子模块的SOC不均衡而导致的储能系统的可用容量下降，进而提高系统的利用率。
在一些实施例中，确定每个储能子模块的SOH的量化值为Score SOH(x)＝SOH(x)；确定每个储能子模块的IGBT结温的量化值为Score temp-IGBT(x)＝100-Temp IGBT(x)；确定每个储能子模块的电池温度的量化值为Score temp-bat(x)＝100-Temp bat(x)；其中，SOH(x)、Temp IGBT(x)和Temp bat(x)为第X个储能子模块的SOH、IGBT结温和电池最低温，Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)为第X个储能子模块的SOH、IGBT结温和电池最低温的量化值。
本申请实施例中，SOH、IGBT结温和电池温度的对应量化值Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)可以同时获取或者获取其中的至少一项。
上述方案中，用具体的Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)来衡量储能子模块的状态参数SOH、IGBT结温和电池最低温，进而控制每个储能子模块的状态，有利于提高储能系统投入和切出储能子模块的准确性。
在一些实施例中，根据每个储能子模块的状态参数中每一项参数的量化值和权重系数，确定每个储能子模块的综合量化值P(x)；根据每个储能子模块的P(x)， 选择N个储能子模块中P(x)最大的n个储能子模块为投入状态，N个储能子模块中剩余的储能子模块为切出状态。
如前文所述，SOC、SOH、IGBT结温和电池温度从不同方面影响储能系统的稳定性，并且这些状态参数对储能系统的重要程度也不完全相同，因此将这些状态参数的量化值和对应状态参数的权重系数结合，共同来控制储能子模块的状态。但是在具体的运算过程中分别运算每个状态参数的值，那么运算量将会很大。
上述方案中，在储能系统的运行过程中，通过采集每个储能子模块的SOC、SOH、IGBT结温和电池最低温，并将这些参数归一化，用综合量化值P(x)对储能子模块进行均衡切入和切出排序。这样的控制状态方式降低了控制算法的时间复杂度，提升了储能系统的响应效率，有利于系统长期稳定运行。
在一些实施例中，P(x)为：
P(x)＝Weight SOC*Score SOC(x)+Weight health*(Score temp-IGBT(x)+Score SOH(x))+Weight temp-bat*Score temp-bat(x)；
其中，Weight SOC、Weight health、Weight temp-bat为储能子模块的SOC、SOH与IGBT结温和电池最低温的权重系数。
上述方案中，将SOC、SOH、IGBT结温和电池最低温归一化，用具体的综合量化值P(x)对储能子模块进行均衡切入和切出排序，降低了控制算法的时间复杂度，提升了储能系统的响应效率，有利于系统长期稳定运行。
在一些实施例中，每个储能子模块的状态参数的权重系数的和为1，SOC的权重系数大于或等于0.7。
SOC、SOH、IGBT结温和电池温度从不同方面影响储能系统的稳定性，并且这些状态参数对储能系统的重要程度也不完全相同，因此用权重系数的数值大小来体现状态参数对于储能系统的重要性。另外，将每个储能子模块的状态参数的权重系数的和限定为1，这样便于计算，也便于统计和分析储能系统在计算过程中的各项权重系数的变化。
上述方案中，用权重系数可以体现每个状态参数对于储能系统的重要性；进一步地，每个储能子模块的所有状态参数对应的权重系数总和为1，其中SOC对应的权重系数大于等于0.7，这样可以在控制储能子模块的状态时，着重考虑对储能系统稳定控制起着重要因素的SOC，这样可以最大程度上保证系统长期稳定可靠的运行。
此处需要说明的是，以上所述SOC的权重系数为0.7只是举例说明，SOC对应的权重系数还可以为0.6、0.5等数值，只要SOC对应的权重系数在所有状态参数对应的权重系数和中占比最大即可，本申请对SOC具体的权重系数值无特别限定。
在一些实施例中，根据每个储能子模块的每一项参数，确定每个储能子模块的每一项参数的变异系数；根据变异系数，调节权重系数。
本申请实施例中，变异系数(Coefficient of Variation,CV)为当需要比较两组数据离散程度大小的时候，如果两组数据的测量尺度相差太大，或者数据量纲的不同，可以消除测量尺度和量纲的影响，它是原始数据标准差与原始数据平均数的比。CV没有量纲，也就可以进行客观比较。CV是反映数据离散程度的绝对值。其数据大小不仅受变量值离散程度的影响，而且还受变量值平均水平大小的影响。
将储能子模块的状态参数与权重系数结合，用综合量化值的排序来决定储能子模块的状态，可以降低控制算法的时间复杂度和提升系统响应效率。
上述方案中，在系统的运行中，动态调整权重系数并重新计算综合量化值，有利于储能系统长期的稳定运行。
在一些实施例中，判断每个储能子模块的每一项参数的变异系数是否大于储能系统的变异系数阈值；在变异系数大于变异系数阈值的情况下，调节状态参数的权重系数。
在储能系统的不断运行过程中，巨大的运算量可能会使变异系数发生变化，而变异系数的变化将直接影响运算结果的准确性。但是若变异系数变化过小，其对运算结果的准确性影响也较小，因此此时并不需要改变对应参数的权重系数。
本申请实施例中，储能系统的变异系数阈值可以在程序开始人为设置，变异系数可以为10，也可以为20，本申请对此不作限定。
本申请实施例中，某个权重系数的变异系数较大则表明在储能系统的工作过程中，该权重系数的变化较大，因此对计算结果就会有较大的影响。所以对于变异系数较大的状态参数而言，可以以0.1为增减幅度对权重系数进行调节。例如，对于权重系数较小的，可增加0.1；权重系数较大的，可减小0.1。以上只是举例说明，具体的调整幅度以及调整对象以储能系统实际运行的情况为主，例如，对于值较小的权重系数可以以0.05为增减幅度，本申请对此不作任何的限定。
上述方案中，若某个状态参数的变异系数大于储能系统的变异系数阈值，则改变该状态参数对应的权重系数，否则该状态参数对应的权重系数不变。通过对变异系数后进行判断后，若变异系数有较大的变化，再改变相应状态参数的权重系数，这样不断调整权重系数，可以让计算结果更加精准，既有利于系统长期稳定的运行，又可以提高储能系统效率。
在一些实施例中，在储能子模块的IGBT结温大于储能系统的IGBT结温阈值的情况下，控制储能子模块为切出状态。
若某个储能子模块的IGBT结温大于储能系统的IGBT结温阈值，那么该储能子模块会对系统产生不利影响，所以应该及时将其从储能系统的工作中切出。
上述方案中，通过将IGBT结温大于储能系统IGBT结温阈值的储能子模块控制为切出状态，可以维护储能系统的安全。
本申请实施例中，该储能系统的控制方法可以设置为当需投入的储能子模块变化时启动，也可以设置为按固定周期启动，本申请对控制方法的启动条件不作任何限定。
图5是本申请又一实施例的储能系统的控制方法的流程图。本实施例与前述实施例中类似的步骤可以参考前述实施例，为了简洁，在此不再赘述。
步骤S501，开始。
步骤S502，确定需要投入的储能子模块数量n。
步骤S503，获取SOC、SOH、IGBT结温和电池温度。
步骤S504，获取各状态参数的权重系数：Weight SOC、Weight health、Weight temp-bat。
步骤S505，判断Temp IGBT(x)是否大于IGBT结温阈值MAX temp-IGBT(x)。
步骤S506，若Temp IGBT(x)大于MAX temp-IGBT(x)，该储能子模块为切出状态。
步骤S507，若Temp IGBT(x)不大于MAX temp-IGBT(x)，获取缓存Temp bat(x)。
步骤S508，确定SOC、SOH、IGBT结温和电池最低温量化值。
步骤S509，计算各储能子模块的综合量化值P(x)。
步骤S510，根据P(x)排序。
步骤S511，确定P(x)前n个储能子模块为投入状态。
步骤S512，统计所有储能子模块的变异系数。
步骤S513，判断变异系数是否大于储能系统的变异系数。
步骤S514，若变异系数大于储能系统的变异系数，调整权重系数，保持权重系数的和为1，且Weight SOC＞0.7。
步骤S515，若变异系数不大于储能系统的变异系数，判断系统是否退出。
步骤S516，若退出系统，结束。
本申请实施例还提供了一种储能系统，图6是本申请一实施例的储能系统的示意性框图。如图6所示，储能系统10包括：N个储能子模块11，N为大于1的正整数；控制器12，用于获取N个储能子模块11中的每个储能子模块11的状态参数，状态参数包括：电池剩余电量SOC以及电池健康度SOH、IGBT结温和电池温度中的至少一项参数，根据每个储能子模块的状态参数，控制N个储能子模块11的工作状态，所述工作状态包括投入状态和切出状态。
在一些实施例中，控制器12用于：获取状态参数中的每一项参数的权重系数；根据每个储能子模块的状态参数和状态参数中的每一项参数的权重系数，控制N个储能子模块的状态。
在一些实施例中，控制器12用于：根据状态参数中的每一项参数，确定状态参数中的每一项参数的量化值；根据状态参数中的每一项参数的量化值和权重系数，控制N个储能子模块的状态。
在一些实施例中，控制器12用于：在储能系统处于充电的情况下，确定每个储能子模块的SOC的量化值为Score SOC(x)＝100-SOC(x)；或在储能系统处于放电的情况下，确定每个储能子模块的SOC的量化值为Score SOC(x)＝SOC(x)；其中，SOC(x)为第X个储能子模块的SOC；Score SOC(x)为第X个储能子模块的SOC的量化值。
在一些实施例中，控制器12用于以下至少一项：确定每个储能子模块的SOH的量化值为Score SOH(x)＝SOH(x)；确定每个储能子模块的IGBT结温的量化值为Score temp-IGBT(x)＝100-Temp IGBT(x)；确定每个储能子模块的电池温度的量化值为Score temp- bat(x)＝100-Temp bat(x)；其中，SOH(x)、Temp IGBT(x)和Temp bat(x)为第X个储能子模块的SOH、IGBT结温和电池最低温，Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)为第X个储能子模块的SOH、IGBT结温和电池最低温的量化值。
在一些实施例中，控制器12用于：根据每个储能子模块的状态参数中每一项参数的量化值和权重系数，确定每个储能子模块的综合量化值P(x)；根据每个储能 子模块的P(x)，选择N个储能子模块中P(x)最大的n个储能子模块为投入状态，N个储能子模块中剩余的储能子模块为切出状态。
在一些实施例中，P(x)为：
P(x)＝Weight SOC*Score SOC(x)+Weight health*(Score temp-IGBT(x)+Score SOH(x))+Weight temp-bat*Score temp-bat(x)；
其中，Weight SOC、Weight health、Weight temp-bat为储能子模块的SOC、SOH与IGBT结温和电池最低温的权重系数。
在一些实施例中，每个储能子模块的状态参数的权重系数的和为1，SOC的权重系数大于或等于0.7。
在一些实施例中，控制器12用于：根据每个储能子模块的状态参数中的每一项参数，确定每个储能子模块的每一项参数的变异系数；根据变异系数，调节权重系数。
在一些实施例中，控制器12用于：判断每个储能子模块的每一项参数的变异系数是否大于储能系统的变异系数阈值；在变异系数大于变异系数阈值的情况下，调节状态参数的权重系数。
在一些实施例中，控制器12用于：在储能子模块的IGBT结温大于储能系统的IGBT结温阈值的情况下，控制储能子模块为切出状态。
本申请实施例还提供了一种储能系统控制的装置。如图7所示，该储能系统控制的装置70包括处理器71和存储器72，其中，存储器72用于存储计算机程序，处理器71用于调用计算机程序，使装置70实现前述本申请各种实施例的方法。
本申请实施例还提供了一种可读存储介质。该可读存储介质存储有计算机程序，该计算机程序被计算设备执行时使得该计算设备实现本申请各种实施例的方法。
虽然已经参考优选实施例对本申请进行了描述，但在不脱离本申请的范围的情况下，可以对其进行各种改进并且可以用等效物替换其中的部件。尤其是，只要不存在结构冲突，各个实施例中所提到的各项技术特征均可以任意方式组合起来。本申请并不局限于文中公开的特定实施例，而是包括落入权利要求的范围内的所有技术方案。

Claims (24)

  1. 一种储能系统的控制方法，其特征在于，所述储能系统包括N个储能子模块，N为大于1的正整数，所述方法包括：
    获取N个所述储能子模块中的每个所述储能子模块的状态参数，所述状态参数包括：电池剩余电量SOC，以及电池健康度SOH、IGBT结温和电池温度中的至少一项参数；
    根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，所述工作状态包括投入状态和切出状态。
  2. 根据权利要求1所述的控制方法，其特征在于，所述控制N个所述储能子模块的状态，包括：
    获取所述状态参数中的每一项参数的权重系数；
    根据每个所述储能子模块的所述状态参数和所述状态参数中的每一项参数的权重系数，控制N个所述储能子模块的状态。
  3. 根据权利要求2所述的控制方法，其特征在于，所述根据每个所述储能子模块的所述状态参数和所述状态参数中的每一项参数的权重系数，控制N个所述储能子模块的状态，包括：
    根据所述状态参数中的每一项参数，确定所述状态参数中的每一项参数的量化值；
    根据所述状态参数中的每一项参数的量化值和权重系数，控制N个所述储能子模块的状态。
  4. 根据权利要求3所述的控制方法，其特征在于，所述确定所述状态参数中的每一项参数的量化值，包括：
    在所述储能系统处于充电的情况下，确定每个所述储能子模块的SOC的量化值为Score SOC(x)＝100-SOC(x)；或
    在所述储能系统处于放电的情况下，确定每个所述储能子模块的SOC的量化值为Score SOC(x)＝SOC(x)；
    其中，SOC(x)为第X个所述储能子模块的SOC；Score SOC(x)为第X个所述储能子模块的SOC的量化值。
  5. 根据权利要求3或4所述的控制方法，其特征在于，所述确定所述状态参数中的每一项参数的量化值，包括以下至少一项：
    确定每个所述储能子模块的SOH的量化值为Score SOH(x)＝SOH(x)；
    确定每个所述储能子模块的IGBT结温的量化值为Score temp-IGBT(x)＝100-Temp IGBT(x)；
    确定每个所述储能子模块的电池温度的量化值为Score temp-bat(x)＝100-Temp bat(x)；
    其中，SOH(x)、Temp IGBT(x)和Temp bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温，Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温的量化值。
  6. 根据权利要求4或5所述的控制方法，其特征在于，所述根据所述状态参数中每一项参数的量化值和权重系数，控制N个所述储能子模块的状态，包括：
    根据每个所述储能子模块的所述状态参数中每一项参数的量化值和权重系数，确定每个所述储能子模块的综合量化值P(x)；
    根据每个所述储能子模块的P(x)，选择N个所述储能子模块中所述P(x)最大的n个所述储能子模块为投入状态，N个所述储能子模块中剩余的所述储能子模块为切出状态。
  7. 根据权利要求6所述的控制方法，其特征在于，所述P(x)为：
    P(x)＝Weight SOC*Score SOC(x)+Weight health*(Score temp-IGBT(x)+Score SOH(x))+Weight temp-bat*Score temp-bat(x)；
    其中，Weight SOC、Weight health、Weight temp-bat为所述储能子模块的SOC、SOH与IGBT结温和电池最低温的权重系数。
  8. 根据权利要求1至7中任一项所述的控制方法，其特征在于，
    每个所述储能子模块的所述状态参数的权重系数的和为1，所述SOC的权重系数大于或等于0.7。
  9. 根据权利要求1至8中任一项所述的控制方法，其特征在于，所述方法还包括：
    根据每个所述储能子模块的所述状态参数中的每一项参数，确定每个所述储能子模块的每一项参数的变异系数；
    根据所述变异系数，调节所述权重系数。
  10. 根据权利要求9所述的控制方法，其特征在于，所述调节所述权重系数包括：
    判断每个所述储能子模块的每一项参数的变异系数是否大于所述储能系统的变异系数阈值；
    在所述变异系数大于所述变异系数阈值的情况下，调节所述状态参数的权重系数。
  11. 根据权利1至10中任一项所述的控制方法，其特征在于，所述根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，包括：
    在所述储能子模块的IGBT结温大于所述储能系统的IGBT结温阈值的情况下，控制所述储能子模块为切出状态。
  12. 一种储能系统，其特征在于，包括：
    N个储能子模块，N为大于1的正整数；
    控制器，用于获取N个所述储能子模块中的每个所述储能子模块的状态参数，所述状态参数包括：电池剩余电量SOC以及电池健康度SOH、IGBT结温和电池温度中的至少一项参数，根据每个所述储能子模块的所述状态参数，控制N个所述储能子模块的工作状态，所述工作状态包括投入状态和切出状态。
  13. 根据权利要求12所述的储能系统，其特征在于，所述控制器用于：
    获取所述状态参数中的每一项参数的权重系数；
    根据每个所述储能子模块的所述状态参数和所述状态参数中的每一项参数的权重系数，控制N个所述储能子模块的状态。
  14. 根据权利要求13所述的储能系统，其特征在于，所述控制器用于：
    根据所述状态参数中的每一项参数，确定所述状态参数中的每一项参数的量化值；
    根据所述状态参数中的每一项参数的量化值和所述权重系数，控制N个所述储能子模块的状态。
  15. 根据权利要求14所述的储能系统，其特征在于，所述控制器用于：
    在所述储能系统处于充电的情况下，确定每个所述储能子模块的SOC的量化值为Score SOC(x)＝100-SOC(x)；或
    在所述储能系统处于放电的情况下，确定每个所述储能子模块的SOC的所述量化值为Score SOC(x)＝SOC(x)；
    其中，SOC(x)为第X个所述储能子模块的SOC；Score SOC(x)为第X个所述储能子模块的SOC的量化值。
  16. 根据权利要求14或15所述的储能系统，其特征在于，所述控制器用于以下至少一项：
    确定每个所述储能子模块的SOH的量化值为Score SOH(x)＝SOH(x)；
    确定每个所述储能子模块的IGBT结温的量化值为Score temp-IGBT(x)＝100-Temp IGBT(x)；
    确定每个所述储能子模块的电池温度的量化值为Score temp-bat(x)＝100-Temp bat(x)；
    其中，SOH(x)、Temp IGBT(x)和Temp bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温，Score SOH(x)、Score temp-IGBT(x)和Score temp-bat(x)为第X个所述储能子模块的SOH、IGBT结温和电池最低温的量化值。
  17. 根据权利要求15或16所述的储能系统，其特征在于，所述控制器用于：
    根据每个所述储能子模块的所述状态参数中每一项参数的量化值和权重系数，确定每个所述储能子模块的综合量化值P(x)；
    根据每个所述储能子模块的P(x)，选择N个所述储能子模块中所述P(x)最大的n个所述储能子模块为投入状态，N个所述储能子模块中剩余的所述储能子模块为切出状态。
  18. 根据权利要求17所述的储能系统，其特征在于，所述P(x)为：
    P(x)＝Weight SOC*Score SOC(x)+Weight health*(Score temp-IGBT(x)+Score SOH(x))+Weight temp-bat*Score temp-bat(x)；
    其中，Weight SOC、Weight health、Weight temp-bat为所述储能子模块的SOC、SOH与IGBT结温和电池最低温的权重系数。
  19. 根据权利要求12至18中任一项所述的储能系统，其特征在于，
    每个所述储能子模块的所述状态参数的权重系数的和为1，所述SOC的权重系数大于或等于0.7。
  20. 根据权利要求12至19中任一项所述的储能系统，其特征在于，所述控制器用于：
    根据每个所述储能子模块的所述状态参数中的每一项参数，确定每个所述储能子模块的每一项参数的变异系数；
    根据所述变异系数，调节所述权重系数。
  21. 根据权利要求20所述的储能系统，其特征在于，所述控制器用于：
    判断每个所述储能子模块的每一项参数的变异系数是否大于所述储能系统的变异系数阈值；
    在所述变异系数大于所述变异系数阈值的情况下，调节所述状态参数的权重系数。
  22. 根据权利要求12至21所述的储能系统，其特征在于，所述控制器还用于：
    在所述储能子模块的IGBT结温大于所述储能系统的IGBT结温阈值的情况下，控制所述储能子模块为切出状态。
  23. 一种储能系统控制的装置，其特征在于，包括处理器和存储器，所述存储器用于存储计算机程序，所述处理器用于调用所述计算机程序，使所述装置实现上述权利要求1至11中任一项所述的方法。
  24. 一种可读存储介质，其特征在于，所述可读存储介质存储有计算机程序，所述计算机程序被计算设备执行时使得所述计算设备实现上述权利要求1至11中任一项所述的方法。
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2011217487A (ja) * 2010-03-31 2011-10-27 Denso Corp 電池制御システムおよびその制御方法
CN105531866A (zh) * 2013-04-30 2016-04-27 台湾立凯绿能移动股份有限公司 大型电动车电源架构及其电池箱轮休排序控制方法
CN112865139A (zh) * 2021-02-02 2021-05-28 长沙理工大学 储能电站安全参与电网一次调频的优化控制策略
CN113595057A (zh) * 2021-07-29 2021-11-02 国家电网有限公司 一种柔性直流系统用直流侧可控储能装置及控制方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2011217487A (ja) * 2010-03-31 2011-10-27 Denso Corp 電池制御システムおよびその制御方法
CN105531866A (zh) * 2013-04-30 2016-04-27 台湾立凯绿能移动股份有限公司 大型电动车电源架构及其电池箱轮休排序控制方法
CN112865139A (zh) * 2021-02-02 2021-05-28 长沙理工大学 储能电站安全参与电网一次调频的优化控制策略
CN113595057A (zh) * 2021-07-29 2021-11-02 国家电网有限公司 一种柔性直流系统用直流侧可控储能装置及控制方法

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