A Three-Level Equalization Control Method for the State of Charge of Batteries in a Distributed Energy Storage-Type MMC under Complex Operating Conditions

Abstract

The present invention provides a three-level equalization control method for the state of charge (SOC) of batteries in a modular multilevel converter with distributed energy storage (MMC-DES) under complex working conditions; aiming at the operating conditions and topological structure of a high-voltage and high-power distributed energy storage type MMC, a control method for the distributed energy storage type MMC system is established; on this basis, aiming at the differences in the SOC of batteries between phases, between arms, and between sub-modules under complex working conditions, the trapezoidal integration method is used to discretize the battery state of charge equation, and a discrete-time domain prediction power model and a prediction current model are established; furthermore, the predicted values of the battery charge and discharge power or the battery current correction amount that make the SOC of each battery approach consistency are calculated, so as to realize the SOC equalization of each battery in the distributed energy storage type MMC, and solve the problem that the energy consumption of each battery is different and the remaining power is inconsistent due to factors such as the manufacturing process of the battery, the number of charge and discharge cycles, and the degree of aging.

Description

Technical Field

[0001] The present invention relates to the technical fields of flexible DC power transmission technology, energy storage and energy saving technology, and specifically relates to a three-level equalization control method for the state of charge of batteries in a distributed energy storage type MMC under complex working conditions. Background Art

[0002] Under the current severe energy and environmental pressures, the sustainable development of new energy is an inevitable choice. However, the intermittency and uncertainty of new energy power generation lead to power fluctuations and difficulties in grid connection. The emergence of energy storage technology makes up for the defects of the natural characteristics of new energy, combines new energy power generation with large-capacity energy storage devices, and safely and efficiently absorbs a high proportion of new energy power generation, such as cascaded H-bridge chain-type battery energy storage systems and distributed energy storage type modular multilevel converters. The distributed energy storage type MMC with a sub-module topology structure in which batteries are connected in parallel to the capacitor side of half-bridge and full-bridge sub-modules through non-isolated bidirectional DC-DC converters has become one of the most promising energy storage solutions due to its significant advantages such as high operating efficiency, strong power transmission capacity, and flexible adjustment of energy storage capacity.

[0003] Factors such as the manufacturing process of batteries, different numbers of charge and discharge cycles, and varying degrees of aging result in differences in the energy consumption of each battery and inconsistent remaining power. Moreover, the capacity and output power of a single battery are limited, which can prevent some batteries from exiting operation due to over-discharge or deep charging, reducing the energy utilization rate of the batteries. During the operation of the energy storage system, not only the needs of the energy storage unit itself need to be considered, but also the needs of the distributed energy storage type MMC system for the friendly access of far-sea wind power under various complex working conditions need to be considered, so as to maximize the utilization of new energy power generation and fully consider the problem of coordinated operation, and ensure the stability and safety of the entire system. Summary of the Invention

[0004] The present invention provides a three-level equalization control method for the state of charge of batteries in a distributed energy storage type MMC under complex working conditions to solve the challenges and problems of equalizing the state of charge of each battery in a high-level large-capacity distributed energy storage type MMC for the friendly access of far-sea wind power under complex working conditions.

[0005] To achieve the above-mentioned invention purpose, the present invention adopts the following technical solutions:

[0006] 1. A three-level equalization control method for the SOC of batteries in a distributed energy storage type MMC under complex working conditions, specifically as follows:

[0007] Step 1: According to the topology structure of the high-level high-power distributed energy storage type MMC, the battery charging and discharging mechanism, and the working mode of the sub-module, analyze the different operating modes and corresponding operating conditions of the energy storage type MMC, and establish a control method for the distributed energy storage type MMC and a control method for the battery.

[0008] Step 2: Under the dynamic steady-state condition, for the differences in the SOC of the batteries among the phases, between the arms, and between the sub-modules of the distributed energy storage type MMC, the trapezoidal integration method is applied to discretize the state-of-charge equations of the batteries at different moments, and a discrete-time domain prediction power model is established. On this basis, the predicted charge and discharge power values that make the battery SOC approach consistency are calculated, realizing the SOC balance of the batteries among the phases, between the arms, and between the sub-modules of the distributed energy storage type MMC under the dynamic steady-state condition.

[0009] Step 3: Under the AC fault condition, different system protection methods are switched to maintain the stable and safe operation of the distributed energy storage type MMC and the quality of the output power. At the same time, for the differences in the SOC of each battery, the discrete-time domain prediction power model is used to calculate the predicted battery power values, which act on the bidirectional DC-DC converter for battery charge and discharge power and SOC control.

[0010] Step 4: Under the DC fault condition, the system-level control switches to DC current control and the bidirectional DC-DC converter switches to the outer-loop sub-module capacitor voltage control to complete the non-blocking DC fault ride-through. For the differences in the SOC of each battery, a discrete-time domain prediction current model is established, and the current correction amount of each battery is calculated. The battery current correction amount is superimposed on the current reference value generated by the outer-loop voltage control of the DC-DC converter to obtain the corrected current reference value of each battery, realizing the SOC balance problem of all the batteries of the distributed energy storage type MMC under complex conditions.

[0011] The three-level SOC balance control method for the batteries of the distributed energy storage type MMC under complex conditions provided by the present invention solves the problem of extremely unbalanced SOC of the batteries of the high-level and large-capacity distributed energy storage type MMC suitable for the friendly access of far-sea wind power under complex conditions. It can achieve the SOC balance of each battery for the distributed energy storage type MMC with a sub-module topology where the batteries are connected in parallel to the capacitor side of the half-bridge or full-bridge through a non-isolated bidirectional DC-DC converter, improving the energy utilization rate of each battery itself. At the same time, considering the maximum utilization of new energy generation and fully considering the problem of coordinated operation, it also ensures the stability and safety of the high-level and large-capacity distributed energy storage type MMC system for the friendly access of far-sea wind power. Description of the Drawings

[0012] Figure 1 is the design flow chart of the three-level SOC balance control method for the batteries of the distributed energy storage type MMC under complex conditions in the embodiment of the present invention;

[0013] Figure 2 is the topological structure diagram of the high-level and large-capacity distributed energy storage type MMC in the embodiment of the present invention;

[0014] Figure 3 is the system control block diagram of the distributed energy storage type MMC under the dynamic steady-state condition and AC fault in the embodiment of the present invention;

[0015] Figure 4 It is the flow chart of the predicted power model under dynamic and steady-state conditions and AC faults in the embodiments of the present invention;

[0016] Figure 5 It is the control block diagram of the distributed energy storage type MMC system under DC faults in the embodiments of the present invention;

[0017] Figure 6 It is the flow chart of the predicted current model under DC faults in the embodiments of the present invention;

[0018] Figure 7 It is the overall control method diagram of the distributed energy storage type MMC under complex conditions in the embodiments of the present invention; Detailed implementation manners

[0019] The drawings are only for illustrative purposes and cannot be construed as a limitation of this patent; for better illustration of this embodiment, some components in the drawings will be omitted, enlarged or reduced, which do not represent the dimensions of the actual product;

[0020] For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted. The technical solutions of the present invention will be further described below in conjunction with the drawings and embodiments.

[0021] The embodiments of the present invention provide a three-level equalization control method for the state of charge of batteries of a distributed energy storage type MMC under complex conditions. The specific flow chart is as Figure 1 shown, and the specific process is as follows:

[0022] S101: According to the topology of the high-level high-power distributed energy storage type MMC, the battery charging and discharging mechanism, and the operating modes of the sub-modules, analyze the different operating modes and corresponding operating conditions of the energy storage type MMC, and establish a control method for the distributed energy storage type MMC and a battery control method.

[0023] S102: Under dynamic and steady-state conditions, for the differences in the SOC of batteries between phases, between arms, and between sub-modules of the distributed energy storage type MMC, apply the trapezoidal integration method to discretize the state of charge equation of the battery at different times, and establish a discrete-time domain predicted power model. On this basis, calculate the predicted charge and discharge power that makes the SOC of the batteries approach consistency, and realize the SOC equalization of the batteries between phases, between arms, and between sub-modules of the distributed energy storage type MMC under dynamic and steady-state conditions.

[0024] S103: Under AC fault conditions, switch different system protection methods to maintain the stable and safe operation of the distributed energy storage type MMC and the quality of the output power. At the same time, for the differences in the SOC of each battery, apply the discrete-time domain predicted power model to calculate the predicted battery power, and act on the bidirectional DC-DC converter for battery charge and discharge power and SOC control.

[0025] S104: Under DC fault conditions, the system-level control switches to DC current control and the bidirectional DC-DC converter switches to the outer-loop sub-module capacitor voltage control to complete the non-blocking DC fault ride-through. For the differences in the SOC of each battery, a discrete-time domain predictive current model is established to calculate the correction amount of the current of each battery. The correction amount of the battery current is superimposed on the current reference value generated by the outer-loop voltage control of the DC-DC converter to obtain the corrected current reference value of each battery, realizing the SOC balance of all batteries of the distributed energy storage type MMC under complex conditions.

[0026] The three-level equalization control method for the state of charge of each battery of the distributed energy storage type MMC under complex conditions provided by the present invention solves the problem of extremely unbalanced state of charge of the distributed energy storage type MMC with high level and large capacity suitable for the friendly access of far-sea wind power under complex conditions. It can achieve the state of charge balance of each battery for the distributed energy storage type MMC with a sub-module topology of batteries connected in parallel to the capacitor side of half-bridge and full-bridge through a non-isolated bidirectional DC-DC converter, and improve the energy utilization rate of each battery itself. At the same time, considering the maximized utilization of new energy generation and fully considering the problem of coordinated operation, it also ensures the stability and safety of the distributed energy storage type MMC system with high level and large capacity for the friendly access of far-sea wind power.

[0027] 1. In the above S101, the high-level and large-capacity distributed energy storage type MMC is an extended structure of a three-phase voltage source converter, a three-port converter connecting the AC side, DC side, and energy storage side. Its sub-module topology is that the battery is connected in parallel to the capacitor side of the half-bridge and full-bridge sub-modules through a non-isolated bidirectional DC-DC converter. The battery adopts the Shepherd model of lithium iron phosphate battery, simplifies its charge and discharge into a reversible process, and divides its discharge process into three regions: exponential region, rated working region, and deep discharge region. The discharge voltage value under the rated state is the rated voltage E b , and its overall topology is as Figure 2 shown. According to Figure 2 the positive direction of power flow of the distributed energy storage type MMC system for the friendly access of far-sea wind power shown, the power transfer relationship can be divided into 4 operating modes.

[0028] Operating mode 1: P b = 0, P dc = P ac . It is the same as the MMC operating mode and is the idle operating condition of the energy storage system.

[0029] Operating mode 2: P b ≠ 0, P b + P ac = P dc . This mode is the dynamic steady-state operating condition. When there is a power deficit in the AC system, the energy storage system discharges and releases energy to the converter station (Pb > 0). When there is power surplus on the AC side, the energy storage system charges and absorbs energy from the converter station (P b < 0), ensuring the constant and stable operation of the DC system power. This mode is the most common operating condition in the distributed energy storage type MMC system.

[0030] Operating mode three: P ac = 0, P dc = P b . This mode is the AC system fault mode, and power is only transferred from the energy storage system to the DC system.

[0031] Operating mode four: P dc = 0, P ac = P b . This mode is the DC system fault mode, and power is only transferred from the AC system to the energy storage system.

[0032] According to the principle of energy conservation and ignoring the losses of the converter station, the sum of the powers flowing into the three-port converter is zero. Therefore, by controlling the power at both ends, the power of the three ports of the converter can be controlled, increasing the control freedom. The power control method of the distributed energy storage type MMC can be divided into DC side power control, AC side power control, and battery charge and discharge power control. The control method that simultaneously controls the AC side power and the battery charge and discharge power is used as the research object in this invention. The classic VF decoupling control is often used in the offshore MMC station in the far-sea wind power system, and the AC side power is under the maximum power tracking control of the far-sea wind turbine. The non-isolated bidirectional DC-DC converter at the energy storage end adopts double closed-loop control, which can control the battery charge and discharge power more accurately. During the normal operation of the battery, the power reference value is set by the outer loop of the battery charge and discharge power tracking, and the inner loop controls the charge and discharge current to change its battery terminal voltage. When the battery charges the converter station (the battery discharges), the battery terminal voltage increases, and when the converter station discharges the battery (the battery charges), the battery terminal voltage decreases. Then, the duty cycle of the bidirectional DC-DC converter is adjusted to independently control the charge and discharge of each energy storage module, and it is easy to obtain Equation (1) and Equation (2).

[0033] Under the dynamic and steady-state conditions, the control block diagram of the distributed energy storage type MMC system is as Figure 3 shown.

[0034]

[0035] 2. In the above S102, for the distributed energy storage type MMC battery SOC three-level balancing method under dynamic and steady-state conditions, for the power outer loop, a design method of dynamic power reference value based on battery SOC is proposed. The change of each battery SOC is estimated by the ampere-hour integration method, and the dynamic and steady-state power reference value is calculated according to the battery power-current characteristics and the energy conservation principle of the converter. The specific control method is as follows:

[0036] Due to characteristics such as different manufacturing processes, varying numbers of charge-discharge cycles, and uneven aging degrees, there are inconsistencies among batteries. Even when the charge-discharge current is the same, the SOC of each battery is affected by many factors, leading to an increase in differences. The ampere-hour integration method is the most widely used way to estimate SOC in engineering. By calculating the electricity accumulated or consumed by the battery during charge-discharge time, the percentage of available battery power is estimated. Define the state of charge SOC of the battery in the i-th sub-module of the j-phase k-th arm at time t k as jki

[0037]

[0038] According to the power-current relationship, the battery SOC in Equation (3) can be written as the following expression. jki

[0039]

[0040] where SOC jki (t 0 ) is the state of charge at time t 0 , Q r is the remaining battery power, Q m is the maximum battery power, i b is the battery charge-discharge current, P b is the battery charge-discharge power, k 1 is the characteristic parameter of each battery, and u b is the rated voltage of the battery.

[0041] By superimposing the SOC of N batteries in the j-phase k-th arm, the overall SOC of the arm's batteries can be obtained as jki jk

[0042]

[0043] Predicting that at time t k , the SOC of each battery in the j-phase k-th arm is balanced to be consistent, we can obtain jki

[0044]

[0045] Substitute Equation (4) into Equation (6) to establish the prediction power model of the batteries in each sub-module.

[0046]

[0047] Using the trapezoidal integration method to discretize Equation (8), the predicted power value P k of each sub-module battery at time t jki (t k ​​​​​)。

[0048]

[0049] Equation (9) can be rewritten as

[0050]

[0051] where P bjki (t + Δt) is the predicted value of the power of each battery in the k-th arm of the j-th phase at the moment of t + Δt, and P bjki (t) is the measured value of the output power of each battery in the k-th arm of the j-th phase at the moment of t, and P bjk (t + Δt) is the predicted value of the total output power of the batteries in the k-th arm of the j-th phase at the moment of t + Δt, and P bjk (t) is the measured value of the total output power of the batteries in the k-th arm of the j-th phase at the moment of t, Δt is the sampling time, and SOC jk (t) is the measured value of the state of charge of N batteries in the k-th arm of the j-th phase at the moment of t, and SOC jkiave is the average state of charge of each battery in the k-th arm of the j-th phase, and k 2 is the characteristic parameter of each battery.

[0052] Similarly, according to the above predicted power model, the predicted value of the power of the batteries in the k-th arm of the j-th phase at the moment of t + Δt, P bjk (t + Δt), and the predicted value of the power of the overall batteries of the j-th phase, P bj (t + Δt), can be obtained.

[0053]

[0054] In a sampling period Δt, the change in the total output power of the battery system is relatively small, and it can be considered that P b (t + Δt) = P b (t). Therefore, the predicted value of the power of the overall batteries of the j-th phase at the moment of t + Δt, P bj (t + Δt), can be rewritten as

[0055]

[0056] where SOC j (t) is the measured value of the total state of charge of 2N sub-modules of the j-th phase at the moment of t, SOC jave (t) is the measured value of the average state of charge of the batteries of the j-th phase at the moment of t, SOC jkave (t) is the measured value of the average state of charge of the batteries of each arm of the j-th phase at the moment of t, P bj (t) is the measured value of the total output power of the batteries of the j-th phase at the moment of t, P b (t) is the measured value of the total output power of the battery system at the moment of t, and k 3 and k 4 are the characteristic parameters of the arm batteries and the phase batteries, respectively.

[0057]

[0058] Figure 4 It is a flowchart of the predicted power model, which consists of the discrete-time domain predicted power model of the distributed energy storage type MMC battery SOC and the output reference power of the non-isolated bidirectional DC-DC converter by equations (10), (11) and (13).

[0059] In the above S103, when a serious three-phase short-circuit fault occurs in the distributed energy storage type MMC AC system, the distributed energy storage type MMC system needs to continue to transmit active power to the DC system to provide active support. Therefore, it is necessary to control the outer-loop active power and the AC system current to 0 to achieve AC fault ride-through. And complete grid connection and restore steady-state operation as quickly as possible after the AC fault is cleared.

[0060] v sa ,v sb ,v sc =0, i sa ,i sb ,i sc =0 (15)

[0061] Under the AC fault condition, aiming at the differences in battery SOC between phases, between arms and between sub-modules, the outer loop of the bidirectional DC-DC converter adopts sub-module battery power control. At this time, the discrete-time domain predicted power model is the same as the predicted model under dynamic and steady-state conditions as shown in equation (14), calculates the predicted value of the battery power that makes the battery SOC of each battery approach consistency, and realizes the three-level equalization control of the battery SOC under the AC fault condition. The control method block diagram is as Figure 3 shown.

[0062] 4. In the above S104, under the DC fault condition, different distributed energy storage type MMCs with different sub-module topologies need to adopt different system protection methods to maintain the safe and stable operation of the system. When a serious short-circuit fault occurs in the DC system of the distributed energy storage type MMC, the AC system continues to transmit active power to the converter station. For the distributed energy storage type MMC with half-bridge sub-modules, there is a natural DC voltage on the DC bus side, which is equivalent to an uncontrolled rectifier converter and cannot clear the short-circuit current independently. This sub-module topology needs to cooperate with a fast DC circuit breaker to quickly open the fault line and complete the fault blocking of the distributed energy storage type MMC. Considering the investment cost and steady-state loss, a distributed energy storage type MMC with a half-full bridge hybrid sub-module is adopted, and a short-circuit fault ride-through control method is introduced to enable it to have the ability to output negative levels of sub-modules to complete non-blocking ride-through of DC faults. At the same time, according to the following predicted current model, three-level equalization of the battery SOC between phases, between arms and between sub-modules can be achieved. The overall control method of the distributed energy storage type MMC under DC faults is as Figure 5As shown

[0063] The predictive power models between phases and between arm bridges under DC fault conditions are the same as those under dynamic and steady-state conditions, as shown in Equations (11) and (13). However, under DC fault conditions, the battery SOC balance among sub-modules needs to adopt a predictive current model. Therefore, by combining Equations (3) and (6), a predictive current model for the batteries of each sub-module is established.

[0064]

[0065] By discretizing Equation (16) using the trapezoidal integration method, a discrete-time domain predictive current model and the battery current correction amount i jki (t + △t) of each sub-module battery can be obtained.

[0066]

[0067]

[0068] Figure 6 Fig. is the flow chart of the predictive current model. The battery current correction amounts of each sub-module are respectively superimposed on the outer-loop control of the capacitor voltage of each sub-module to obtain the battery current reference value, and the corrected current reference value is obtained, realizing the problem of the SOC balance of all batteries of the distributed energy storage type MMC under DC faults.

[0069]

[0070] Figure 7 Fig. is the overall control method of the distributed energy storage type MMC. Finally, the three-level balance of the charge states of the batteries among phases, between arm bridges and among sub-modules of the distributed energy storage type MMC under complex conditions is realized, solving the problem of the imbalance of the charge states of the batteries caused by different manufacturing processes, aging degrees and different numbers of cycle uses, and improving the energy utilization rate of each battery itself.

[0071] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0072] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0073] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0074] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Those of ordinary skill in the art can still modify or equivalently replace the specific implementation manners of the present invention with reference to the above embodiments. Any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention are within the scope of the claims of the present invention pending approval.

Claims

1. A three - level equalization control method for the battery SOC of a distributed energy storage type MMC under complex working conditions; Characterized in that, Aiming at the extremely uneven problem of the battery SOC of the distributed energy storage type MMC under complex working conditions, the present invention proposes a three - level equalization control method for the battery SOC under complex working conditions, realizing the equalization of the battery SOC between phases, between arms and between sub - modules of the distributed energy storage type MMC with the sub - module topology that the battery is connected in parallel to the capacitor side of the half - bridge and full - bridge sub - modules through a non - isolated bidirectional DC - DC converter, and improving the energy utilization rate of each battery itself; the method includes the following steps: Step 1: According to the topology of the high - level high - power distributed energy storage type MMC, the battery charge - discharge mechanism and the working mode of the sub - modules, analyze the different operation modes and corresponding operation conditions of the energy storage type MMC, and establish a control method for the distributed energy storage type MMC and a control method for the battery; Step 2: Under dynamic and steady - state working conditions, aiming at the differences in the battery SOC between phases, between arms and between sub - modules of the distributed energy storage type MMC, discretize the state - of - charge equation of the battery at different moments by using the trapezoidal integration method, and establish a discrete - time - domain prediction power model; on this basis, calculate the predicted charge - discharge power that makes the battery SOC approach consistency, and realize the equalization of the battery SOC between phases, between arms and between sub - modules of the distributed energy storage type MMC under dynamic and steady - state working conditions; Step 3: Under AC fault conditions, switch different system protection methods to maintain the stable and safe operation of the distributed energy storage type MMC and the quality of the output power; at the same time, aiming at the differences in the battery SOC, calculate the predicted battery power by using the discrete - time - domain prediction power model, and act on the bidirectional DC - DC converter for battery charge - discharge power and SOC control; Step 4: Under DC fault conditions, the system - level control switches to DC current control and the bidirectional DC - DC converter switches to the outer - loop sub - module capacitor voltage control to complete the non - blocking DC fault ride - through; aiming at the differences in the battery SOC, establish a discrete - time - domain prediction current model, and calculate the current correction amount of each battery; superimpose the battery current correction amount on the current reference value generated by the outer - loop voltage control of the DC - DC converter to obtain the corrected current reference value of each battery, and realize the equalization problem of the battery SOC of all batteries of the distributed energy storage type MMC under complex working conditions.

2. The three - level equalization control method for the battery SOC of the distributed energy storage type MMC under complex working conditions according to claim 1, Characterized in that, Steps 1 to 4. The previous step is the basis for the execution of the next step. These 4 steps are closely linked and executed sequentially, forming an organic and inseparable whole. Aiming at the problem of extremely uneven state of charge of batteries in a high-level and large-capacity distributed energy storage type MMC for friendly access of far-sea wind power under complex working conditions, it can achieve the balance of the state of charge of each battery and improve the energy utilization rate of each battery itself for a distributed energy storage type MMC with a sub-module topology where the battery is connected in parallel to the capacitor side of the half-bridge and full-bridge through a non-isolated bidirectional DC-DC converter. At the same time, considering the maximum utilization of new energy power generation and fully considering the problem of coordinated operation, it also ensures the stability and safety of the high-level and large-capacity distributed energy storage type MMC system for friendly access of far-sea wind power.

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