引用本文:马文忠,孙 伟,王玉生,等.基于MMC的分布式储能系统及其快速SOC均衡控制策略[J].电力系统保护与控制,2024,52(16):1-11.
MA Wenzhong,SUN Wei,WANG Yusheng,et al.Distributed energy storage system based on MMC and rapid SOC balancing control strategy[J].Power System Protection and Control,2024,52(16):1-11
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基于MMC的分布式储能系统及其快速SOC均衡控制策略
马文忠,孙 伟,王玉生,等
1.中国石油大学(华东)新能源学院,山东 青岛 266580;2.中国石油天然气股份有限公司规划总院,北京 100083
摘要:
提高基于模块化多电平换流器(modular multilevel converter, MMC)的分布式储能系统(distributed energy storage systems, DESS)的能量利用率,解决储能子模块(energy sub-module, ESM)荷电状态(state of charge, SOC)均衡问题至关重要。针对现有的SOC均衡控制策略的不足,提出内外分层的快速SOC均衡控制策略。外层针对桥臂间或相间的SOC差异,通过改进MMC模型预测控制(model predictive predictive control, MPC),配合自适应均衡系数,快速调整功率差额。内层引入自适应虚拟电阻法,根据ESM的SOC情况确定主导ESM,自适应调节各单元的虚拟电阻,产生相应的电压梯度,结合MMC排序算法使ESM按照各自SOC进行功率分配,从而实现ESM的SOC快速均衡,提高DESS能量利用率。通过在Matlab/Simulink构建仿真模型,证明了所提控制策略的有效性和可行性。
关键词:  模块化多电平换流器  分布式储能系统  模型预测控制  荷电状态  虚拟电阻
DOI:10.19783/j.cnki.pspc.231432
分类号:
基金项目:国家自然科学基金项目资助(52277208)
Distributed energy storage system based on MMC and rapid SOC balancing control strategy
MA Wenzhong1, SUN Wei1, WANG Yusheng2, ZHANG Wenyan1, LI Hengshuo1, ZHU Yaheng1
1. Institute of New Energy, China University of Petroleum (East China), Qingdao 266580, China; 2. PetroChina Planning and Engineering Institute, Beijing 100083, China
Abstract:
To improve the energy utilization of distributed energy storage systems (DESS) based on modular multilevel converters (MMC), it is crucial to address the state of charge (SOC) balance of energy sub-modules (ESM). To address the limitations of existing SOC balance control strategies, a fast SOC balance control strategy based on internal and external hierarchical control is proposed. The outer layer aims to address the SOC differences between upper and lower arms or phase legs. To achieve this, this paper proposes improving the model predictive control (MPC) of MMC, in conjunction with adaptive equalization coefficients, to rapidly adjust power imbalances. The inner layer introduces an adaptive virtual resistance approach. Based on the SOC of ESM, the dominant ESM is determined, and the virtual resistance of each unit is adjusted adaptively to generate a corresponding voltage gradient. Combined with the MMC sorting algorithm, the ESM are allocated power according to their respective SOC, thereby achieving fast SOC balance and improving the energy utilization of DESS. A simulation model is built in Matlab/Simulink to demonstrate the effectiveness and feasibility of the proposed control strategy.
Key words:  modular multilevel converter  distributed energy storage system  model predictive control  state of charge  virtual resistor
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