Protected: MODEL PREDICTIVE OPTIMAL CONTROL STRATEGY FOR MODULAR MULTILEVEL HYBRID CONVERTER BATTERY ENERGY STORAGE SYSTEM
Publication Date : 28/05/2023
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Abstract: Based on MMHC-BESS and combining MPC algorithm with duty cycle modulation idea, a model predictive optimal control strategy is proposed, which can effectively reduce the computational burden of the system. The control strategy uses the MPC algorithm to realize the power control, deduces the optimal output voltage through the discrete model of the converter, and uses the carrier phase shift modulation method to realize the switching signal output. At the same time, considering the voltage imbalance of the power grid, the MPC algorithm is used to suppress the negative sequence current and power fluctuation, which has a good ability of redundant fault-tolerant operation. Finally, the effectiveness and feasibility of the proposed control method are verified by the simulation model. Key words: model predictive control, optimal control, battery energy storage system, MMHC-BESS, redundant fault tolerant control 摘要: 基于MMHC-BESS,将MPC算法与占空比调制思想结合,提出一种可有效减小系统计算负担的模型预测优化控制策略。控制策略利用MPC算法实现功率控制,通过变换器的离散模型反推出最优输出电压,采用载波移相调制方法实现开关信号输出。同时考虑电网电压不平衡状况,利用MPC算法对负序电流及功率波动进行抑制,具备较好的冗余容错运行能力。最后通过仿真模型验证了所提控制方法的有效性和可行性。 关键词: 模型预测控制, 优化控制, 电池储能系统, MMHC-BESS, 冗余容错控制
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