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Energy management and intelligent power control of a stand-alone wind energy conversion system with battery storage
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-07-21 , DOI: 10.1002/2050-7038.13003
Fatima Ez‐zahra Lamzouri 1 , El‐Mahjoub Boufounas 1 , Aumeur El Amrani 1
Affiliation  

This present paper considers a novel strategy for energy management and intelligent power control of a stand-alone electric generation system (EGS). The considered system consists of a wind energy conversion system, which contains a wind turbine with permanent magnet synchronous generator associated with a battery storage system and a direct current (DC) load. According to different climatic changes, load variations, and battery state of charge, the considered EGS is studied as a switched and uncertain nonlinear system. The main control objectives are, first, to regulate the wind power generation to satisfy the required power and second, to maintain the battery state of charge within a certain limits to extend its life cycle. Thus, a strategy of energy management is proposed based on different modes of system operation. Furthermore, a neural network-based integral sliding mode controller (NN-ISMC) is developed, as a robust and intelligent control method, to satisfy the reference power of each operation areas and to improve the robustness and the stability of such stand-alone system under high perturbations and external disturbances. The analytical stability of the proposed approach is demonstrated and assured using Lyapunov function method. In addition, the simulation results, realized using Matlab software, show that the suggested NN-ISMC control strategy ensures faster transient response and smaller steady-state error performances, compared to the other presented methods.

中文翻译:

具有电池存储的独立风能转换系统的能量管理和智能功率控制

本文考虑了一种用于独立发电系统 (EGS) 的能源管理和智能功率控制的新策略。所考虑的系统由一个风能转换系统组成,其中包含一个风力涡轮机,带有与电池存储系统和直流 (DC) 负载相关联的永磁同步发电机。根据不同的气候变化、负载变化和电池荷电状态,将所考虑的EGS作为切换和不确定的非线性系统进行研究。主要的控制目标是,一是调节风力发电量以满足所需功率,二是将电池的荷电状态保持在一定限度内,以延长其生命周期。因此,提出了一种基于不同系统运行模式的能源管理策略。此外,开发了一种基于神经网络的积分滑模控制器(NN-ISMC),作为一种鲁棒和智能的控制方法,以满足每个操作区域的参考功率,提高这种独立系统在高强度下的鲁棒性和稳定性。扰动和外部干扰。使用李雅普诺夫函数方法证明并保证了所提出方法的分析稳定性。此外,使用 Matlab 软件实现的仿真结果表明,与其他提出的方法相比,建议的 NN-ISMC 控制策略可确保更快的瞬态响应和更小的稳态误差性能。满足各作业区的参考功率,提高单机系统在高扰动和外部扰动下的鲁棒性和稳定性。使用李雅普诺夫函数方法证明并保证了所提出方法的分析稳定性。此外,使用 Matlab 软件实现的仿真结果表明,与其他提出的方法相比,建议的 NN-ISMC 控制策略可确保更快的瞬态响应和更小的稳态误差性能。满足各作业区的参考功率,提高单机系统在高扰动和外部扰动下的鲁棒性和稳定性。使用李雅普诺夫函数方法证明并保证了所提出方法的分析稳定性。此外,使用 Matlab 软件实现的仿真结果表明,与其他提出的方法相比,建议的 NN-ISMC 控制策略可确保更快的瞬态响应和更小的稳态误差性能。
更新日期:2021-09-16
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