一种基于草原犬的新型元启发式优化算法,用于改进混合微电网的控制,更好的过渡响应和电力质量提升
Gagan Kumar Sahoo1, Subhashree Choudhury2, Rajkumar Singh Rathore3
1Department of EE, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar 751030, India.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
一个新的草原狗优化 (PDO) 算法有效调整微电网中的混合可再生能源系统 (HRES) 的控制器. 这种方法提高了电源质量和系统稳定性在干扰期间.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 可再生能源系统可再生能源系统
背景情况:
- 越来越多的电力需求需要可靠的电网.
- 混合可再生能源系统 (HRES) 提供更高的可靠性和减少微电网 (MG) 的损失.
- 有效的控制器对于管理HRES集成和减轻电力质量 (PQ) 问题至关重要.
研究的目的:
- 提出一种新的草原狗优化 (PDO) 算法,用于调整基于光伏,FC和电池的HRES中的比例积分 (PI) 控制器.
- 评估PDO算法在补偿负载需求和减轻MG系统中的PQ问题方面的有效性.
- 为了证明PDO算法的优越性与现有的优化技术相比.
主要方法:
- 为基于光伏,电流和电池的HRES开发一个MATLAB/Simulink模型.
- 实施草原狗优化 (PDO) 算法来调整PI控制器参数.
- 在各种故意的PQ干扰下测试MG系统 (膨胀,不平衡负载,振荡过渡,隙).
- 使用蜂群优化 (BCO),热交换优化和PI技术进行比较分析.
主要成果:
- PDO算法实现了最佳的PI控制器收益,以有效的负载补偿和PQ缓解.
- 模拟结果显示,总波扭曲 (THD) 的最小化得到了显著改善.
- 观察到增强了主动和反应功率的控制,提高了功率因子,并减少了电压偏差.
- 在PQ故障期间保持了稳定的终端电压,直流连接电压,电网电压和电网电流.
结论:
- 拟议的PDO算法对于优化基于HRES的MGs中的PI控制器是高效和强大的.
- PDO显著提高了整体系统运行,电力质量和稳定性.
- 该PDO方法显示了在微电网应用中实时实施的强大潜力.
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