交流微电网的先进控制策略:基于ANN的混合型自适应PI控制器,具有垂落控制和虚拟阻抗技术
Sarra Adiche1, Mhamed Larbi1, Djilali Toumi1
1Department of Electrical Engineering, L2GEGI Laboratory, University of Tiaret, Tiaret, 14000, Algeria.
Scientific reports
|December 27, 2024
概括
使用基于人工神经网络 (ANN) 的自适应比例积分 (PI) 控制器的改进的电压控制策略提高了微电网 (MG) 的性能. 这种方法显著降低了总波扭曲 (THD),并改善了用于可再生能源整合的电力共享.
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:
- 分布式发电 (DG) 的微电网 (MG) 在电压控制和电源质量方面面临着挑战.
- 传统的控制器在动态条件下难以保持稳定性和波扭曲.
研究的目的:
- 为微电网提出一个改进的电压控制策略.
- 为了提高电压控制,功率共享,并减少总波扭曲 (THD).
- 为了在不同的负载和发电条件下提高系统的稳定性.
主要方法:
- 一个基于人工神经网络 (ANN) 的自适应比例积分 (PI) 控制器,结合掉落控制和虚拟阻抗技术 (VIT).
- VIT用于分离主动和反应功率,并减轻负功率相互作用.
- 在各种测试场景下进行模拟,以评估性能.
主要成果:
- 降低了75%的电压THD和69%的电流THD.
- 在上升时间 (60%) 和超越 (80%) 中实现了显著的减少.
- 保持电压和频率波动在国际标准内,电源质量低于IEEE-519标准.
结论:
- 拟议的基于ANN的自适应PI控制器与VIT为微电网电压控制提供了卓越的性能.
- 该战略有效地减少了THD,改善了权力共享,并提高了系统的稳定性和适应性.
- 这种方法已被验证,用于在不确定的条件下优化微电网运行.
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