使用电动鱼食优化算法对联网光伏和风力轮混合系统进行最佳控制和优化.
Saad A Mohamed Abdelwahab1, Ali M El-Rifaie2, Hossam Youssef Hegazy3
1Electrical Department, Faculty of Technology and Education, Suez University, Suez 43221, Egypt.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
这项研究优化了使用电动食优化 (EEFO) 的混合风能和光伏能源系统,以获得可靠,无排放的电力. EEFO确保高效的电网集成和稳定的发电量,推进可持续的能源解决方案.
科学领域:
- 可再生能源系统可再生能源系统
- 电气工程 电气工程
- 优化技术 优化技术
背景情况:
- 风能和光伏 (PV) 等可再生能源是间歇性的,这给稳定的发电带来了挑战.
- 综合多种可再生能源的混合系统对于可靠,无排放的能源至关重要.
- 解决间歇性需要先进的控制和优化,以实现无电网集成.
研究的目的:
- 探索混合风能-光伏能源系统,以获得可靠,无排放的电力.
- 使用先进的算法优化电力调节,电网集成和负载管理.
- 评估电动鱼食优化 (EEFO) 在混合系统操作中的有效性.
主要方法:
- 利用粒子群优化 (PSO) 和电捕食优化 (EEFO) 进行系统优化.
- 在 MATLAB/SIMULINK 中使用数学建模和模拟技术.
- 通过各种操作场景和电网连接系统模拟来评估优化策略.
主要成果:
- EEFO有效地优化了连接到电网的风能-光伏混合系统的运行.
- 建议的优化策略准确且快速地补偿相关负载.
- 该系统展示了有效控制能源供应,以保持所需的负载功率.
结论:
- 带有EEFO的混合风能-光伏系统为电力需求提供了可持续和可靠的解决方案.
- 优化策略提高系统性能,最大限度地提高能源产量,并改善电网集成.
- 这种方法有助于推动清洁能源技术和可持续能源系统的发展.
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