根据增强的粒子群集优化算法,基于电动汽车的微电网的战略调度
Saeed Abdollahi Khou1, Javad Olamaei2, Mohammad Hassan Hosseini1
1Department of Power Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
Scientific reports
|December 27, 2024
概括
本研究介绍了电动汽车微电网的增强优化算法,提高了经济效率和环境可持续性. 与现有算法相比,新方法显著降低了系统成本.
科学领域:
- 电气工程 电气工程
- 环境科学 环境科学
- 优化理论 优化理论
背景情况:
- 微电网面临着稳定性的挑战,原因是可再生能源的变化和不可预测的需求.
- 作为动态负载的电动汽车 (EV) 给微电网管理带来了进一步的复杂性.
- 现有的粒子群优化算法 (PSOA) 与局部优化作斗争,限制了它们的有效性.
研究的目的:
- 为集成电动汽车的微电网开发一个双重目标的优化框架.
- 提高微电网运营中的经济效率和环境可持续性.
- 在复杂的微电网场景中解决传统公用事业服务计划的局限性.
主要方法:
- 在两人零和游戏 (TPZSG) 框架内采用线性权重策略.
- 开发了一种增强的自适应模拟回火粒子群优化算法 (ASA-PSOA).
- 对电动汽车实施了系统的充电和放电策略.
主要成果:
- 与标准PSOA相比,ASA-PSOA将总系统成本降低了11.1%.
- 多功能权重策略有效地减轻了不确定性,优化了可再生资源的利用.
- 系统的电动汽车充电/放电降低了运营和环境成本.
结论:
- 增强的ASA-PSOA显著提高了微电网的经济和生态效率.
- 拟议的框架为使用可再生能源和电动汽车的微电网管理提供了一个强大的解决方案.
- 优化电动汽车集成和先进的算法是可持续微电网运行的关键.
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