多目标随机模型智能微电网联盟的最佳运行与透可再生能源资源与需求响应的透
Ali Abdolahzadeh1, Amir Hassannia2, Farhoud Mousavizadeh1
1Department of Electrical Engineering, Se.C., Islamic Azad University, Semnan, Iran.
Scientific reports
|July 1, 2025
概括
与可再生能源,需求响应和电动汽车 (EV) 协调的智能微电网可降低成本和排放. 合作显著提高了能源系统的运营效率和可持续性.
科学领域:
- 能源系统工程 能源系统工程
- 优化理论 优化理论
- 环境科学 环境科学
背景情况:
- 由于快速转型,现代能源系统面临成本效益,可靠性和可持续性的挑战.
- 整合可再生能源 (RES),需求响应 (DR) 和电动汽车 (EV) 对于未来的能源网络至关重要.
- 可再生发电和能源需求的不确定性需要先进的运营策略.
研究的目的:
- 为相互连接的智能微电网开发一种新的多目标随机优化模型.
- 同时尽量减少运营成本和环境排放,同时确保能源平衡.
- 通过需求侧措施,能源交易和车辆到电网 (V2G) 服务来加强能源管理.
主要方法:
- 开发了一种混合溶液方法,结合了e-约束方法和Benders分解.
- 该模型解决了可再生能源发电和能源需求的不确定性.
- 在一个由五个相互连接的智能微电网组成的联盟中进行了案例研究.
主要成果:
- 微电网的协调运行比独立运行带来了显著的好处.
- 总运营成本减少了高达22.7%的成本.
- 证明了高达75%的可再生能源利用率和31.1%的碳排放减少.
结论:
- 智能微电网联盟为减少对化石燃料的依赖和提高电网稳定性提供了可行的途径.
- 拟议的优化框架为可持续能源生态系统提供了实用和可扩展的解决方案.
- 电动汽车和DR战略的整合提高了系统的弹性和经济绩效.
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