一个优化的需求响应框架,以提高风力发电和电动汽车引发的不确定性下的电力系统可靠性
Hadi Pakbin1, Amin Karimi2, Mohammad Naseh Hassanzadeh1
1Department of Electrical Engineering, Islamic Azad University, Sanandaj, Iran.
Scientific reports
|July 2, 2025
概括
本研究介绍了一种优化需求响应 (DR) 框架,用于管理风能和电动汽车 (EV) 集成. 这种新的方法通过调整DR激励措施以适应实时电网条件来提高电力系统的可靠性和成本效益.
科学领域:
- 电力系统工程 电力系统工程
- 整合可再生能源的整合
- 智能电网是一种智能电网.
背景情况:
- 风能和电动汽车 (EV) 的整合为电力系统带来了重大运营挑战,因为其固有的变化和复杂的负载动态.
- 现有的需求响应 (DR) 策略往往缺乏适应能力,无法有效管理可再生发电和灵活的电动汽车充电模式带来的不确定性.
研究的目的:
- 开发和验证一个新的,优化的需求响应 (DR) 框架,以提高电力系统的可靠性,在风能透率高和广泛采用电动汽车 (EV) 的背景下.
- 根据实时风力发电波动,需求弹性和电动汽车充电行为来动态调整DR激励措施,以提高电网稳定性和成本效益.
主要方法:
- 开发了一种使用统计平均值标准偏差关系的实时不确定性模型,以量化风力发电波动.
- 一个优化的DR框架被设计为每小时动态分配激励措施,考虑到风力波动,需求弹性和电动汽车收费模式.
- 使用基于幸福感的概率方法评估系统可靠性,将系统状态分为健康 (P(H),边际 (P(M) 和风险 (P(R)).
主要成果:
- 拟议的框架提高了健康系统状态概率 (P(H)) 从95.1% (没有DR) 和97.2% (非优化DR) 到97.44%.
- 未供应的能源从52.230兆瓦时减少到51.900兆瓦时,这表明电网可靠性得到了提高.
- 需求响应激励成本降低了5.6%,证明了成本效益的提高.
结论:
- 不确定性驱动的DR优化和概率福利评估的综合方法为管理可再生能源变化提供了实际的解决方案.
- 该框架有效地提高了电力系统的弹性和成本效益,在高可再生能源透率和显著的电动汽车集成的电网中.
- 调整DR激励措施以适应实时电网条件,特别是风力波动,是先前研究中未涉及的关键创新.
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