在微电网中,在社会和需求动态下使用量子经典混合算法进行行为意识的能源管理
Liu Minghong1, Fu Gaoshan2, Wang Pengchao1
1State Grid Xinjiang Economic Research Institute, Ürümqi, Xinjiang, China.
Scientific reports
|July 2, 2025
概括
本研究介绍了微电网能源管理的混合量子-经典优化框架,使用行为建模来增强需求响应的弹性和灵活性. 这种新的方法提高了复杂能源网络的效率和可靠性.
科学领域:
- 能源系统工程 能源系统工程
- 计算优化计算优化
- 行为经济学是一种行为经济学.
背景情况:
- 现代微电网面临的复杂性是由于不可预测的需求,分布式可再生能源和用户行为.
- 现有的优化方法与这些系统的动态和随机性质作斗争.
研究的目的:
- 开发一个混合量子-经典优化框架,用于微电网的需求侧能源管理.
- 整合社会认知理论中的行为建模原则,以增强微电网的弹性和灵活性.
- 支持分布式决策和适应性前性消费者行为.
主要方法:
- 一个混合框架,将量子和NSGA-III算法结合起来,用于多目标优化.
- 将社会认知理论原则 (模仿,自我效能,社会强化) 纳入优化模型.
- 在一个点对点微型电网网络案例研究中测试框架.
主要成果:
- 在提高能源效率和减少峰值需求方面已证明有效.
- 提高了微电网网络的运行弹性.
- 与混合整数编程等传统方法相比,量子启发模型显示出更高的可扩展性和稳定性.
结论:
- 混合量子-经典方法与行为建模为智能微电网控制提供了强大的工具.
- 将量子启发的优化与行为科学相结合,推动了对社会有反应性的能源管理.
- 这一框架有效地处理复杂微电网中的成本,可靠性和需求响应之间的权衡.
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