在不确定性下的电力和水系统的综合最佳运行:可调节的强大优化方法
Gal Perelman1, Mashor Housh2, Aviad Navon3
1Faculty of Civil and Environmental Engineering, Technion-Israel Institute of Technology, Haifa 3200003, Israel.
Water research
|January 11, 2026
概括
本研究将水和电力系统集成使用强大的优化 (RO) 和可调的强大的优化 (ARO) 来提高不确定性下的可靠性. 这种新的方法显著提高了限制满意度,成本增加最小,优于确定性方法.
科学领域:
- 工程 工程师 工程师 工程师
- 优化理论 优化理论
- 可持续的基础设施可持续的基础设施
背景情况:
- 水和电力系统相互依赖,但通常是单独优化,导致效率低下.
- 需求,负载和可再生能源的不确定性使综合系统分析复杂化.
- 现有的优化方法与合,不确定的系统的复杂性作斗争.
研究的目的:
- 开发和应用强大的优化 (RO) 和可调节的强大的优化 (ARO) 用于水和电力系统的整合日前调度.
- 在RO和ARO模型中引入一种新的配方,以消除不确定的平等约束.
- 为了提高相互依赖的基础设施运营在不确定性下的效率,可靠性和稳定性.
主要方法:
- 提出了一种新的数学公式,通过分解决策向量来系统地消除不确定的平等约束.
- 将RO和ARO框架应用于运行和发电机调度的综合调度.
- 利用两个案例研究来评估成本最佳性和稳定性之间的帕雷托权衡.
主要成果:
- 实现了强度的大幅提高,限制满足率从<25%增加到>99%,运营成本仅增加了2-5%.
- 证明了ARO与RO在实现较低的运营成本与相似的稳定性水平方面的优势.
- 展示了合模型能够使用实时信息实现适应性决策的能力.
结论:
- 拟议的RO和ARO方法为优化相互依存的水和电力系统提供了强大而适应性的方法.
- 这种方法提高了运营可靠性,并支持可持续的基础设施发展.
- 这种新的限制消除技术有助于在复杂系统中实际实施先进的优化技术.
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