数据驱动的综合能源系统鲁棒调度控制方法研究

There are a large number of uncertainties in the integrated energy system (IES), such as the outputs of wind/ solar generation on the generation side, the energy demand on the load side, and the energy supply topology on the network side, which challenges the secure and economic operation of the IES. Flexible dispatch strategy is one of the most effective ways to improve the performance of the IES against operational uncertainties. This project focuses on the dispatch strategy decision-making problem of the IES in the uncertain environment, and combines the data-driven approach and robust optimization theory. Considering the multiple time-scale feature of the dispatch problem of the IES and the regional characteristics of the IES, this project is carried out in two dimensions, which are temporal, including day-ahead and real-time, and spatial, including regional and multi-region. Specifically, it proposes day-ahead/real-time dispatch strategy of IES based on data-driven robust optimization as well as distributed computation methods for the data-driven robust dispatch of multi-region IES. This project will provide technical support and guarantee for the reliable and economical operation of the IES in an uncertain environment.

综合能源系统中存在大量不确定因素，如源侧风光发电、负荷侧用户用能需求及网侧供能拓扑等，为其安全经济运行带来了严峻挑战。灵活的调度控制策略是提升综合能源系统对上述不确定性应对能力的有效手段之一。本项目围绕不确定环境下综合能源系统调度控制决策问题，基于数据驱动方法与鲁棒优化理论，结合综合能源系统调度控制问题多时间尺度及综合能源系统区域性特点，在时间（日前-实时）、空间（单区域-多区域）两个维度开展研究，提出基于数据驱动鲁棒优化理论的综合能源系统日前/实时调度控制决策方法和数据驱动的多区域互联综合能源系统多时间尺度鲁棒调度控制分布式决策方法。该研究将为不确定环境下综合能源系统安全经济运行提供技术支持和保障。

综合能源系统中存在大量不确定因素，如源侧风光发电、负荷侧用户用能需求及网侧供能拓扑等，为其安全经济运行带来了严峻挑战。灵活的调度控制策略是提升综合能源系统对上述不确定性应对能力的有效手段之一。本项目围绕不确定环境下综合能源系统调度控制决策问题，基于数据驱动方法与鲁棒优化理论，结合综合能源系统调度控制问题多时间尺度及综合能源系统区域性特点，在时间（日前-实时）、空间（单区域-多区域）两个维度开展研究，提出了基于数据驱动鲁棒优化理论的综合能源系统日前/实时调度控制决策方法和数据驱动的多区域互联综合能源系统多时间尺度鲁棒调度控制分布式决策方法。该研究将为不确定环境下综合能源系统安全经济运行提供技术支持和保障。