针对新能源大规模集中和分布式并网接入各级电网带来的调控灵活资源不足、运行不确定性高、海量控制对象以及多主体信息隐私等技术挑战，进行了“电力系统能量管理与运行控制”理论和方法的研究和系统开发，并开展了工程实践。

本项目扩展了配电网优化模型的精确凸松弛方法，提出了配电网分析与运行优化的高效算法体系；构建了分布式资源集群控制架构及其拟二阶收敛的分布式算法，发明了递归反馈优化方法解决模型不完备的控制问题，实现大规模分布式电源集群敏捷、精准控制；提出多参数空间投影分解算法，实现输配网多控制中心协同安全评估与优化调度。建立了主动配电网能量管理与运行调控的理论体系及其关键技术，研制出配电网能量管理与分布式资源集群控制系统。主持研制了配电网能量管理与集群控制、可靠性综合规划等系列软件系统，得到了推广应用。成果获得2020年中国电力科学技术进步一等奖(排1)和2022年日内瓦发明展金奖(排1)。

解决了从常规发电到可再生能源发电、从单控制区域到多控制区域、从常规电力调度到电网-城市供热系统的多能协调调度、从省级电网到大区电网应用中的系列关键技术及其理论难题，利用多种能源的时空互补性，调控对象从"纯电"变革为"多能"，调控模式从"确定性调控"变革为"风险量化的概率调控"，研发了高比例新能源电力系统多能协同调控系统。成果已应用于多个省级及以上电网，出版专著《可再生能源集群控制与优化调度》。成果获得2021年中国电工技术学会技术发明一等奖 (排1)、2020年教育部自然科学一等奖（排2）和2022年吉林省科技进步一等奖（排2）。

As large scale wind/solar farms and massive distributed renewables integrated into power grid with different voltage levels, the operation of power systems meets significant technical challenges including insufficient regulation capability, high uncertainties, huge mount of controllable entities and information privacy concerns. This research project aims to develop new energy management & control architecture and theory to accommodate these challenges and conduct pilot engineering projects.

Optimal power flow is the basic model of power system scheduling problem, it is a non-convex optimization problem which is hard to solve. In this dissertation, a feasible solution recovery algorithm for convex relaxed OPF model is proposed to solve the problem that the convex relaxation is infeasible for mesh networks. The algorithm not only guarantees convergence, but can also obtain a feasible solution that satisfies the KKT conditions of the original OPF problem.

We propose a feasible solution recovery algorithm for convex relaxed OPF model of mesh networks. Based on the relaxation& recovery techniques, the efficient algorithms for distribution network analysis and optimization are developed. Two distributed algorithms with quasi-second order convergence are presented for coordinating multiple renewable clusters, and a data-driven feedback-based optimization method is proposed to tackle the issues caused by model mismatch and insufficient measurements in renewables clusters. A nested decentralized method to solve multilevel coordinated optimization problems for the integrated transmission and distribution networks. Based on these innovations, a active distribution network energy management and cluster control system is developed and deployed in many cities. This achievement is awarded the first class prize of Electric Power Science and Technology Progress of China（2020） and gold medal of International Exhibition of Inventions of Geneva（2022）.

The comprehensive studied have been conducted on the operation of conventional generation and renewable generation, the coordination of multiple control area, synergistic optimization of electric power and heat supply systems. In this research, we developed an energy management and operation control system for the multi-vector energy systems, which can coordinate the electric power networks, district heat networks and wind/solar power farms. To address the issue caused by the variable renewables, the stochastic unit commitment, stochastic economic dispatch considering optimal curtailment schedule as well their analytical solutions are proposed. This control system has been deployed in numerous provincial power grids. Based on these achievement, a monograph ”renewable energy cluster control and optimal dispatch” is published. This work is awarded the first rank prize of China Electrotechnical Society Technology Innovation(2021), the first rank prize of Natural Science Award of the Ministry of Education(2020) and the first class prize of Electric Power Science and Technology Progress of Jilin Province(2022).