电力系统自动化2024，Vol.48Issue(7)：235-247,13.DOI:10.7500/AEPS20230720018
数据中心集群灵活边界下电力系统分布鲁棒优化调度方法
Distributionally Robust Optimal Scheduling Method for Power System Under Flexibility Boundaries of Data Center Clusters
摘要
Abstract
The widespread integration of distributed resources and the volatility of uncontrollable resources such as wind and solar power pose significant challenges to the operation and control of power systems.This paper investigates optimal scheduling strategies for distributed cluster resources under the uncertainty of renewable energy,exploits the flexibility of various controllable resources,and enhances the utilization rate of centralized uncontrollable resources.To achieve the flexible control of distributed controllable resources,this paper first proposes a time-variant adjustable potential boundary computation method for aggregating data centers and photovoltaic-energy storage clusters,ensuring their aggregation optimality and decomposition feasibility.Furthermore,the ∞-Wasserstein fuzzy set is constructed based on historical data to capture the stochastic characteristics of wind power,providing reliable out-of-sample guarantee.Finally,an adaptive polyhedral approximation method is proposed to address the inherent infinite-dimensional solving challenge in the distributionally robust optimization problem.The two-stage distributionally robust scheduling model is transformed into a finite-dimensional problem to achieve the rapid solution.The effectiveness of the proposed method is verified based on the simulation on the modified IEEE-RTS 24-bus system.关键词
可调度域/风电消纳/分布鲁棒优化/近似求解Key words
schedulable region/wind power accommodation/distributionally robust optimization/approximation solution引用本文复制引用
张锞,王旭,杨宏坤,蒋传文..数据中心集群灵活边界下电力系统分布鲁棒优化调度方法[J].电力系统自动化,2024,48(7):235-247,13.基金项目
国家自然科学基金资助项目(52277110) （52277110）
内蒙古自治区"揭榜挂帅"项目(2022JBGS0043) （2022JBGS0043）
上海市"科技创新行动计划"软科学研究青年项目(23692119500). This work is supported by National Natural Science Foundation of China(No.52277110),Inner Mongolia Autonomous Region Plan(No.2022JBGS0043)and Shanghai Soft Science Research Youth Project of Science and Technology Innovation Action Plan(No.23692119500). （23692119500）
