摘要
针对源荷预测误差对主动配电网调度影响较大的问题,充分考虑源荷数据相关性,提出基于模型预测控制(MPC)的主动配电网多场景变时间尺度优化调度策略。在日前、日内优化阶段,采用藤Copula模型描述源荷相关性,结合场景生成与削减技术形成源荷出力场景,以多场景下配电网期望运行成本最小为目标建立优化模型,求解配电网中机组、储能、无功补偿装置等可调资源运行状态及出力情况;在实时优化阶段,采用MPC思想,以可调资源调整量最小为目标,提出场景相似度的概念以及自适应追踪最优轨迹的方法,得到基于滚动优化和反馈以及最优参考轨迹的实时调度。采用修改后的IEEE 33节点系统验证了所提优化策略的可行性。
Aiming at the problem that the source-load prediction error has large influence on the scheduling of active distribution network,a multi-scenario variable time scale optimal scheduling strategy of active distribution network is proposed based on MPC(Model Predictive Control),which fully considers the correlation of source-load data.In the day-ahead and intra-day optimization stage,the Vine Copula model is used to describe the source-load correlation,the source-load output scenarios are formed by combining the scenario generation and reduction technology.An optimization model with the minimum expected operation cost of distribution network under multiple scenarios as its objective is built,and the operation status and output of adjustable resources,such as units,energy storage and reactive power compensation devices in distribution network are solved.In the real-time optimization stage,the idea of MPC is adopted,aiming at the objective of minimum the adjustable resource adjustment,the concept of scenario similarity and a method of adaptive tracking optimal trajectory are proposed,and the real-time scheduling based on rolling optimization and feedback and optimal reference trajectory is obtained.The modified IEEE 33-bus system is used to verify the feasibility of the proposed optimization strategy.
作者
刘自发
张婷
王岩
LIU Zifa;ZHANG Ting;WANG Yan(School of Electrical and Electronic Engineering,North China Electric Power University,Beijing 102206,China;Department of Electrical Engineering,North China Electric Power University(Baoding),Baoding 071003,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2022年第4期121-128,共8页
Electric Power Automation Equipment
基金
国家重点研发计划项目(2016YFB0900105)。