电力系统自动化2025，Vol.49Issue(22)：123-134,12.DOI:10.7500/AEPS20240427005
基于冗余约束快速辨识的电力系统前瞻调度鲁棒决策方法
Robust Decision-making Method for Look-ahead Dispatch in Power System Based on Fast Identification of Redundant Constraints
摘要
Abstract
To address the electric power balance issues in systems caused by intraday power deviations of renewable energies,power dispatch departments require minute-level revisions to the day-ahead plans from a look-ahead perspective.Therefore,a robust decision-making method for the look-ahead dispatch in power system is proposed based on the fast identification of redundant constraints.The method improves the renewable energy accommodation rate and supply capacity of the power system in extreme operation scenarios while ensuring efficient solving in a short time.First,in the look-ahead dispatch decision-making mode,a two-stage optimization model is constructed considering the uncertainty of wind and photovoltaic power,along with the coordinated control of multiple resources such as hydro,thermal,storage,and tie-lines.The first stage considers the economy and safety of the system,while the second stage considers the renewable energy accommodation and power supply guarantee.Furthermore,considering the model complexity added by the uncertainty of renewable energy,an identification and reduction method for redundant constraints based on graph convolution neural network and long short-term memory network is proposed,followed by a robust optimization solution for the reduced look-ahead dispatch model using column and constraint generation algorithm.Finally,the effectiveness of the proposed model for the fast identification of redundant constraints is validated through numerical results in the IEEE 118-bus system,and the proposed robust decision-making method can efficiently solve look-ahead dispatch strategies in various types of scenarios.关键词
新能源/决策/极端运行场景/前瞻调度/冗余约束/图卷积神经网络/长短期记忆网络/鲁棒优化Key words
renewable energy/decision-making/extreme operation scenario/look-ahead dispatch/redundant constraint/graph convolution neural network/long short-term memory network/robust optimization引用本文复制引用
王麒宁,陈思远,徐箭,陈亦平,颜融,郭岩..基于冗余约束快速辨识的电力系统前瞻调度鲁棒决策方法[J].电力系统自动化,2025,49(22):123-134,12.基金项目
国家重点研发计划资助项目(2022YFB2403500). This work is supported by National Key R&D Program of China(No.2022YFB2403500). （2022YFB2403500）
