| 引用本文: | 刘与铮,丁涛,肖杨,代江,田年杰,赵倩,唐翀,禤培正,程兰芬.基于拉格朗日松弛及子问题解耦动态规划的周机组组合快速求解方法[J].电力自动化设备,2025,45(6):173-181,190. |
| LIU Yuzheng,DING Tao,XIAO Yang,DAI Jiang,TIAN Nianjie,ZHAO Qian,TANG Chong,XUAN Peizheng,CHENG Lanfen.Fast solving method for weekly unit commitment based on Lagrangian relaxation and subproblem decoupling dynamic programming[J].Electric Power Automation Equipment,2025,45(6):173-181,190. |
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| 基于拉格朗日松弛及子问题解耦动态规划的周机组组合快速求解方法 |
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刘与铮1, 丁涛1, 肖杨1, 代江2, 田年杰2, 赵倩2, 唐翀3, 禤培正3, 程兰芬3
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1.西安交通大学 电气工程学院 电力设备电气绝缘国家重点实验室，陕西 西安 710049;2.贵州电网有限责任公司电力调度控制中心，贵州 贵阳 550005;3.南方电网科学研究院有限责任公司 直流输电技术全国重点实验室，广东 广州 510663
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| 摘要: |
| 当前逐渐增大的电力系统规模和逐渐拓展的模拟周期使得快速求解机组组合问题面临巨大挑战。提出一种基于拉格朗日松弛和子问题解耦动态规划的周机组组合快速求解方法，以提高周机组组合计算效率。引入拉格朗日对偶乘子对原始问题中的耦合约束进行松弛，并分解得到若干单机组子问题；构建单机组子问题的状态转移图及状态转移成本，利用动态规划算法计算单机组最优状态转移，以获得单机组子问题最优解；对问题进行迭代求解直至收敛，从而快速得到周机组组合结果。将所提方法应用于IEEE 118节点系统、IEEE 300节点系统和贵州电网，验证其优异的计算效率。 |
| 关键词: 拉格朗日松弛 动态规划 机组组合 次梯度优化算法 分解协调 |
| DOI：10.16081/j.epae.202503009 |
| 分类号:TM73 |
| 基金项目:中国南方电网有限责任公司科技项目(电力市场环境下考虑安全约束的优化调度关键技术(课题4))(GZKJXM20222442) |
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| Fast solving method for weekly unit commitment based on Lagrangian relaxation and subproblem decoupling dynamic programming |
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LIU Yuzheng1, DING Tao1, XIAO Yang1, DAI Jiang2, TIAN Nianjie2, ZHAO Qian2, TANG Chong3, XUAN Peizheng3, CHENG Lanfen3
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1.State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China;2.Power Dispatching and Control Center of Guizhou Power Grid Co.,Ltd.,Guiyang 550005, China;3.State Key Laboratory of HVDC, Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China
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| Abstract: |
| At present, the gradually increasing scale of power system and the gradually expanding simulation cycle have brought big challenge to the rapid solution of unit commitment problems. A fast solving method for weekly unit commitment based on Lagrangian relaxation and subproblem decoupling dynamic programming is proposed to improve the calculation efficiency of weekly unit commitment. The Lagrangian dual multiplier is introduced to relax and decompose the coupling constraints of original problem into several single unit sub-problems. The state transition graph and state transition cost for single unit sub-problems are constructed, and the dynamic programming algorithm is used to calculate the optimal state transition of single unit and obtain the optimal solution for each unit sub-problem. The problems are iteratively solved until the convergence, thus the weekly unit commitment results are rapidly obtained. The proposed method is applied in IEEE 118-bus system, IEEE 300-bus system and Guizhou Power Grid, and its excellent calculation efficiency is demonstrated. |
| Key words: Lagrangian relaxation dynamic programming unit commitment subgradient optimization algorithm decomposition-coordination |
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