谢敏;闫圆圆;刘明波;赵文猛;

• 1:华南理工大学电力学院

摘要(Abstract)：

向量序优化是一种新的解决多目标、超大计算量、复杂优化问题的有效方法。文中以煤耗量、购电费用、SO2排放量为优化目标,首次引入向量序优化理论求解含大规模随机风电的多目标机组组合问题。以含大型风电场及水、火、核、气、生物质能等复杂电源的某省级电力系统为例,将所提算法的优化结果与基于GAMS-BARON求解器的混合整数非线性规划法(mixed integer nonlinear programming,MINLP)进行对比分析,结果表明所提算法的求解速度大大优于传统的MINLP且优化结果偏差很小,验证了采用向量序优化方法求解含随机风电的大规模多目标机组组合问题的有效性。

关键词(KeyWords)： 随机风电;多目标机组组合;向量序优化;足够好解;场景法;BP神经网络

Abstract:

Keywords:

基金项目(Foundation): 国家重点基础研究发展计划项目(973项目)(2013CB228205);; 国家自然科学基金青年科学基金项目(50907023)~~

作者(Author): 谢敏;闫圆圆;刘明波;赵文猛;

Email:

DOI: 10.13335/j.1000-3673.pst.2015.01.033

参考文献(References)：

• [1]Wu H,Shahidehpour M.Stochastic SCUC solution with variable wind energy using constrained ordinal optimization[J].IEEE Transactions on Sustainable Energy,2014,5(2):379-388.
• [2]江岳文,陈冲,温步瀛.含风电场的电力系统机组组合问题随机模拟粒子群算法[J].电工技术学报,2009,24(6):129-137.Jiang Yuewen,Chen Chong,Wen Buying.Particle swarm research of stochastic simulation for unit commitment in wind farms integrated power system[J].Transactions of China Electrotechnical Society,2009,24(6):129-137(in Chinese).
• [3]张宁宇,高山,赵欣.一种考虑风电随机性的机组组合模型及其算法[J].电工技术学报,2013,28(5):22-29.Zhang Ningyu,Gao Shan,Zhao Xin.An unit commitment model and algorithm with randomness of wind power[J].Transactions of China Electrotechnical Society,2013,28(5):22-29(in Chinese).
• [4]孙元章,吴俊,李国杰,等.基于风速预测和随机规划的含风电电力系统动态经济调度[J].中国电机工程学报,2009,29(4):41-47.Sun Yuanzhang,Wu Jun,Li Guojie,et al.Dynamic economic dispatch considering wind power penetration based on wind speed forecasting and stochastic programming[J].Proceedings of the CSEE,2009,29(4):41-47(in Chinese).
• [5]姜欣,陈红坤,熊虎,等.基于预测误差不确定性的规模化间歇式电源机组组合研究[J].电网技术,2014,38(9):2456-2460.Jiang Xin,Chen Hongkun,Xiong Hu,et al.A prediction error uncertainty based day-ahead unit commitment of large-scale intermittent power generation[J].Power System Technology,2014,38(9):2456-2460(in Chinese).
• [6]雷宇,杨明,韩学山.基于场景分析的含风电系统机组组合的两阶段随机优化[J].电力系统保护与控制,2012,40(23):58-67.Lei Yu,Yang Ming,Han Xueshan.A two-stage stochastic optimization of unit commitment considering wind power based on scenario analysis[J].Power System Protection and Control,2012,40(23):58-67(in Chinese).
• [7]赵文猛,刘明波.求解含风电场随机机组组合问题的动态多削减多切割方法[J].电力系统自动化,2014,38(9):26-32.Zhao Wenmeng,Liu Mingbo.Multi-cut method with dynamic reduction for solving stochastic unit commitment problem with wind farm integration[J].Automation of Electric Power Systems,2014,38(9):26-32(in Chinese).
• [8]Loh W L.On Latin hypercube sampling[J].The Annals of Statistics,1996,24(5):2058-2080.
• [9]Heitsch H,Rmisch W.Scenario reduction algorithms in stochastic programming[J].Computational Optimization and Applications,2003,24(2-3):187-206.
• [10]Zhao Q C,Ho Y C,Jia Q S.Vector ordinal optimization[J].Journal of Optimization Theory and Applications,2005,125(2):259-274.
• [11]Li M,Vitanyi P.An introduction to Kolmogorov complexity and its applications[M].New York:Springer-Verlag New York Inc.,1997:47-49.
• [12]卢恩,王一,陈雨果,等.含复杂电源结构的电网调峰优化模型[J].电力系统自动化,2013,37(20):119-126.Lu En,Wang Yi,Chen Yuguo,et al.Optimization model for peak load regulation of power system with complex generation structure[J].Automation of Electric Power Systems,2013,37(20):119-126(in Chinese).
• [13]GAMS Development Corporation.GAMS,the solvers’manual[EB/OL].[2013-12-23].http://www.gams.com/solvers/.
• [14]董萍,徐良德,刘明波,等.多站点无功补偿装置的多目标协调控制[J].中国电机工程学报,2014,34(4):587-595.Dong Ping,Xu Liangde,Liu Mingbo,et al.Multi-objective coordinated control of reactive compensation devices among multiple substations[J].Proceedings of the CSEE,2014,34(4):587-595(in Chinese).
• [15]谢敏.电力市场环境下输电网规划建模及求解方法研究[D].武汉:华中科技大学,2005.