含多区域差异特性新能源的多随机变量联合机会约束改进求解方法  

An Improved Solution Method for Multi-area Systems With Different Characteristics of Renewable Energy Based on Multiple Stochastic Variables Joint Chance Constraints

作　　者：黎静华[1] 宋骏凤 林立成 LI Jinghua;SONG Junfeng;LIN Licheng(Guangxi Key Laboratory of Power System Optimization and Energy-saving Technology(Guangxi Unversity),Nanning 530004,Guangxi Zhuang Autonomous Region,China)

机构地区：[1]广西电力系统最优化与节能技术重点实验室(广西大学),广西壮族自治区南宁市530004

出　　处：《中国电机工程学报》2025年第5期1767-1779,I0012,共14页PROCEEDINGS OF THE CHINESE SOCIETY FOR ELECTRICAL ENGINEERING

基　　金：国家自然科学基金项目(51977042)。

摘　　要：随着新能源电力系统的建设与发展,机组组合面临多区域、特性迥异新能源的多重不确定性挑战。机会约束是考虑随机因素最具代表性的模型之一,多区域差异特性新能源的机组组合模型采用多随机变量联合机会约束模型,准确求解涉及到多个概率分布函数的卷积运算,计算复杂。因此,现有方法往往忽略新能源分布的差异性,将新能源按照服从相同概率分布进行简单处理,导致调度结果与实际运行偏差较大。为此,提出一种简化联合机会约束的改进求解方法,通过添加辅助变量,将联合机会约束中含多个随机变量线性组合的不等式形式转换成含单个随机变量的不等式形式,在保留新能源概率分布特性差异的同时,避免了复杂的卷积运算。在处理单个变量的联合机会约束到确定性约束转化方面,通过优化模型,确定满足置信度的最小概率点(多维p-有效点),将多个概率分布函数的积分运算转换为常规的整数规划问题求解,避免了多重积分的复杂运算。通过3区域117节点和196节点算例,从旋转备用配置、新能源弃电率、运行成本和计算时间等方面,验证所提方法的优越性。With the construction and development of new energy power systems,the unit commitment is facing multiple uncertain challenges of multi-regions and new energy with different characteristics.Chance constraint is one of the most representative models considering stochastic factors.The unit commitment model for multi-area systems with different stochastic characteristics of new energy uses joint chance constraint model of multiple stochastic variables,and the accurate solution requires the convolution operation of multiple probability distribution functions,which is computationally complex.Therefore,existing methods often ignore the differences in the distribution of new energy and simply deal with them according to the same probability distribution,leading to a large deviation between the scheduling results and the actual situation.In this paper,an improved solution method based on simplified joint chance constraint is proposed.In the joint chance constraint,inequality forms with linear combination of multiple stochastic variables are transformed into inequality forms with single stochastic variable by introducing auxiliary variables.This approach avoids complex convolution operation and preserves the difference of distinct probability distribution characteristics of new energy.By optimizing the model to obtain the minimum probability point(multi-dimensional p-efficient point)that satisfies the confidence level,it achieves the conversion from joint chance constraint to deterministic constraint of single stochastic variable.The complex integral operation of multiple probability distribution functions is converted into a conventional integer programming problem.Finally,the superiority of the proposed method is verified through the 3-regional 117-node and 196-node system test cases in terms of spinning reserve allocation,curtailment rate of new energy power running cost and calculation time.

关 键 词：新能源电力系统 多区域系统 多重不确定性 联合机会约束 多随机变量线性组合 多维p-有效点 

分 类 号：TM71[电气工程—电力系统及自动化]