中国电力 ›› 2024, Vol. 57 ›› Issue (10): 166-171.DOI: 10.11930/j.issn.1004-9649.202311067

• 应对非常规安全风险的新型电力系统规划、运行与控制关键技术 • 上一篇    下一篇

基于改进凸松弛的新能源电网概率最优潮流快速计算方法

崔伟1(), 柴龙越2(), 王聪1, 王炜1, 汪莹1, 杨仑2()   

  1. 1. 国网电网有限公司西北分部,陕西 西安 710000
    2. 西安交通大学 自动化科学与工程学院,陕西 西安 710049
  • 收稿日期:2023-11-15 出版日期:2024-10-28 发布日期:2024-10-25
  • 作者简介:崔 伟(1987—),男,工程师,硕士,从事电力系统及其自动化研究,E-mail:1479377442@qq.com
    柴龙越(2001—),女,硕士研究生,从事电力系统优化运行研究,E-mail:chailongyue@163.com
    杨仑(1992—),男,通信作者,博士,助理教授,从事电力系统优化运行研究,E-mail:yanglun2019@gmail.com
  • 基金资助:
    国家电网公司西北分部科技项目(SGTYHT/21-JS-226);国家重点研发计划资助项目(2022YFA1004600)。

Fast Calculation Method of Probabilistic Optimal Power Flow for Renewable Dominated Power Grid Based on Improved Convex Relaxation

Wei CUI1(), Longyue CHAI2(), Cong WANG1, Wei WANG1, Ying WANG1, Lun YANG2()   

  1. 1. Northwest Branch of State Grid Corporation of China, Xi'an 710000
    2. School of Automation Science and Engineering, Xi'an Jiaotong University, Xi'an 710049
  • Received:2023-11-15 Online:2024-10-28 Published:2024-10-25
  • Supported by:
    This work is supported by Northwest Branch of SGCC (No.SGTYHT/21-JS-226) and the National Key Research and Development Program of China (No.2022YFA1004600).

摘要:

现有概率最优潮流计算侧重于概率计算方法的设计和改进,难以从本质上提高概率最优潮流的计算效率。为此,以交直流新能源电网为研究对象,考虑风电、光伏发电的不确定性,建立交直流互联新能源电网概率最优潮流模型。首先,提出一种改进凸松弛技术处理非线性非凸潮流方法,将其转化为凸规划形式下的概率最优潮流模型;其次,利用Nataf变换处理非正态分布随机变量间的相关性,进而采用结合拉丁超立方采样技术的蒙特卡罗模拟法(monte carlo simulation,MCS)进行求解以降低MCS的计算量;最后,通过改进的IEEE 39节点、118节点以及500节点系统验证所提方法的有效性。

关键词: 概率最优潮流, 凸松弛, 不确定性, 拉丁超立方

Abstract:

The existing probabilistic optimal power flow (POPF) studies mainly focus on the design and improvement on probabilistic calculation methods, which may be difficult to improve the computational efficiency of POPF as POPF is a nonconvex and nonlinear programming problem under uncertainty. Therefore, this paper centers on renewable-dominated AC-DC power grid and proposes a POPF model considering uncertainties associated with wind and solar power. To efficiently solve the POPF model, an improved convex relaxation is proposed to address the nonconvex and nonlinear power flow equations and reformulate the nonlinear POPF model as convex one. Furthermore, the Nataf transformation is adopted to address the correlations of non-normal distribution and then a Monte Carlo Simulation based Latin Hypercube sampling technique is developed to solve the convex POPF model. Finally, the effectiveness of the proposed improved convex relaxation based POPF method is demonstrated by a set of case results tested on the modified IEEE 39-bus, 118-bus, and 500-bus systems.

Key words: probabilistic optimal power flow, convex relaxation, uncertainty, Latin hypercube Sampling