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基于互补约束和绝对值线性化松弛的日前无功计划优化
作者:
作者单位:

1.电网运行风险防御技术与装备全国重点实验室,江苏省南京市 211106;2.国电南瑞科技股份有限公司,江苏省南京市 211106;3.国网电力科学研究院有限公司(南瑞集团有限公司),江苏省南京市 211106

摘要:

为高效求解大规模非线性含多时段耦合绝对值约束和整数变量的日前无功计划优化问题,提出了一种基于互补约束和绝对值线性化松弛的两阶段优化算法。通过线性化方法松弛多时段耦合绝对值约束,并基于互补条件和离散变量等价转换,将原问题转换为含互补约束的连续数学规划问题。将求解步骤分为两个阶段,并采用内点法依次求解。首先,不计互补约束,快速获得离散变量近似优化解;然后,求解含互补约束的完整模型以获得离散变量和连续变量的精确优化解。此外,为减少内点法迭代时综合海森矩阵的计算量,提出了一种快速稀疏存储计算方法。IEEE 118节点等标准测试系统和实际省级电网的仿真结果表明了所提算法的有效性、快速性及其在实际大规模电力系统的工程适用性。

关键词:

基金项目:

国家电网公司科技项目“基于数据挖掘的电压控制关键影响因素溯因推理与策略优化技术研究”(5108-202440046A-1-1-ZN)。

通信作者:

作者简介:

黄华(1978—),男,通信作者,硕士,研究员级高级工程师,主要研究方向:电力系统优化调度与无功电压控制。E-mail:huanghua2@sgepri.sgcc.com.cn
徐泰山(1968—),男,博士,研究员级高级工程师,博士生导师,主要研究方向:电力系统安全稳定分析与控制。E-mail:xutaishan@sgepri.sgcc.com.cn
高宗和(1962—),男,硕士,研究员级高级工程师,主要研究方向:电力系统调度自动化。E-mail:gaozonghe@sgepri.sgcc.com.cn


Day-ahead Reactive Power Schedule Optimization Based on Complementary Constraints and Absolute Value Linearization Relaxation
Author:
Affiliation:

1.State Key Laboratory of Technology and Equipment for Defense Against Power System Operational Risks, Nanjing 211106, China;2.NARI Technology Co., Ltd., Nanjing 211106, China;3.State Grid Electric Power Research Institute (NARI Group Corporation), Nanjing 211106, China

Abstract:

A two-stage optimization algorithm based on complementary constraints and absolute value linearization relaxation is proposed to efficiently solve the large-scale nonlinear day-ahead reactive power schedule optimization problems with multi-time period coupling absolute value constraints and integer variables. By using a linearization method to relax the multi-time period coupling absolute value constraints, and based on equivalence transformation between complementary conditions and discrete variables, the original problem is transformed into a continuous mathematical programming problem with complementary constraints. The solution steps are decomposed into two stages which are solved by the interior point method sequentially. Firstly, the approximate optimization solution for discrete variables is quickly obtained without considering complementary constraints. Then, the complete model with complementary constraints is solved to obtain the accurate optimization solutions for both discrete and continuous variables. In addition, a fast sparse storage calculation method is proposed to reduce the computational complexity of the integrated Hessian matrix during the iteration of the interior point method. The simulation results of standard test systems such as the IEEE 118-bus system and an actual provincial power grid demonstrate the effectiveness and rapidity of the proposed algorithm, as well as its engineering applicability in real large-scale power systems.

Keywords:

Foundation:
This work is supported by State Grid Corporation of China (No. 5108-202440046A-1-1-ZN).
引用本文
[1]黄华,徐泰山,高宗和,等.基于互补约束和绝对值线性化松弛的日前无功计划优化[J].电力系统自动化,2025,49(3):156-169. DOI:10.7500/AEPS20231008002.
HUANG Hua, XU Taishan, GAO Zonghe, et al. Day-ahead Reactive Power Schedule Optimization Based on Complementary Constraints and Absolute Value Linearization Relaxation[J]. Automation of Electric Power Systems, 2025, 49(3):156-169. DOI:10.7500/AEPS20231008002.
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  • 收稿日期:2023-10-08
  • 最后修改日期:2024-05-11
  • 录用日期:2024-05-16
  • 在线发布日期: 2025-02-07
  • 出版日期: