摘要
无功功率优化与补偿技术是电力系统高效运行和稳定性提升的关键环节。随着现代电网规模的不断扩大以及新能源接入比例的持续增加，无功功率管理面临新的挑战。本文旨在研究电力系统中无功功率优化与补偿技术的有效方法及其实际应用价值。通过结合传统优化算法与智能计算技术，提出了一种基于改进粒子群算法的无功功率优化模型，该模型能够综合考虑系统节点电压分布、网损降低以及设备成本等多目标约束条件。同时，针对分布式电源接入场景，设计了动态无功补偿策略，以适应复杂工况下的功率波动需求。仿真结果表明，所提方法在降低系统网损、提高电压合格率以及增强系统稳定性方面具有显著效果。与现有技术相比，本文提出的优化模型在收敛速度和全局寻优能力上表现出明显优势，为大规模电力系统的无功功率管理提供了新思路。研究结论验证了该技术方案的可行性和优越性，为未来智能电网建设中的无功功率优化提供了理论支持和技术参考。
关键词：无功功率优化；粒子群算法；分布式电源
Abstract
Reactive power optimization and compensation technology is a critical component for enhancing the efficiency and stability of power systems. With the continuous expansion of modern grid scales and the increasing penetration of renewable energy sources, reactive power management faces new challenges. This paper focuses on investigating effective methods and practical application values of reactive power optimization and compensation technologies in power systems. By integrating traditional optimization algorithms with intelligent computing techniques, an improved reactive power optimization model based on the modified particle swarm optimization algorithm is proposed. This model comprehensively considers multi-ob jective constraints, including system node voltage distribution, network loss reduction, and equipment cost. Additionally, a dynamic reactive power compensation strategy is designed for scenarios involving distributed power source integration, aiming to adapt to power fluctuation demands under complex operating conditions. Simulation results demonstrate that the proposed method significantly reduces system network losses, improves voltage qualification rates, and enhances system stability. Compared with existing technologies, the optimization model presented in this paper exhibits evident advantages in convergence speed and global search capability, providing new insights into reactive power management for large-scale power systems. The conclusions drawn from this study validate the feasibility and superiority of the proposed technical solution, offering theoretical support and technical references for reactive power optimization in future smart grid construction.
Keywords：Reactive Power Optimization; Particle Swarm Algorithm; Distributed Generation
目 录
摘要 I
Abstract II
一、绪论 1
(一) 无功功率优化的研究背景与意义 1
(二) 国内外研究现状分析 1
(三) 本文研究方法与技术路线 2
二、无功功率的基本理论与分析 2
(一) 无功功率的定义与特性 2
(二) 电力系统中无功功率的作用 3
(三) 无功功率对系统稳定性的影响 3
三、无功功率优化方法研究 4
(一) 传统优化算法的应用与局限 4
(二) 现代智能优化算法的引入 4
(三) 基于目标函数的优化模型构建 5
(四) 优化方法的仿真验证与结果分析 6
四、无功功率补偿技术探讨 6
(一) 补偿技术的基本原理与分类 6
(二) 静态补偿装置的性能分析 7
(三) 动态补偿技术的发展与应用 7
(四) 补偿技术在实际工程中的案例研究 8
结 论 9
参考文献 10
无功功率优化与补偿技术是电力系统高效运行和稳定性提升的关键环节。随着现代电网规模的不断扩大以及新能源接入比例的持续增加，无功功率管理面临新的挑战。本文旨在研究电力系统中无功功率优化与补偿技术的有效方法及其实际应用价值。通过结合传统优化算法与智能计算技术，提出了一种基于改进粒子群算法的无功功率优化模型，该模型能够综合考虑系统节点电压分布、网损降低以及设备成本等多目标约束条件。同时，针对分布式电源接入场景，设计了动态无功补偿策略，以适应复杂工况下的功率波动需求。仿真结果表明，所提方法在降低系统网损、提高电压合格率以及增强系统稳定性方面具有显著效果。与现有技术相比，本文提出的优化模型在收敛速度和全局寻优能力上表现出明显优势，为大规模电力系统的无功功率管理提供了新思路。研究结论验证了该技术方案的可行性和优越性，为未来智能电网建设中的无功功率优化提供了理论支持和技术参考。
关键词：无功功率优化；粒子群算法；分布式电源
Abstract
Reactive power optimization and compensation technology is a critical component for enhancing the efficiency and stability of power systems. With the continuous expansion of modern grid scales and the increasing penetration of renewable energy sources, reactive power management faces new challenges. This paper focuses on investigating effective methods and practical application values of reactive power optimization and compensation technologies in power systems. By integrating traditional optimization algorithms with intelligent computing techniques, an improved reactive power optimization model based on the modified particle swarm optimization algorithm is proposed. This model comprehensively considers multi-ob jective constraints, including system node voltage distribution, network loss reduction, and equipment cost. Additionally, a dynamic reactive power compensation strategy is designed for scenarios involving distributed power source integration, aiming to adapt to power fluctuation demands under complex operating conditions. Simulation results demonstrate that the proposed method significantly reduces system network losses, improves voltage qualification rates, and enhances system stability. Compared with existing technologies, the optimization model presented in this paper exhibits evident advantages in convergence speed and global search capability, providing new insights into reactive power management for large-scale power systems. The conclusions drawn from this study validate the feasibility and superiority of the proposed technical solution, offering theoretical support and technical references for reactive power optimization in future smart grid construction.
Keywords：Reactive Power Optimization; Particle Swarm Algorithm; Distributed Generation
目 录
摘要 I
Abstract II
一、绪论 1
(一) 无功功率优化的研究背景与意义 1
(二) 国内外研究现状分析 1
(三) 本文研究方法与技术路线 2
二、无功功率的基本理论与分析 2
(一) 无功功率的定义与特性 2
(二) 电力系统中无功功率的作用 3
(三) 无功功率对系统稳定性的影响 3
三、无功功率优化方法研究 4
(一) 传统优化算法的应用与局限 4
(二) 现代智能优化算法的引入 4
(三) 基于目标函数的优化模型构建 5
(四) 优化方法的仿真验证与结果分析 6
四、无功功率补偿技术探讨 6
(一) 补偿技术的基本原理与分类 6
(二) 静态补偿装置的性能分析 7
(三) 动态补偿技术的发展与应用 7
(四) 补偿技术在实际工程中的案例研究 8
结 论 9
参考文献 10
