摘 要
随着电力系统规模的不断扩大和复杂性的增加，传统负荷优化方法难以满足现代电力系统高效、稳定运行的需求，智能算法为解决这一问题提供了新的思路。本研究旨在探讨智能算法在电力系统负荷优化中的应用，以提高电力系统的运行效率和稳定性。基于对电力系统负荷特性及现有优化方法的深入分析，选取遗传算法、粒子群算法等典型智能算法进行研究。通过构建适用于电力系统负荷优化的数学模型，将智能算法与电力系统实际运行数据相结合，在多种场景下进行仿真实验。结果表明，智能算法能够有效处理电力系统负荷优化问题，相较于传统方法，其优化精度更高、收敛速度更快。特别是在应对复杂多变的电力系统环境时，智能算法展现出更强的适应性。本研究创新性地将改进后的智能算法应用于电力系统负荷优化，不仅提高了优化效果，还为电力系统负荷优化提供了一种新途径，有助于推动电力系统向智能化方向发展，对电力系统的规划、运行和管理具有重要意义。
关键词：智能算法 电力系统负荷优化 遗传算法
Abstract
With the continuous expansion and increasing complexity of power systems, traditional load optimization methods are struggling to meet the demands for efficient and stable operation in modern power systems. Intelligent algorithms offer a novel approach to addressing this challenge. This study investigates the application of intelligent algorithms in power system load optimization to enhance operational efficiency and stability. Based on an in-depth analysis of power system load characteristics and existing optimization methods, typical intelligent algorithms such as genetic algorithms and particle swarm optimization are selected for research. By constructing mathematical models suitable for power system load optimization and integrating these algorithms with actual operational data, simulation experiments are conducted under various scenarios. The results demonstrate that intelligent algorithms can effectively handle power system load optimization problems, achieving higher optimization accuracy and faster convergence rates compared to traditional methods. Notably, in complex and dynamic power system environments, intelligent algorithms exhibit superior adaptability. Innovatively, this study applies improved intelligent algorithms to power system load optimization, not only enhancing optimization outcomes but also providing a new pathway for load optimization. This contributes to the intelligent development of power systems and holds significant implications for the planning, operation, and management of power systems.
Keyword:Intelligent Algorithm Power System Load Optimization Genetic Algorithm
目 录
1绪论 1
1.1电力系统负荷优化的研究背景与意义 1
1.2智能算法在电力系统中的应用现状 1
1.3本文研究方法与技术路线 2
2智能算法在负荷预测中的应用 2
2.1负荷预测的重要性与挑战 2
2.2常用智能算法的原理及特点 3
2.3智能算法在短期负荷预测的应用 3
2.4智能算法在中长期负荷预测的应用 4
3智能算法在负荷调度中的优化 4
3.1负荷调度的基本概念与目标 4
3.2遗传算法在负荷调度中的应用 5
3.3粒子群算法在负荷调度中的应用 5
4智能算法在负荷均衡中的实现 6
4.1负荷均衡的意义与要求 6
4.2模糊逻辑在负荷均衡中的应用 7
4.3神经网络在负荷均衡中的应用 7
4.4智能算法对系统稳定性的作用 8
结论 9
参考文献 10
致谢 11
