摘 要
随着电气工程领域的快速发展，智能优化算法在解决复杂非线性问题中展现出显著优势。本研究旨在探索智能优化算法在电气系统设计、运行与控制中的应用潜力，以提升系统效率和稳定性。研究选取了多种典型智能优化算法，包括遗传算法、粒子群优化算法及差分进化算法，并结合实际电气工程场景进行改进与验证。通过构建多目标优化模型，将算法应用于电力调度、负荷预测以及设备参数优化等问题，结果表明所提出的改进算法能够有效提高求解精度和收敛速度。特别地，本研究提出了一种融合自适应机制的混合优化策略，该策略可根据问题特性动态调整算法参数，从而显著增强其鲁棒性和适用性。
关键词：智能优化算法 电气系统 自适应混合优化策略
Abstract
With the rapid development of the electrical engineering field, intelligent optimization algorithms show significant advantages in solving complex nonlinear problems. This study aims to explore the potential of intelligent optimization algorithms in the design, operation and control of electrical systems to improve system efficiency and stability. A variety of typical intelligent optimization algorithms were selected, including genetic algorithm, particle swarm optimization algorithm and differential evolution algorithm, and were improved and verified by combining with actual electrical engineering scenarios. By constructing a multi-ob jective optimization model, the algorithm is applied to power dispatching, load prediction and equipment parameter optimization, and the results show that the proposed improved algorithm can effectively improve the solution accuracy and convergence speed. In particular, this study proposes a hybrid optimization strategy incorporating adaptive mechanisms, which dynamically adjusts the algorithm parameters according to the problem properties, thus significantly enhancing its robustness and applicability.
Keyword:Intelligent Optimization Algorithm Electrical System Adaptive Hybrid Optimization Strategy
目 录
1绪论 1
1.1电气工程与智能优化算法的研究背景 1
1.2智能优化算法在电气工程中的研究现状 1
1.3本文研究方法与技术路线 2
2智能优化算法基础理论分析 2
2.1智能优化算法的基本原理 2
2.2常见智能优化算法的分类与特点 2
2.3智能优化算法在电气工程中的适用性分析 3
2.4算法性能评价指标体系构建 3
3智能优化算法在电力系统中的应用研究 4
3.1电力系统优化问题概述 4
3.2智能优化算法在负荷预测中的应用 4
3.3智能优化算法在电力调度中的实践 5
3.4算法改进对电力系统效率的影响 5
4智能优化算法在电气设备优化中的研究 6
4.1电气设备优化设计的需求分析 6
4.2智能优化算法在电机设计中的应用 6
4.3智能优化算法在变压器优化中的作用 7
4.4算法在电气设备故障诊断中的潜力 7
结论 8
参考文献 9
致谢 10
随着电气工程领域的快速发展，智能优化算法在解决复杂非线性问题中展现出显著优势。本研究旨在探索智能优化算法在电气系统设计、运行与控制中的应用潜力，以提升系统效率和稳定性。研究选取了多种典型智能优化算法，包括遗传算法、粒子群优化算法及差分进化算法，并结合实际电气工程场景进行改进与验证。通过构建多目标优化模型，将算法应用于电力调度、负荷预测以及设备参数优化等问题，结果表明所提出的改进算法能够有效提高求解精度和收敛速度。特别地，本研究提出了一种融合自适应机制的混合优化策略，该策略可根据问题特性动态调整算法参数，从而显著增强其鲁棒性和适用性。
关键词：智能优化算法 电气系统 自适应混合优化策略
Abstract
With the rapid development of the electrical engineering field, intelligent optimization algorithms show significant advantages in solving complex nonlinear problems. This study aims to explore the potential of intelligent optimization algorithms in the design, operation and control of electrical systems to improve system efficiency and stability. A variety of typical intelligent optimization algorithms were selected, including genetic algorithm, particle swarm optimization algorithm and differential evolution algorithm, and were improved and verified by combining with actual electrical engineering scenarios. By constructing a multi-ob jective optimization model, the algorithm is applied to power dispatching, load prediction and equipment parameter optimization, and the results show that the proposed improved algorithm can effectively improve the solution accuracy and convergence speed. In particular, this study proposes a hybrid optimization strategy incorporating adaptive mechanisms, which dynamically adjusts the algorithm parameters according to the problem properties, thus significantly enhancing its robustness and applicability.
Keyword:Intelligent Optimization Algorithm Electrical System Adaptive Hybrid Optimization Strategy
目 录
1绪论 1
1.1电气工程与智能优化算法的研究背景 1
1.2智能优化算法在电气工程中的研究现状 1
1.3本文研究方法与技术路线 2
2智能优化算法基础理论分析 2
2.1智能优化算法的基本原理 2
2.2常见智能优化算法的分类与特点 2
2.3智能优化算法在电气工程中的适用性分析 3
2.4算法性能评价指标体系构建 3
3智能优化算法在电力系统中的应用研究 4
3.1电力系统优化问题概述 4
3.2智能优化算法在负荷预测中的应用 4
3.3智能优化算法在电力调度中的实践 5
3.4算法改进对电力系统效率的影响 5
4智能优化算法在电气设备优化中的研究 6
4.1电气设备优化设计的需求分析 6
4.2智能优化算法在电机设计中的应用 6
4.3智能优化算法在变压器优化中的作用 7
4.4算法在电气设备故障诊断中的潜力 7
结论 8
参考文献 9
致谢 10
