基于智能算法的电力系统有功经济调度研究
2022-11-05 10:15:28
论文总字数:19439字
摘 要
电力系统的有功优化是电力系统经济调度中十分重要的一环,处理电力系统有功优化有着许多方法,其中包含了经典法和蚁群智能算法,经典法具有可靠性强、计算速度快、准确性高等特点。蚁群智能算法具有抗干扰性强并且采用了正反馈机制。本文在这两种基本算法的基础上进行改进优化,提出改进后的算法并进行对比研究。首先介绍了节点导纳矩阵传统存贮方式和改进存贮方式、传统CU三角分解法和改进CU三角分解法求解线性方程组,通过极坐标牛顿拉夫逊法提出PQ极坐标分解法并提出改进。通过算例比较发现,使用改进后的存贮方式和引入矩阵的对称性和稀疏性可以加快求解电力系统线性方程组的速度,从而减少潮流计算的时间。最后详细介绍了基本蚁群算法及三种单参数改进的蚁群算法,在这些方法的基础提出多参数改进的蚁群算法,并在电力系统有功优化中应用,验证了改进蚁群算法在电力系统有功优化中的可行性。
关键词:电力系统;智能算法;有功优化;经济调度;蚁群算法
Research on Active Economic Scheduling Based on Intelligent Algorithm
Abstract
Active power optimization of power system is a very important link in the economic dispatching of power system. There are many methods to deal with active power optimization of power system, including classical method and ant colony intelligence algorithm. The classical method has the characteristics of strong reliability, fast calculation speed and high accuracy. Ant colony intelligence algorithm has strong anti-interference and adopts positive feedback mechanism. On the basis of these two basic algorithms, this paper improves and optimizes the improved algorithm and makes a comparative study. Firstly, the traditional and improved storage methods of node admittance matrix, the traditional and improved Cu-trigonometric decomposition methods to solve linear equations are introduced, and the PQ polar decomposition method is proposed and improved through the Newton method of polar coordinates. Through the comparison of the examples, it is found that using the improved storage method and introducing the symmetry and sparsity of the matrix can accelerate the speed of solving the linear equations of power system, thus reducing the time of power flow calculation. Finally, the basic ant colony algorithm and three kinds of single-parameter improved ant colony algorithm are introduced in detail. On the basis of these methods, the multi-parameter improved ant colony algorithm is proposed and applied in the active power optimization of power system, which verifies the feasibility of the improved ant colony algorithm in the active power optimization of power system.
Key words: power system; Intelligent algorithm; Active power optimization; Economic dispatching; Ant colony algorithm
目 录
摘 要 I
Abstract II
第一章 绪 论 1
1.1 主题背景 1
1.2 国内外研究现状 1
1.3 蚁群智能算法 2
1.4 电力系统有功优化 2
1.4.1 线性规划法 3
1.4.2 非线性规划法 3
1.4.3 二次规划法 3
1.5 本文的主要工作 3
第二章 电力系统潮流计算 5
2.1 节点导纳参数设置 5
2.2 导纳矩阵的分类 5
2.3 节点导纳矩阵的求取 6
2.4 牛顿拉夫逊法潮流计算 6
2.5 本章总结 8
第三章 智能算法优化原理分析 10
3.1 智能算法 10
3.2 蚁群智能算法 10
3.3 用MATLAB实现蚁群算法 13
3.3.1 基本步骤 13
3.3.2 具体实现 13
3.3.3 算例数据 14
3.3.4 参数设置 16
第四章 智能优化算法在电力系统无功优化中的应用 17
4.1 智能优化算法的优劣 17
4.2 蚁群算法参数设置 18
4.3 结果与分析 19
第五章 结论与展望 21
5.1结论 21
5.2展望 21
致 谢 22
参考文献 23
第一章 绪 论
1.1 主题背景
和物品交易一样,需要市场化,那么电力的市场化也同样是不可避免的趋势,无论是在国内还是在世界的工业史上,市场化是近年来在工业上电力改革的方向。
如今电力系统正在飞速发展,电力网发展的目标主要为大容量和高电压,人们重视的点更加偏向于电力系统如何才能更加具有经济性。
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