论文总字数：23938字

摘 要

在科研领域和生活实际应用中，复杂问题的寻优一直受到人们的广泛关注，电力系统的经济调度在电力系统优化中起着至关重要的作用。随着电力网络规模的发展扩大，电力系统经济调度模型也越来越复杂，由于经济调度问题本身也是一个优化问题。传统的数学优化算法无法满足现如今具有高维度、非线性等诸多特点的调度模型。一方面，化石能源的不可再生性和当今社会对环境保护的追求，人们开始重视电能的“安全、可靠、优质、环保、高效”性。智能优化算法的出现，为解决复杂优化问题提供了一种新的方向。生物地理学优化算法是智能优化算法的一种，寻优速度快，稳定性高是BBO算法的特点。随着对现代智能技术的深入研究，智能优化算法也逐渐被应用到电力系统之中用于求最优解

本文通过学习生物地理学优化算法(Biogeography-based optimization, BBO)来对电力系统经济调度问题进行研究。主要内容有：

1）对国内外电力系统经济调度和智能优化算法进行综述，阐释了研究背景及意义。点明了电力系统经济调度问题具有高维度，约束条件复杂等特点，传统优化算法不能很好解决该问题。指出智能优化算法的发展和BBO算法的发展以及应用。

2）详细说明了BBO算法的设计原理，讲解了BBO算法中的最重要的两个算子：迁移算子和变异算子。根据对测试函数的仿真优化计算结果，对比其他两种智能优化算法，证实了BBO算法对于优化问题的可行性。探讨了BBO算法的基本流程和控制参数。

3）在考虑阀点效应的情况下将BBO算法应用到电力系统经济调度中去，为电力系统经济调度建立数学模型，引入罚函数法来进行约束条件的处理，通过惩罚项过滤掉不满足约束条件的结果，保留优质解。在此基础上，用一个9节点和一个30节点的算例进行仿真测试，并讨论不同参数设置对优化结果的影响。分析优化后结果，得出结论。

关键词：群体智能；生物地理学优化算法；电网经济调度；仿真运算

Abstract

In the field of scientific research and practical application, the optimization of complex problems has been widely concerned by people, and the economic dispatching of power system plays a vital role in the optimization of power system. With the development and expansion of power network, the economic dispatching model of power system becomes more and more complicated, because the economic dispatching problem itself is also an optimization problem. Traditional mathematical optimization algorithms cannot satisfy the current scheduling models with high dimensions and non-linearity. On the one hand, because of the non-renewability of fossil energy and the pursuit of environmental protection in today"s society, people begin to pay attention to the "safety, reliability, high quality, environmental protection and efficiency" of electric energy. The emergence of intelligent optimization algorithm provides a new direction for solving complex optimization problems. Biogeography optimization algorithm is a kind of intelligent optimization algorithm. The characteristics of BBO algorithm are fast optimization speed and high stability. With the in-depth study of modern intelligent technology, intelligent optimization algorithm is gradually applied to the power system to find the optimal solution

In this paper, Biogeography-based optimization (BBO) is used to study the economic scheduling problem of power systems. The main contents are:

1) The economic dispatching and intelligent optimization algorithms of power systems at home and abroad are summarized, and the research background and significance are explained. It is pointed out that the economic dispatching problem of power system has the characteristics of high dimension and complicated constraint conditions, and the traditional optimization algorithm can not solve the problem well. The development and application of intelligent optimization algorithm and BBO algorithm are pointed out.

2) The design principle of BBO algorithm is explained in detail, and the two most important operators in BBO algorithm are explained: transfer operator and mutation operator. According to the simulation and optimization calculation results of the test function, the feasibility of the BBO algorithm for the optimization problem is verified by comparing the other two intelligent optimization algorithms. The basic flow and control parameters of BBO algorithm are discussed.

3) Applying the BBO algorithm to the economic dispatching of power system under the condition of considering the valve point effect, establishing the mathematical model for the economic dispatching of power system, introducing the penalty function method to deal with the constraint conditions, filtering out the results that do not meet the constraint conditions through the penalty term, and retaining the high quality solution. On this basis, a 9-node and a 30-node example are used for simulation tests, and the influence of different parameter Settings on the optimization results is discussed. The optimized results are analyzed and the conclusion is drawn.

Key words: Swarm intelligence; Biogeographic optimization algorithm; Economic dispatch of power grid; Simulation operation

目录

摘要 I

Abstract II

第1章 绪论 1

1.1 课题的研究背景的和意义 1

1.2 国内外研究现状 1

1.2.1 电力系统优化研究现状 1

1.2.2 经济调度的求解方法 2

1.2.3 生物地理学算法在电力系统中的应用 3

1.3 本文主要研究内容和章节安排 3

第2章 生物地理学优化算法 5

2.1 引言 5

2.2 生物地理学优化算法的设计原理 5

2.3 生物地理学优化算法简介 5

2.3.1 迁移操作 6

2.3.2 变异操作 7

2.4 BBO算法的寻优性能分析 9

2.4.1 测试函数 9

2.4.2 优化算法相关参数设置 10

2.4.3 寻优测试结果及分析 10

2.5 本章小结 13

第3章 生物地理学算法在考虑阀点效应的静态经济调度问题中的应用 14

3.1 引言 14

3.2 静态经济调度问题简述 14

3.2.1 目标函数 14

3.2.2 约束条件 15

3.3 约束条件的处理 16

3.4 本章小结 16

第4章 基于BBO算法经济调度的算例分析 17

4.1 引言 17

4.2 算例1：3机9节点系统 17

4.2.1 算例描述和设置 17

4.2.2 算例的优化结果 19

4.3 算例2：6机30节点系统 21

4.3.1 算例描述和设置 21

4.3.2 算例的优化结果 23

4.4 本章小结 24

第5章 结论 25

致谢 26

参考文献 27

绪论

课题的研究背景的和意义

电力工业是我国能源产业的一部分，也是我国经济发展的命脉所在，亦是国民经济稳定快速发展的基础，支撑着交通运输，信息传输，商业服务业等第三产业的稳步发展。国家对电力产业的大力支持，使其在中国特色社会主义进程中起着举足轻重的作用，成为了国家经济发展的基石。然而随着不可再生资源的大量使用，人们越来越关注环境问题和效率问题。

经济调度(Economic Dispatch, ED)问题实际上是一个优化问题，用数学表达式可以表示为：

以上公式中，式1‑1是ED问题的目标函数，一般是电力系统的发电总成本，发电成本就是发电过程中人力、物力投入的总和。式1‑2是各类约束条件：是D维优化变量，一般表示各个发电机的输出功率：在实现目标值（发电成本）最小的同时满足用户的负荷需求，满足系统各种约束条件，是解决ED问题的根本所在。

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