论文总字数：34056字

摘 要

随着环保、能源危机和用电量的大幅度增长等方面的压力逐渐增大，各国越发重视新能源的开发利用。 并且社会的高速发展也给分布式电源的发展提供了坚实的基础，使风力发电、太阳能发电等分布式电源能够有效补充传统电网。本论文简述了中外的一些探索成果，对部分理论着重探索，主要工作大致为：

首先对风机光伏电源的发电原理和并网方式做大概介绍，而后探讨了负荷的预测方法并建立预测模型，验证可行后对各个DG的发电量也做预测，因为DG发电量和用户端需求不匹配，所以含DG的区域电网得要与无穷大电网之间进行功率交换，在达到功率平衡的前提下提出了最终优化的目标函数，同时提出一系列约束条件，据此完成系统优化，给出了基于模型预测的配电网PQ协调控制策略。

本文对于预测电源供电功率和负荷耗电功率的智能预测方法选择的是RBF神经网络预测，用MATLAB编程建模做仿真实验，对于系统优化则选择借助LINGO软件实现。

关键词：分布式电源 负荷预测 神经网络 系统优化 协调控制

Active and reactive power coordinated control strategy for distribution network based on model prediction

Abstract

With the environmental protection, energy crisis and the substantial increase in electricity consumption and other aspects of the pressure gradually increased, more and more attention to the development and utilization of new energy. And the rapid development of society to the development of distributed power to provide a solid foundation for wind power, solar power and other distributed power supply can effectively complement the traditional power grid.This paper summarizes some research results at home and abroad, and focuses on some theories, and the main work is as follows:

Firstly, the principle of power generation and the way of grid connection are introduced. Then, the load forecasting method is established and the forecasting model is established. After verification, the power generation of the distributed power supply is also predicted. Because the distributed power supply and the load demand do not match, the power grid with the distributed power supply needs to communicate with the infinite power grid to meet the power balance as the premise of the final optimization objective function and a series of constraints. Based on the system optimization, the active and reactive power coordination control strategy of distribution network based on model prediction is given.

In this paper, the intelligent prediction method for predicting the power supply and power consumption of the power supply is selected by RBF neural network prediction, and the simulation experiment is done with MATLAB programming. For system optimization, we choose LINGO software.

Key Words: Distributed power; Load forecasting;Neural networks; System optimization;Coordination control

目 录

摘要 I

Abstract II

第一章 绪论 1

1.1课题研究背景及意义 1

1.2研究现状 2

1.3本文研究内容及主要工作 3

第二章 典型分布式电源的工作原理 5

2.1 风力发电电电源 5

2.1.1 风力发电系统及电特性数学表述 5

2.1.2 风力发电并网方式 6

2.2 光伏电源 6

2.2.1 太阳能光伏发电系统及电特性表述 6

2.2.2 光伏发电系统并网方式 7

2.3 能量存储环节与并网方式 8

2.3.1 储能装置的存在意义 8

2.3.2 蓄电池储能系统的拓扑电路及数学表述 9

2.3.3 储能系统能量的并网利用 10

第三章 区域电网的负荷预测 11

3.1 RBF神经网络负荷预测 11

3.1.1 输入变量选择及预处理 11

3.1.2 RBF神经网络负荷预测模型 11

3.2 RBF神经网络负荷预测算例分析 14

第四章 配电网的优化 16

4.1 区域分布式电源电网系统优化总体思路 16

4.2 配电网整体优化调度 17

4.3 有功-无功协调优化 22

第五章 算例分析 27

第六章 总结与展望 30

6.1 总结 30

6.2 展望 31

参考文献 32

附录 34

第一章 绪论

1.1课题研究背景及意义

分布式电源(Distributed Generator,DG)的逐渐接入使主动配电网（Active Distribution Network,ADN）的运行愈发繁杂。尤其是接入DG后有一定可能导致配电网发生局部过电压，再引发停运等现象。

请支付后下载全文，论文总字数：34056字