风力发电并网的小时间尺度随机优化方法研究

项目名称： 风力发电并网的小时间尺度随机优化方法研究

项目编号： No.51307062

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 电工技术

项目作者： 李梦诗

作者单位： 华南理工大学

项目金额： 22万元

中文摘要： 为了降低风速的随机特性对经济调度和无功优化过程中对运行成本、补偿装置配置、电压稳定性的扰动影响，提高风电渗透率，本申请提出了一种基于拟蒙特卡洛法和双粒子算法相结合的具有抗扰性的随机优化算法。研究将首先设计一种小时间尺度上的风电场随机模型，从而利用历史风速统计数据，描述时间尺度上与调度周期相一致的风电场有功出力概率。根据该模型，随机潮流分析过程创新性地通过拟蒙特卡罗方法生成一组低差异风电场出力样本，并依次进行潮流计算，获得每个样本下系统的燃料损耗、电压稳定性及风电渗透率等指标的概率。在优化过程中，经济调度和无功优化使用了传统牛顿法搜索与自启发式算法相结合的双粒子算法，能够保证优化的速度和收敛性。同时，目标函数除了包含各项指标的均值，还将引入指标的方差，以抵御风电的随机特性对优化结果的扰动，因此结果的置信度高。

中文关键词： 风电；小时间尺度；随机性；优化；调度

英文摘要： The stochastic behavior of wind power has negative impact on operation cost, compensation device configuration, and voltage stability in economic dispatch and reactive power dispatch. In order to reduce the interference and further increase the wind power penetration to the grid, this project aims to propose a stochastic optimization method, which is based on a Quasi-Monte Carlo power flow simulation and a Paired-Bacteria Optimizer (PBO). The research firstly develops a small-time scale wind farm stochastic model, which is used to calculate the real/reactive power output probability density function based on the measurements of wind speed during a dispatch iteration. Weibull distributions are usually used to describe long-term wind stochastic characteristic such as months and years, which is not suitable in the applications of dispatch. Thus, this project proposes a novel stochastic model with multiple peaks in concern with the description of wind farm stochastic characteristic within the time-scale of hours. Most of conventional stochastic analysis is based on Monte Carlo simulation, which depends on power flow evaluations on a large number of samples generated using probability density function, and causes a great computation. To reduce the computational complexity, Quasi-Monte Carlo simulation is employed

英文关键词： wind power；small time-scale；stochastic；optimization；dispatch