考虑新能源发电预测误差及其联合分布特性的电力系统随机优化理论研究

项目名称： 考虑新能源发电预测误差及其联合分布特性的电力系统随机优化理论研究

项目编号： No.51277141

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 电工技术

项目作者： 王建学

作者单位： 西安交通大学

项目金额： 72万元

中文摘要： 由于新能源的随机性，使得新能源发电功率预测的准确性不高。如果沿用传统处理方法，将新能源出力视为确定性变量来安排系统优化运行，会存在较大误差。伴随2011年光伏发电的迅猛发展，未来电力系统将同时消纳风力发电和光伏发电。多类新能源并网必将带来不同新能源预测误差分布的相互影响，其优化运行问题将是多随机变量、多约束的复杂非线性规划问题。本项目以预测误差分布为主线对此进行研究，主要内容包括：研究风力发电和光伏发电的预测方法机理和实际数据统计，确定预测误差的分布形式和置信区间；建立多种新能源发电预测误差的联合概率模型，即多维随机变量线性和的概率模型；分析新能源预测误差对随机潮流和谐波潮流的影响，并探讨统一建模方法；采用随机规划理论中期望值和机会约束模型，将预测误差分布通过数学变换纳入到机组组合、经济调度等系统优化基础问题中。本项目将为多种新能源发电并网下的电力优化运行提供有力的理论支持和技术支撑。

中文关键词： 概率预测；随机优化；机组组合；谐波潮流；电网规划

英文摘要： Due to the random character of renewable and sustainable energy, the accuracy of renewable and sustainable energy power generation forecast is not high. Prediction error of renewable and sustainable energy is large if we still regard the renewable and sustainable energy generation as deterministic variables when optimizing power system operation. With the rapid development of photovoltaic power generation in 2011, wind power and photovoltaic power will be connected to power system together in the future. When different renewable and sustainable energy is connected to power grid, distributions of their prediction errors influence each other and the problem of optimal operation become a multi-constrained and nonlinear programming problem with more than one random variable. This project concentrates on the distribution of prediction error. Our study includes prediction methods and data statistic for wind power and photovoltaic power to determine prediction results. After getting the distribution of prediction error, the confidence interval of prediction error can be calculated. The joint probability model for prediction errors of renewable and sustainable energy power is established by calculating the sum of different random variables. After renewable and sustainable energy power generation is connected to the grid

英文关键词： Probabilistic forecasting；Stochastic Programming；Unit Commitment；Harmonic Power Flow；Transmission Expansion Planning