光伏发电主气象影响因子识别优化与功率预测模型研究

项目名称： 光伏发电主气象影响因子识别优化与功率预测模型研究

项目编号： No.51277075

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： 米增强

作者单位： 华北电力大学（保定）

项目金额： 78万元

中文摘要： 光伏发电是受辐照度、温度等多元气象因素影响的间歇式电源，其规模化集中接入会给电网的安全运行带来严峻挑战，光伏发电功率预测是解决此问题的关键技术之一。由于光伏发电功率与其多元气象影响因子间存在着不均衡的非线性关系，且各因子间又相互关联，如何有科学依据地优化选取光伏发电功率预测模型的输入变量，并据此进行预测模型与建模方法研究，对解决光伏发电功率预测的应用基础问题，具有重要的学术与应用价值。 本项目利用光伏电站实际运行数据，采用数据挖掘与灵敏度分析方法，研究光伏发电功率与多元气象影响因子间的动态关联规律，给出关联性强弱的科学表示，识别影响光伏发电功率的主气象影响因子；利用关联矩阵和神经网络方法，研究建立针对不同天气类型的"主气象影响因子-发电功率"模型；利用不同时空的实际运行数据对选取的输入变量及模型的准确性、适应性进行优化、验证。研究成果将为光伏发电功率预测的研究提供科学依据与技术基础。

中文关键词： 光伏发电；功率预测；影响因子；识别优化；模型

英文摘要： The output of photovoltaic (PV) power generation is influenced by many factors including irradiance, temperature, wind speed, etc. PV power generation is intermittent power source and its large-scale centralized access will bring grim challenges to the safe operation of the power grid. PV power forecasting is one of the key technologies to solve this problem. Due to the unbalanced and non-linear relationship between PV power and its multiple meteorological impact factors which are interrelated and interact on each other, how to optimize and select the input variables of PV power forecasting model with scientific foundation, and carry out the research of forecasting model and modeling method based on these input variables are of important academic and application value to slove the application basic problems of PV power forecasting. In this project, data mining and sensitivity analysis are adopted to reveal the dynamic association rules between PV power and multiple meteorological impact factors by using the actual operating data of PV power station. The scientific representation describing the degree of relevance will be given, and the major meteorological impact factors of PV power will be recognized. Then the 'dorminant meteorological impact factors-generation power' model for different weather patterns will

英文关键词： photovoltaic power generation；power forecasting；impact factors；recognition and optimization；model