智能电网环境下的负荷预测理论与方法研究

项目名称： 智能电网环境下的负荷预测理论与方法研究

项目编号： No.51277057

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： 罗滇生

作者单位： 湖南大学

项目金额： 70万元

中文摘要： 紧密结合我国大力发展智能电网的现状，为克服智能电网发展给负荷预测带来的全新挑战，实现节能环保优化调度，多层次、多策略地考虑各种因素对电网负荷预测的影响，构建智能电网环境下的负荷预测理论与方法体系。在总体上，研究综合气象指标构造方法、累积效应、延迟效应，建立基于综合实时气象要素的电网负荷预测理论与方法。在供电侧，以数值天气预报NWP为基础，以元学习组合算法为核心，建立具有随机性、间歇性特点的风力发电与光伏发电负荷自适应精细化预测理论与方法。在用电侧，综合运用概率分析、经济学分析等科学原理，研究电动汽车电能日均消耗规律，建立电动汽车日充电概率性负荷预测理论与方法；研究基于形态相似准则的典型用户自动提取方法，分析多种因素，特别是不同情况下需求响应对典型用户负荷的影响，建立互动性负荷分析预测理论与方法。在以上研究基础上，开发满足智能电网环境下的新一代负荷预测平台，提高负荷预测水平。

中文关键词： 智能电网；云计算；经验模式分解；蒙特卡洛方法；模糊循环推理系统

英文摘要： This project is in close connection with the status of developing smart grid in China, aiming at overcoming new challenges to load forecasting brought by the development of smart grid, realizing optimization scheduling based on energy conservation and environmental protection. New theory and method system of load forecasting under the environment of the smart grid is constructed taking into account a variety of factors on load forecasting multi-levelly and strategely. In General, the theory and method of power system load forecast based on comprehensive hourly weather factors is constructed. Comprehensive meteorological index constructing method, cumulative effect, delay effect are researched. On the supply side, considering random, intermittent nature , wind power and photovoltaic power load adaptive forecasting theory and method using metal learning algorithm based on NWP (numerical weather forecast) is researched. On the demand side, electric vehicle's law of average daily electric power consumption is researched. Probability theory and method of load forecasting in electric vehicle daily charge are established using integrated probabilistic analysis, economic analysis. Automatic extraction method based on morphological similarity criteria for typical customers is studied. Interactive load forecasting theory

英文关键词： Smart Grid；Cloud Computing；Empirical Mode Decomposition；Monte Carlo Method；Fuzzy Recursive Inference system