基于随机分布与LSSVM算法的居民峰谷电价响应模型研究
摘要：为克服无相关历史数据的困难,满足首次设计峰谷分时电价时挖掘居民用户行为规律的需要,提出一种模拟居民对分时电价需求响应规律的模型。在一定的响应行为随机分布假设前提下,首先通过问卷设计与抽样调查,统计目标地区居民在各种设定的电价情景下选择执行分时电价的频率及概率;其次结合问卷种类与统计结果设计模型的输入、输出属性并确定训练样本集合;最后在训练样本集的基础上运用LSSVM回归算法构造响应行为预测模型。该模型可在输入一定幅度内任意分时电价的情况下,输出对应的目标居民平均响应结果及标准差,从而实现了在无历史数据时,对居民在分时电价下的响应规律进行模拟,并为更多研究提供数据支持。算例仿真验证了该模型方法的合理性以及可行性。
Abstract:To obtain relative historical data and to meet the demand of discovering residential customers behavior rule when first designing time-of-use (TOU) price, a model of simulating the demand response behavior rule of residents under TOU price is proposed. Under a certain behavioral assumption of random distribution, the frequencies and probabilities of choosing TOU prices under a variety of given situations for residents in target area are counted through questionnaire designing and random sampling firstly. Secondly, the input and output attributes of the model and training set are designed and determined in line with the questionnaire categories and statistical results. In the end, the response behavior prediction model is built by using least square support vector machine (LSSVM) regression algorithm based on information of the training set. This model can predict the average response results and standard deviations under any TOU price within a certain range to describe residential customers behavior rule under TOU price when there is no historical data, which provides data support for researches in future. Accuracy, rationality and feasibility of the model are verified through case simulation.
标题：基于随机分布与LSSVM算法的居民峰谷电价响应模型研究
英文标题：Research on Responsive Behavior Model of Time-of-use Price for Residents Based on Random Distribution and LSSVM Algorithm
作者：赵会茹, 王玉玮, 谭忠富, 舒 艳, 张 超,
关键词：峰谷分时电价, 居民用户, 需求响应, 随机分布, LSSVM,
发表日期：2016-12-19
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