现阶段我国实行可再生能源市场化的激励政策研究

首先对国内外的可再生能源政策进行研究,并结合我国社会发展的实际情况及电力系统特点,在明确市场化激励方向的基础上,进行了以实行绿色电力价格试点和建立可交易的可再生能源绿色证书制度为主要内容的可再生能源的市场化激励政策机制分析,并着重阐明方案的具体实现方式。     

区间数信息下的用电客户信用评价

从解决实际问题的思路出发,首先建立了用电客户信用评价指标体系,并针对评价信息为区间数的实际情况,运用基于区间数的不确定性多指标决策法对用电客户信用进行评价,并通过一个算例说明了该方法的实用性和有效性。     

充电站典型模块设计及其经济效益分析

为了探究电动汽车充电站方案设计并寻求其最大经济效益,以福建省为例,基于福建省地标对箱变容量的规定以及现有市场充电桩规格,设计了4种充电站典型模块。通过对租金模式和服务费分成模式进行财务对比以及敏感因素影响研究,分析不同方案的经济效益。结果显示,采用大功率的充电桩经济性好,单位投资最低,收益率高。研究结果对充电站运营模式的选择、规模确定、设备选型等起到一定指导作用,同时对全国范围内充电站的建设也具有一定的参考价值。     

基于模糊多属性决策法的用电客户信用评价

用电客户的信用评价是供电企业及全社会都应该关注的问题.文章在分析了用电客户信用评价应该考虑的主要因素的基础上,建立了一套适用于用电客户信用评价的指标体系,并以三角模糊数的形式给出指标值和评价者的主观感觉值,将基于期望值的模糊多属性决策法引入用电客户的信用评价中,同时讨论了指标权重完全未知和部分未知时用电客户的信用评价问题.     

RS-SVM forecasting model and power supply-demand forecast

A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.