摘要
针对现行销售电价机制中用户分类不够科学规范、繁简不当的问题,借助模糊C均值算法,根据用户的典型日负荷曲线对用户进行分类并得到了典型用户负荷率曲线及用电参数。在此基础上,考虑用户需求响应建立了分时电价的最优化模型,分别计算分析了在峰荷最小、谷荷最大和峰谷差最小三种优化目标下的负荷曲线及各方收益变化。结果表明,在执行所设计的分时电价后,削峰填谷、改善负荷曲线的目标得以实现,有效缓解了电力供应高峰时段的负荷缺口,同时各方收益也得到了保证。
The Fuzzy C-means （FCM） algorithm is used to classify the electricity customers based on load factor curves of the typical days to solve the problem that the current classification isn＇t standard and scientific. The load factor curve of typical users and the electricity parameters are obtained. Additionally, an optimal time-of-use （TOU） model is established based on response of users＇ demand. The load curve and the income and expenses have been cal-culated and analyzed under three optimization objectives： min peak load, max valley load and rain valley-to-peak difference. The simulation result shows that the implementation of TOU model has helped to achieve the purposes of load shifting and load curve improving. The load gap during peak hours is effec.tively reduced, and profits of all par-ties are guaranteed.
出处
《华东电力》
北大核心
2014年第1期168-173,共6页
East China Electric Power
基金
上海交通大学文理交叉专项基金项目(11JCY11)
关键词
销售电价
用户用电特性
模糊C均值算法
用户需求响应
分时电价
electricity retail tariff
users＇ electrical characteristics
Fuzzy C-means algorithm
user demand re-sponse
TOU tariff
作者简介
薛承荣（1988），男，硕士，研究方向为电力系统规划及电力市场。
