Demand response of customers in Kitakyushu smart community project to critical peak pricing of electricity

被引:34
作者
Li, Yanxue [1 ]
Gao, Weijun [1 ]
Ruan, Yingjun [2 ]
Ushifusa, Yoshiaki [3 ]
机构
[1] Univ Kitakyushu, Fac Environm, Kitakyushu, Fukuoka 8080135, Japan
[2] Tongji Univ, Inst Engn Mech, Siping Rd 1239, Shanghai, Peoples R China
[3] Univ Kitakyushu, Fac Econ & Business Adm, Kitakyushu, Fukuoka 8028577, Japan
关键词
Critical peak pricing; Demand response; Peak cut; Multiple regression model; ENERGY; JAPAN; IMPLEMENTATION; HOUSEHOLDS;
D O I
10.1016/j.enbuild.2018.03.029
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Dynamic pricing is an effective way to induce the customers to change their electricity usage patterns, critical peak pricing (CPP) event shows a great potential to reduce the peak demand and enhance the grid reliability. This paper investigates performances of the CPP experiment across aggregated group-level of electricity customers covering 16 commercial, 15 office and 50 residential objectives in the Kitakyushu Smart Community demonstration project. A data-based approach to the comparisons of electricity demand curves and distributions among time of use (TOU) and CPP events. Result confirms the differences in price-based responsiveness across types of customer, there is demand shaping effect during the CPP event period by adjusting the electricity price at 30-min interval. The power saving effects were obviously confirmed in residential and commercial sectors under CPP event program. A multiple linear regression model is used to examine the response effectiveness and weigh the influencing factors of the fixed time for the dynamic pricing scheme. For the no-residential part, the electricity consumption strongly depends on the variations in temperature, commercial consumer tends to respond more to the changes of electricity price than office sector. The residential customer shows a promising potential for load reduction corresponding the increasing electricity price. However, the effects depend on the preferences of residential customers to change their power usage pattern at real time of the CPP event period. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:251 / 260
页数:10
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