How real time pricing modifies Chinese households' electricity consumption

Authored by Hongxia Wang, Hong Fang, Xueying Yu, Sai Liang

Date Published: 2018

DOI: 10.1016/j.jclepro.2017.12.251

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

Implementing real-time electricity pricing in residential sector is supposed to be an effective measure to balance daily electricity load and promote electricity conservation. However, due to lack of empirical evaluation, evidence about the in-field impacts of real-time electricity pricing is still lacking in China. Based on household survey and agent-based modeling, this study simulates Chinese household's 24-h electricity demand profile, and analyzes how households adjust their electricity use activities under the dynamic real-time pricing, scheme. Results show that real-time pricing has the potential to shift residential electricity load from peak to off-peak periods and reduce total electricity consumption. The magnitudes of these two effects hinge on the probability of households' response to electricity price increases. Survey results indicate that such probability varies along the two dimensions of households' characteristics and the type of electricity use activities. To raise the response rates and improve real-time pricing's effects, the following strategies are proposed: 1) introduce and subsidize the purchase of economically feasible domestic electricity storage devices; 2) integrate environmental education modules in the real-time pricing policy design, so as to raise household dwellers' sensitive to the price signals. (C) 2017 Elsevier Ltd. All rights reserved.

Tags

Model Demand-side management Residential demand Determinants Sector Load Grids Customers Real time pricing Household electricity demand Block tariffs Reform