Open AccessResponse reliability and risk analysis of users under time‐of‐use price
Author(s) -
Wu Hongbin,
Wang Jingjie,
Ren Yinze,
Bi Rui,
Sun Ming,
Wei Wei
Publication year - 2022
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12331
Subject(s) - demand response , reliability (semiconductor) , response time , electricity , computer science , sensitivity (control systems) , operations research , reliability engineering , econometrics , power (physics) , engineering , economics , physics , computer graphics (images) , quantum mechanics , electronic engineering , electrical engineering
Time‐of‐use (TOU) electricity prices are implemented based on the response characteristics of users. TOU prices guide the electricity consumption behaviour of users and make them actively respond to peak shaving and valley filling. In this paper, the conventional psychology response model of consumers is improved based on the history data of customer response to the TOU price. The paper defines four types of response load curves and proposes the response reliability indices. Additionally, it establishes the probability models of customer response. According to the characteristics of customer response, the sensitivity analysis of influencing factors and the risk analysis of customers are carried out according to the probability model of response. For instance, risk and characteristics analyses of the customer response were performed using the load data of residential areas in Nanjing city. The results indicate that the probability distribution of the customer response is approximate to the trapezoid distribution. The sequence of sensitivity coefficients of customer response factors is as follows: customer income, type of customer, and electrical equipment. The proposed method provides a scientific basis for electricity price implementers to accurately grasp the response behaviour of the user and establish a reasonable demand response strategy.