Modeling of regional electrical heating load characteristics considering user response behavior difference. (December 2020)

• Record Type: Journal Article
• Authors: Wang, Zhiqiang; Wang, Hanyu; Lin, Zijian; Liu, Wenxia; Mao, Yuyang; Wang, Xiaolong; Wang, Shan
• Is Part Of: International journal of electrical power & energy systems. Volume 123(2020)
• Publication Date: 2020-12
• Subjects: Coal-to-electricity -- Thermal comfort -- Demand response -- Diversified demand -- Discrete selection; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2020.106297
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: The user comfort and building features are considered in the thermal load modeling. The multi-objective model of electric heating load considers user response behavior. A multi-objective model solving method based on discrete decision is proposed. A modeling method of aggregate load for regional electric heating is proposed. Abstract: The load characteristics of "coal-to-electricity" based on demand response are affected by the users' diversified demand and differential response behavior. Therefore, to describe the response behavior of different users in detail, a regional electric heating system load characteristics modeling method considering the dual difference of demand and response behavior is proposed. Firstly, considering the users' characteristics and external environmental factors, a thermal comfort temperature model of differential users is proposed. And a thermal load characteristics modeling method is proposed based on the air temperature time-varying equations of buildings. Secondly, a multi-objective optimization method and a decision-making method are used to simulate the differential response behavior of users to obtain the load characteristics of a single class of users, which based on the discrete selection model. Finally, the regional users' classification criteria are established, which based on the influence factors of heat demand and response behavior. And the modeling method of multi-type users aggregate load characteristic is proposed. At the end of this paper, case studies of the modeling method have been validated the effectiveness of improving the solution accuracy of load characteristics.