EconPapers    
Economics at your fingertips  
 

A multi-objective optimization model considering users' satisfaction and multi-type demand response in dynamic electricity price

Qing Lu and Yufeng Zhang

Energy, 2022, vol. 240, issue C

Abstract: Dynamic electricity price mechanism is an important regulation method adopted by power companies in various countries to solve the contradiction between source and charge. According to the principle of consumer psychology, a non-cooperative Stackelberg model is constructed based on game theory to study the demand response characteristics of multi-type users. The model classifies users to realize the comprehensive consideration of users with different preferences. Meanwhile, it quantifies the impact of grid load fluctuation on the benefits of the power company and users' satisfaction with electricity consumption. Finally, the model is applied to a practical example, the Nash equilibrium solution of the model is obtained by NSGA-Ⅱ algorithm, and the sensitivity analysis of correlation coefficient is carried out. The results show that the model has a good effect on utility optimization of power supply and demand.

Keywords: Demand response; Game theory; Nash equilibrium solution; Users' satisfaction; Multi-type users (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544221027535
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:240:y:2022:i:c:s0360544221027535

DOI: 10.1016/j.energy.2021.122504

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:240:y:2022:i:c:s0360544221027535
            
OSZAR »