A novel approach for multi-objective cost-peak optimization for demand response of a residential area in smart grids. (1st September 2022)

• Record Type: Journal Article
• Authors: Haider, Haider Tarish; Muhsen, Dhiaa Halboot; Al-Nidawi, Yaarob Mahjoob; Khatib, Tamer; See, Ong Hang
• Is Part Of: Energy. Volume 254:Part B(2022)
• Publication Date: 2022-09-01
• Subjects: Demand response -- Adaptive consumption pricing scheme -- Time of use -- Multi-objectives optimization -- VIKOR; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.124360
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: In this paper, an optimal load scheduling model of household appliances for smart home energy management considering demand response for different pricing schemes is proposed. Henry gas solubility optimization method is used to obtain optimal load scheduling solutions, and then these solutions are sorted using VIKOR multi-criteria decision making method. Multiple pricing schemes have been used such adaptive consumption level pricing scheme and time of use. The use of multiple pricing scheme is to compare the results of customers cost saving obtained. The results show, the proposed method a saves more than 80% and 76% of end-user energy cost for time of use and adaptive consumption level pricing scheme respectively. Meanwhile, the peak load of end-user is reduced by 55% for the baseline operation. The outcomes of this paper are also compared with other works in the literature in order to validate the proposed method. It is concluded in this research that the proposed method provides essential saving for energy cost and demand's peak power as well as keeps acceptable range of customer inconvenience level. Highlights: We propose multi-objectives optimization method for cost and energy saving. The solutions is evaluated by using hybrid multi-criteria decision making methods. The provided solutions of end-users are subject to acceptable level of inconvenience. The proposed method a saves more than 80% of end-user energy cost. The proposed method reduces end-user's peak load by 55% for the baseline operation.