User satisfaction-induced demand side load management in residential buildings with user budget constraint. (1st February 2017)

• Record Type: Journal Article
• Authors: Ogunjuyigbe, A.S.O.; Ayodele, T.R.; Akinola, O.A.
• Is Part Of: Applied energy. Volume 187(2017)
• Page Start: 352
• Page End: 366
• Publication Date: 2017-02-01
• Subjects: Demand side load management -- Electrical energy -- User satisfaction -- Residential buildings -- Budget constraint -- Genetic algorithm; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.11.071
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: DSM scheme that could maximize satisfaction within user's budget is presented. Load-satisfaction algorithm using the scheme is developed based on GA. We quantified user satisfaction based on certain rules. We develop cost per unit satisfaction index, k ($) that relates budget to satisfaction. The proposed algorithm is effective in offering the maximum satisfaction. Abstract: This paper presents a demand side load management technique that is capable of controlling loads within the residential building in such a way that the user satisfaction is maximized at minimum cost. Load-satisfaction algorithm was developed based on three postulations that allow satisfaction to be quantified. The input data required by the algorithm includes the power ratings of the electrical devices, its time of use, kW h electrical consumption as well as the satisfaction of the user on each electrical appliance at every hour of the day. From the data, the algorithm is able to generate an energy usage pattern, which would give the user maximum satisfaction at a predetermined user-budget. A cost per unit satisfaction index (k) which relates the expenditure of a user to the satisfaction achievable is also derived. To test the applicability of the proposed load-satisfaction management technique, three budget scenarios of $0.25/day, $0.5/day and $1.00/day are performed. The result of each of the scenarios using the proposed techniques is compared to cases in which the electrical appliances are randomly used. The results obtained revealed that the proposed algorithm offered the maximum satisfaction and minimum cost per unit satisfaction for all the scenarios.