A multi-objective genetic approach to domestic load scheduling in an energy management system

Ana Soares, Carlos Henggeler Antunes, Carlos Oliveira and Álvaro Gomes

Energy, 2014, vol. 77, issue C, 144-152

Abstract: In this paper a multi-objective genetic algorithm is used to solve a multi-objective model to optimize the time allocation of domestic loads within a planning period of 36 h, in a smart grid context. The management of controllable domestic loads is aimed at minimizing the electricity bill and the end-user’s dissatisfaction concerning two different aspects: the preferred time slots for load operation and the risk of interruption of the energy supply. The genetic algorithm is similar to the Elitist NSGA-II (Nondominated Sorting Genetic Algorithm II), in which some changes have been introduced to adapt it to the physical characteristics of the load scheduling problem and improve usability of results. The mathematical model explicitly considers economical, technical, quality of service and comfort aspects. Illustrative results are presented and the characteristics of different solutions are analyzed.

Keywords: Domestic energy resources; Multi-objective problems optimization; Genetic algorithms (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:77:y:2014:i:c:p:144-152

DOI: 10.1016/j.energy.2014.05.101

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