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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Domestic Load Scheduling Using Genetic Algorithms
verfasst von : Ana Soares, Állvaro Gomes, Carlos Henggeler Antunes, Hugo Cardoso
Erschienen in: Applications of Evolutionary Computation
Verlag: Springer Berlin Heidelberg
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An approach using a genetic algorithm to optimize the scheduling of domestic electric loads, according to technical and user-defined constraints and input signals, is presented and illustrative results are shown. The aim is minimizing the end-user’s electricity bill according to his/her preferences, while accounting for the quality of the energy services provided. The constraints include the contracted power level, end-users’ preferences concerning the admissible and/or preferable time periods for operation of each load, and the amount of available usable power in each period of time to account for variations in the (non-manageable) base load. The load scheduling is done for the next 36 hours assuming that a dynamic pricing structure is known in advance. The results obtained present a noticeable decrease of the electricity bill when compared to a reference case in which there is no automated scheduling.