A binary integer programming model for optimal load scheduling of household appliances with consumer's preferences

This paper addresses the residential demand response problem through the scheduling of typical home appliances while incorporating more realistic aspects. The objective of this study is to generate an optimal load schedule of home appliances with consumer's preferences, which includes preferred...

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Veröffentlicht in:2018 International Conference on the Domestic Use of Energy (DUE) S. 1 - 8
Hauptverfasser: Yahia, Zakaria, Kholopane, Pule
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Cape Peninsula University of technology 01.04.2018
Schlagworte:
Binary integer programming
Home appliances
Household appliances
Household energy management
Inconvenience
Linear programming
Load modeling
Mathematical model
Optimal scheduling
Residential load scheduling
Schedules
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Zusammenfassung:This paper addresses the residential demand response problem through the scheduling of typical home appliances while incorporating more realistic aspects. The objective of this study is to generate an optimal load schedule of home appliances with consumer's preferences, which includes preferred schedule for some appliances. To obtain an optimal load schedule of home appliances, a binary integer programming optimization model is proposed under a time-of-use electricity tariff. The proposed mathematical formulation is compared against a non-linear mathematical model formulation from the literature. The objective function minimizes the weighted score of electricity cost and earn the relevant incentive and the scheduling inconvenience. A case study shows that a household can shift consumption in response to the varying prices and incentives, through which the consumer may realize an electricity cost saving of around 55% compared to the preferred schedule defined by the consumer, and by around 31% compared to the schedule resulted from the non-linear model from the literature. Furthermore, the results show that the proposed binary model proves a significant superior performance, especially in terms of computation time.
DOI:10.23919/DUE.2018.8384381