Next Article in Journal
A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming
Previous Article in Journal
A Numerical and Graphical Review of Energy Storage Technologies
Article Menu

Export Article

Open AccessArticle

Optimal Scheduling of Domestic Appliances via MILP

CEITEC - Central European Institute of Technology, Brno University of Technology, Technicka 3058/10, CZ-61600 Brno, Czech Republic
Author to whom correspondence should be addressed.
Academic Editor: Josep M. Guerrero
Energies 2015, 8(1), 217-232;
Received: 20 August 2014 / Accepted: 12 November 2014 / Published: 29 December 2014
PDF [501 KB, uploaded 17 March 2015]


This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power peaks in order to achieve a balanced daily load schedule. An exact and computationally efficient mixed-integer linear programming (MILP) formulation of the problem is presented. This model is verified by several problem instances. Realistic scenarios based on the real price tariffs commercially available in the Czech Republic are calculated. The results obtained by solving the optimization problem are compared with a simulation of the ripple control service currently used by many domestic consumers in the Czech Republic. View Full-Text
Keywords: optimal scheduling; mixed integer linear programming (MILP); ripple control; smart home; smart appliance optimal scheduling; mixed integer linear programming (MILP); ripple control; smart home; smart appliance

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Bradac, Z.; Kaczmarczyk, V.; Fiedler, P. Optimal Scheduling of Domestic Appliances via MILP. Energies 2015, 8, 217-232.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top