Publication detail
Simulator for optimal scheduling of domestic appliances
KACZMARCZYK, V. FIEDLER, P. BRADÁČ, Z. FRANEK, L. PÁSEK, J.
Original Title
Simulator for optimal scheduling of domestic appliances
English Title
Simulator for optimal scheduling of domestic appliances
Type
conference paper
Language
en
Original Abstract
Introduction of real-time pricing models for the price of electricity may lead to a reduction in both economic and environmental burden compared with existing models. Thanks to the timely response to price changes during the day the user can achieve a reduction in the payments for energy. However, recent studies show that lack of knowledge of users and their unwillingness to adapt their habits to changing energy prices is the biggest obstacle to successful implementation of the model. In our work, we propose to solve this problem by introducing automatic optimal energy consumption scheduling framework. This article presents the authors extension in the past created MILP model for the optimization of household appliances. The model is extended by rules of behavior that allows preserving logical links in the course of periodically triggered optimization (so called receding horizon). We also present and test the software simulator, in which the designed model is implemented. The application simulates the operation of Building Energy Manager, which based on user preferences, prediction electricity prices and other important parameters controls the operation of appliances in the house.
English abstract
Introduction of real-time pricing models for the price of electricity may lead to a reduction in both economic and environmental burden compared with existing models. Thanks to the timely response to price changes during the day the user can achieve a reduction in the payments for energy. However, recent studies show that lack of knowledge of users and their unwillingness to adapt their habits to changing energy prices is the biggest obstacle to successful implementation of the model. In our work, we propose to solve this problem by introducing automatic optimal energy consumption scheduling framework. This article presents the authors extension in the past created MILP model for the optimization of household appliances. The model is extended by rules of behavior that allows preserving logical links in the course of periodically triggered optimization (so called receding horizon). We also present and test the software simulator, in which the designed model is implemented. The application simulates the operation of Building Energy Manager, which based on user preferences, prediction electricity prices and other important parameters controls the operation of appliances in the house.
Keywords
Smart power applications, Optimization, Linear Programming, Energy Management System
RIV year
2015
Released
13.05.2015
Location
Krakow, Polsko
ISBN
1474-6670
Periodical
Programmable devices and systems
Year of study
2015
Number
13
State
GB
Pages from
1
Pages to
6
Pages count
6
Documents
BibTex
@inproceedings{BUT115225,
author="Václav {Kaczmarczyk} and Petr {Fiedler} and Zdeněk {Bradáč} and Lešek {Franek} and Jan {Pásek}",
title="Simulator for optimal scheduling of domestic appliances",
annote="Introduction of real-time pricing models for the price of electricity may lead to a reduction in both economic and environmental burden compared with existing models. Thanks to the timely response to price changes during the day the user can achieve a reduction in the payments for energy. However, recent studies show that lack of knowledge of users and their unwillingness to adapt their habits to changing energy prices is the biggest obstacle to successful implementation of the model. In our work, we propose to solve this problem by introducing automatic optimal energy consumption scheduling framework. This article presents the authors extension in the past created MILP model for the optimization of household appliances. The model is extended by rules of behavior that allows preserving logical links in the course of periodically triggered optimization (so called receding horizon). We also present and test the software simulator, in which the designed model is implemented. The application simulates the operation of Building Energy Manager, which based on user preferences, prediction electricity prices and other important parameters controls the operation of appliances in the house.
",
booktitle="Proceedings of Programmable devices and systems",
chapter="115225",
doi="10.1016/j.ifacol.2015.07.014",
howpublished="online",
number="13",
year="2015",
month="may",
pages="1--6",
type="conference paper"
}