Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid

Mohamed Arikiez; Floriana Grasso; Dariusz Kowalski; Michele Zito

doi:10.1109/ENERGYCON.2016.7513915

Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid

Mohamed Arikiez
, Floriana Grasso
, Dariusz Kowalski
, Michele Zito

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

This paper investigates using heuristic algorithms to solve Multi-Objective Optimization Problem (MOOP). The primary goal is to minimize the electricity cost for a set of air conditioners in residential or commercial buildings. The second objective is to minimize the discomfort factor. The algorithm, also, enhances the utilization of local renewable power. This allocation problem can be formulated using a static technique such as Mixed Integer Linear Programming (MILP), but solving MILP-based MOOP could be impracticable in heavy problems due to the hardness of the problem. Accordingly, a trade-off between cost and runtime is required. Our algorithm uses an MILP-based heuristic algorithm and LP relaxation and an innovative rounding technique called, Minimum Deviation Rounding (MDR) to get a sub-optimal solution. The result reveals that our algorithm can solve a massive problem in few seconds and gives a superb sub-optimal solution.

Original language	English (US)
Title of host publication	2016 IEEE International Energy Conference, ENERGYCON 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467384636
DOIs	https://doi.org/10.1109/ENERGYCON.2016.7513915
State	Published - Jul 14 2016
Externally published	Yes
Event	2016 IEEE International Energy Conference, ENERGYCON 2016 - Leuven, Belgium Duration: Apr 4 2016 → Apr 8 2016

Publication series

Name	2016 IEEE International Energy Conference, ENERGYCON 2016

Conference

Conference	2016 IEEE International Energy Conference, ENERGYCON 2016
Country/Territory	Belgium
City	Leuven
Period	4/4/16 → 4/8/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Demand-side management
heating ventilation and air conditioning
heuristic algorithm
smart grid

ASJC Scopus subject areas

Computer Networks and Communications
Energy Engineering and Power Technology
Electrical and Electronic Engineering

Access to Document

10.1109/ENERGYCON.2016.7513915

Cite this

Arikiez, M., Grasso, F., Kowalski, D., & Zito, M. (2016). Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid. In 2016 IEEE International Energy Conference, ENERGYCON 2016 Article 7513915 (2016 IEEE International Energy Conference, ENERGYCON 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ENERGYCON.2016.7513915

Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid. / Arikiez, Mohamed; Grasso, Floriana; Kowalski, Dariusz et al.
2016 IEEE International Energy Conference, ENERGYCON 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7513915 (2016 IEEE International Energy Conference, ENERGYCON 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Arikiez, M, Grasso, F, Kowalski, D & Zito, M 2016, Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid. in 2016 IEEE International Energy Conference, ENERGYCON 2016., 7513915, 2016 IEEE International Energy Conference, ENERGYCON 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Energy Conference, ENERGYCON 2016, Leuven, Belgium, 4/4/16. https://doi.org/10.1109/ENERGYCON.2016.7513915

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author = "Mohamed Arikiez and Floriana Grasso and Dariusz Kowalski and Michele Zito",

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Y1 - 2016/7/14

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AB - This paper investigates using heuristic algorithms to solve Multi-Objective Optimization Problem (MOOP). The primary goal is to minimize the electricity cost for a set of air conditioners in residential or commercial buildings. The second objective is to minimize the discomfort factor. The algorithm, also, enhances the utilization of local renewable power. This allocation problem can be formulated using a static technique such as Mixed Integer Linear Programming (MILP), but solving MILP-based MOOP could be impracticable in heavy problems due to the hardness of the problem. Accordingly, a trade-off between cost and runtime is required. Our algorithm uses an MILP-based heuristic algorithm and LP relaxation and an innovative rounding technique called, Minimum Deviation Rounding (MDR) to get a sub-optimal solution. The result reveals that our algorithm can solve a massive problem in few seconds and gives a superb sub-optimal solution.

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KW - smart grid

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Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this