TY - GEN

T1 - Heuristic algorithm for minimizing the electricity cost of air conditioners on a smart grid

AU - Arikiez, Mohamed

AU - Grasso, Floriana

AU - Kowalski, Dariusz

AU - Zito, Michele

N1 - Publisher Copyright:
© 2016 IEEE.

PY - 2016/7/14

Y1 - 2016/7/14

N2 - 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.

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.

KW - Demand-side management

KW - heating ventilation and air conditioning

KW - heuristic algorithm

KW - smart grid

UR - http://www.scopus.com/inward/record.url?scp=84982786499&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84982786499&partnerID=8YFLogxK

U2 - 10.1109/ENERGYCON.2016.7513915

DO - 10.1109/ENERGYCON.2016.7513915

M3 - Conference contribution

AN - SCOPUS:84982786499

T3 - 2016 IEEE International Energy Conference, ENERGYCON 2016

BT - 2016 IEEE International Energy Conference, ENERGYCON 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Energy Conference, ENERGYCON 2016

Y2 - 4 April 2016 through 8 April 2016

ER -