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Open AccessEditor’s ChoiceArticle

Optimizing Energy Consumption in the Home Energy Management System via a Bio-Inspired Dragonfly Algorithm and the Genetic Algorithm

1
Faculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan
2
Endicott College of International Studies, Woosong University, Daejeon 300-718, Korea
3
Department of Electronics Engineering, Hankuk University of Foreign Studies, Yongin 17035, Korea
*
Authors to whom correspondence should be addressed.
Electronics 2020, 9(3), 406; https://doi.org/10.3390/electronics9030406
Received: 13 January 2020 / Revised: 5 February 2020 / Accepted: 15 February 2020 / Published: 28 February 2020
(This article belongs to the Special Issue Transforming Future Cities: Smart City)
Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the world have taken a keen interest in this issue and finally introduced the concept of the smart grid. Smart grid is an ultimate solution to all of the energy related problems of today’s modern world. In this paper, we have proposed a meta-heuristic optimization technique called the dragonfly algorithm (DA). The proposed algorithm is to a real-world problem of single and multiple smart homes. In our system model, two classes of appliances are considered; Shiftable appliances and Non-shiftable appliances. Shiftable appliances play a significant role in demand side load management because they can be scheduled according to real time pricing (RTP) signal from utility, while non-shiftable appliances are not much important in load management, as these appliances are fixed and cannot be scheduled according to RTP. On behalf of our simulation results, it can be concluded that our proposed algorithm DA has achieved minimum electricity cost with a tolerable waiting time. There is a trade-off between electricity cost and waiting time because, with a decrease in electricity cost, waiting time increases and vice versa. This trade-off is also obtained by our proposed algorithm DA. The stability of the grid is also maintained by our proposed algorithm DA because stability of the grid depends on peak-to-average ratio (PAR), while PAR is reduced by DA in comparison with an unscheduled case. View Full-Text
Keywords: optimization; demand side management; demand response; dragonfly algorithm; energy management controller; energy management system; genetic algorithm; smart meter; smart grid; traditional grid; peak to average ratio optimization; demand side management; demand response; dragonfly algorithm; energy management controller; energy management system; genetic algorithm; smart meter; smart grid; traditional grid; peak to average ratio
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Hussain, I.; Ullah, M.; Ullah, I.; Bibi, A.; Naeem, M.; Singh, M.; Singh, D. Optimizing Energy Consumption in the Home Energy Management System via a Bio-Inspired Dragonfly Algorithm and the Genetic Algorithm. Electronics 2020, 9, 406.

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