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All Journal Frontier Energy System and Power Engineering
Tutkun, Nedim
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Control & Systems Engineering Electrical & Electronics Engineering Energy

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Low Cost and Reliable Energy Management in Smart Residential Homes Using the GA Based Constrained Optimization Alsallout, Amjad; Tutkun, Nedim
Frontier Energy System and Power Engineering Vol 2, No 2 (2020): JULY
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v2i2p16-25

Abstract

Recently smart grids have given chance to residential customers to schedule operation times of smart home appliances to reduce electricity bills and the peak-to-average ratio through the demand side management. This is apparently a multi-objective combinatorial optimization problem including the constraints and consumer preferences that can be solved for optimized operation times under reasonable conditions. Although there are a limited number of techniques used to achieve this goal, it seems that the binary-coded genetic algorithm (BCGA) is the most suitable approach to do so due to on/off controls of smart home appliances. This paper proposes a BCGA method to solve the above-mentioned problem by developing a new crossover algorithm and the simulation results show that daily energy cost and peak to average ratio can be managed to reduce to acceptable levels by contributing significantly to residential customers and utility companies.
Home Appliances in the Smart Grid: A Heuristic Algorithm-Based Dynamic Scheduling Model Abuznaid, Anan R.S.; Tutkun, Nedim
Frontier Energy System and Power Engineering Vol 3, No 1 (2021): JANUARY
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v3i1p20-27

Abstract

Customers and power utilities alike will benefit from smart grid technology by lowering energy prices and regulating generating capability. The accuracy of information sharing between main grids and smart meters is critical to the performance of scheduling algorithms. Customers, on the other hand, are expected to plan loads, respond to electricity demand alerts, engage in energy bidding, and constantly track the utility company's energy rates. Consumer loyalty can be improved by strengthening the connectivity infrastructure between the service provider and its customers. We suggest a heuristic demand-side control model for automating the scheduling of smart home appliances in order to optimize the comfort of the customers involved. Simulation findings show that the suggested hybrid solution will reduce the peak-to-average ratio of overall energy demand while still lowering total energy costs without sacrificing consumer convenience
Co-Authors Abuznaid, Anan R.S. Alsallout, Amjad