Efficient Electricity Consumption Scheduling for Residential Load Integrated with Renewable Energy Resource in Smart Grid
Ranjini A1, B.S.E. Zoraida2

1Ranjini A*, Research Scholar, School of Computer Science, Engineering and Applications, Bharathidasan University, India.
2B.S.E.Zoraida2 , Assistant Professor, School of Computer Science, Engineering and Applications, Bharathidasan University, India.

Manuscript received on October 16, 2019. | Revised Manuscript received on 27 October, 2019. | Manuscript published on November 10, 2019. | PP: 4199-4208 | Volume-9 Issue-1, November 2019. | Retrieval Number: A6116119119/2019©BEIESP | DOI: 10.35940/ijitee.A6116.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Satisfying consumer’s electricity demand at peak hours is an important problem in smart grid. From the perspective of consumers, the residential electricity consumption scheduling would aim to minimize the electricity cost and also wish to maintain their comfort. In contrast, the power utilities concentrate on to flatten the peak loads in the electricity demand. In this paper, both the viewpoints are taken into consideration while scheduling the residential appliances in smart grid. The Self Adaptive Mutated Particle Swarm Optimization Algorithm is proposed for solving the above problem. Simulations have been carried out and the results are compared with the NonDominated Sorting Genetic Algorithm II. From the results obtained, it is clearly proved that the proposed algorithm provides better schedules for the smart home, with minimized electricity cost and least Peak-to-Average Value whereas maximizing the user comfort. Moreover, the proposed algorithm shows its effectiveness with the increase in problem size.
Keywords: Scheduling Problem, Self Adaptive Mutated Particle Swarm Optimization, Smart Grid, Heuristic Algorithm.
Scope of the Article: Algorithm Engineering