Consumer-Driven Demand-Side Management Using K-Mean Clustering and Integer Programming in Standalone Renewable Grid

Muhammad Ahsan Ayub, Hufsa Khan, Jianchun Peng and Yitao Liu
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Muhammad Ahsan Ayub: College of Physics and Optoelectronics Engineering, Shenzhen University, Shenzhen 518000, China
Hufsa Khan: College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518000, China
Jianchun Peng: College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518000, China
Yitao Liu: College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518000, China

Energies, 2022, vol. 15, issue 3, 1-17

Abstract: Many countries have larger land areas and scattered communities. Therefore, to electrify them, small standalone power systems are the more preferred and cost-efficient solution as compared to utility grid extensions. The main objective of a standalone power system is to supply cleaner, cheaper, and uninterrupted electricity. However, for standalone power systems, demand-side management always remains a challenging task. In this paper, a load scheduling algorithm driven by K-mean clustering and linear integer programming to schedule consumers’ appliances for the upcoming day is proposed. In addition, the basic power to run the necessary appliances is kept available in the system all the time. Furthermore, to assist the consumer in every situation, the battery storage system and the overall system size reduction are also taken into consideration. Consumer input is also used in scheduling the appliances. The proposed method is evaluated on the publicly available real-world dataset; the simulation results demonstrate that the proposed approach performs better, due to which the reliability and continuity of the system are increased.

Keywords: standalone hybrid renewable energy system; K-mean clustering; demand-side management; demand response (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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