Optimal Demand Side Management in Generation Constrained Power Systems

Azasoo, Julius Quarshie, Kanakis, Triantafyllos, Al-Sherbaz, Ali ORCID: 0000-0002-0995-1262 and Agyeman, Michael Opoku (2020) Optimal Demand Side Management in Generation Constrained Power Systems. In: 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, pp. 29-36. ISBN 9781728140346

Text (Peer Reviewed Version) 9395 Azasoo, J.Q., Kanakis, T., Al-Sherbaz, A., Opoku Agyeman, M. (2019) Optimal-demand-side-management-in-generation-constrained-power-systems.pdf - Accepted Version Restricted to Repository staff only (Publicly available by other means eg published). Available under License All Rights Reserved. Download (1MB)

Abstract

In the face of dwindling generation from hydroelectric generators in most developing countries coupled with a continuous increase in electricity demand is forcing the electric utility companies to effect various demand-side management (DSM). Amongst the DSMs being implemented in these countries is the severe load shedding method that seeks to reduce the overall demand by cutting off sections of a grid resulting in a complete power cut to the affected areas. In this paper, the potential of the smart grid is harnessed to enable microload shedding to avoid a complete cut-off from the grid. Algorithm for efficient allocation of available generation is proposed. Dynamic programming-based algorithms are developed to achieve this constraint by granularly controlling home appliances to reduce the overall demands for electricity by the consumers on the grid. The efficacy of the proposed system is proven by the simulation results obtained.

Item Type:	Book Section
Uncontrolled Keywords:	Demand Side Management; Smart Grid; Smart Metering; Optimisation; Microload Management; Generation Constrained Power Systems
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Kate Greenaway
Date Deposited:	11 Mar 2021 11:23
Last Modified:	01 Sep 2023 12:45
URI:	https://eprints.glos.ac.uk/id/eprint/9395

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