Improving the Load Estimation Process in the Design of Rural Electrification Systems

Jane Namaganda-Kiyimba, Joseph Mutale and Brian Azzopardi
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Jane Namaganda-Kiyimba: Department of Electrical and Electronic Engineering, The University of Manchester, Sackville Street, Manchester M13 9PL, UK
Joseph Mutale: Department of Electrical and Electronic Engineering, The University of Manchester, Sackville Street, Manchester M13 9PL, UK
Brian Azzopardi: Institute of Engineering and Transport, Malta College of Arts, Science and Technology (MCAST), PLA9032 Paola, Malta

Energies, 2021, vol. 14, issue 17, 1-23

Abstract: The design of reliable and sustainable rural electrification systems relies on accurate prediction of the electrical load. This paper evaluates the current methods for load estimation and proposes an improved approach for load estimation for off-grid unelectrified rural communities that yields more accurate estimates. Improved accuracy is mainly due to better modelling of the influence of customer habits and gender on the estimated current and future load using the Markov chain process. A program was developed using MATLAB software to generate load profiles. The results show that gender considerations have a significant impact on load profiles and that the Markov chain process can suitably be used to determine year-to-year load profiles by incorporating the effect of changes in customer habits on the estimated load. The results from the case study on energy consumption in rural community households showed an increase in average daily consumption when gender was considered during load estimation. The peak consumption when gender was considered was about 50% higher than the value for when gender was not considered.

Keywords: customer habits; gender aspects; load estimation; load profiles; rural electrification (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: 2021
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