Gender mediated optimal multivariate electricity load management model

Abstract

Electricity load management embraces optimal power generation, transmission, distribution and utilisation, while demand-side management considers electricity consumption after the meter. Multivariate analysis uses Wilks' lambda, Pillai's trace, Hotelling's trace and Roy's largest eigenvalue to obtain multidimensional additive linear equations. A load management questionnaire having 54 predictors was randomly distributed to around 300 residents in a Windhoek suburb. The 127 questionnaire responses were analysed using statistical package for social sciences. Results indicate there was no statistical difference between predictors. Low Wilks' lambda values show substantial differences exist across gender in attitude towards optimal electricity load management and females were less likely to use electricity optimally. It is recommended for least costs and minimal resources deployment in power utilities that, the female gender is sensitised, encouraged and urged to adopt optimal multivariate electricity load management strategies proposed in this study for affordable and sustainable electricity generation, supply, utilisation, growth and overall development.