Application of agglomerative hierarchical clustering and logistic model development for assessing solar energy acceptability as an alternate energy option

Abstract

This paper is focused on the assessment of acceptability of solar energy as an alternate efficient energy management option using Agglomerative Hierarchy Cluster (AHC) and logistic regression modelling approach. The study population includes randomly selected shop-owners and residential occupants within the Port Harcourt city in Rivers State, Nigeria. The collected data sets were subjected to AHC analysis using a statistical package XLSTAT 2016 version 4.6. The central object identified from the application of AHC with respect to the sampled shop-owners and residential occupants as pertaining to the acceptability of solar energy as an alternate efficient energy management option was centered around the financial implication of energy generation and the political influence of the government solar energy policies for energy generation. Finally, logistic regression modelling approach was applied into developing a predictive model for the probability of general acceptance (variable ‘yes’) of solar energy as an effective energy management system. From the developed model the chance of acceptance of a solar energy management system is 1% with 59.5% rejection from the study population while it is 99% with an unawareness level of 40.51% from the study population.