Energy is the fundamental resource, it gives the ability to transform, transport and manufacture
any and all goods and it is vital to the development of any economy. In Nigeria, electricity is one
of the oldest energy forms available for daily activities. It is also, unfortunately, grossly
inadequate to meet the demands of an ever increasing population. This is largely due to
inadequate planning. Efficient energy management necessitates the development and utilization
of an energy plan to ensure a balance between demand and supply with any economy. Energy
analysis is defined as a particular set of procedures for evaluating the total energy requirements
for the supply of a service or project. Energy analysis is an important exercise in the overall
energy systems planning and management. Its relevance lies in the generation of forecasts for
future energy consumption (demand/supply) patterns, and this is the main objective of the
present work. Regression and artificial neural network methods are employed in energy analysis
to determine energy requirements up to 2036. We examine in particular the problems of
Nigeria’s electricity system and based on electricity generation and consumption data we
present a conceptual approach aimed at enhancing electricity generation in the country. The
predicted values of the responses by ANN and regression models were compared and their
closeness with the actual data values was determined.