Measurement of the macro-efficiency of hydropower plants in Nigeria using transfer functions and data envelopment analysis

Persistent power challenges plague Nigeria, with hydropower constituting a vital component of the country's energy mix. This study assessed the macro efficiency of three operational hydropower plants in Nigeria using three distinct methods: Constant Return to Scale Method of Data Envelopment Analysis (DEA-CRS), Input-oriented Variable Return to Scale Method of Data Envelopment Analysis (DEA-VRS), and System's Coefficient of Performance Methodology (SCOPM) employing transfer functions. Input factors included man-hours, plant capacity, and water flow, while energy generation was the output. DEA-VRS revealed Shiroro and Jebba as the most efficient, while Kainji was the least. DEA-CRS indicated Shiroro as the most efficient and Kainji as the least. SCOPM indicated Jebba as the most efficient and Shiroro as the least. SCOPM's higher standard deviation suggests better discrimination among plants. DEA-VRS result showed that the scale of the biggest power plant, Kainji, has some effects on its efficiency. The study recommends the adoption of SCOPM by electricity utility operators and regulators for performance improvement due to its robust results. The contributions of the research are significant because of the novel application of DEA and SCOPM to measure the efficiency of power plants in Nigeria, and SCOPM for measurement of macro efficiency of power plants.