Benchmarking performance of photovoltaic power plants in multiple periods

There is a general consensus about the performance of photovoltaic plants particularly on their efficiency benefits. However, it is not clear to what extents such efficiencies correlate with the efficient frontier of performance when such plants are evaluated under varying geospatial environmental factors and over intertemporal periods. This study carries out a performance benchmarking exercise on photovoltaic power stations. It employs a non-parametric modelling technique in the form of Data Envelopment Analysis to evaluate the performance over time of three photovoltaic power plants within an electric utility. It presents an optimization modelling approach for performance benchmarking over time under situations where there are a limited number of decision-making units. Specifically, the study introduces a multi-period modeling approach which employs real data and captures actual variabilities in environmental factors that influence the output of photovoltaic power plants over time. In comparing the deterministic approach often employed in the extant literature with the multi-period model, the results reveal that the deterministic model overestimates the efficiency values and underestimates the output targets relative to a unit operating on the efficient frontier. The study further employs non-parametric statistical techniques and post-hoc tests to validate the findings.