Electricity trading occurs under different mechanisms in each country, with auctions being one of these mechanisms. Auctions are widely used to determine their remuneration in the scope of clean energy technologies, such as photovoltaics. Added to the auction process’s bureaucracies and uncertainties, the competing photovoltaic project must keep its technical and economic performance maximized. Given this context, this study aimed to contribute to the competitiveness of photovoltaic plant projects in energy auctions through a performance diagnosis model to identify, measure, and analyze factors in the designing process. For this, a systematic literature review was performed to identify the factors that influence the implementation of a photovoltaic plant project; additionally, the fuzzy Delphi method was applied to examine the factors’ importance. An analytic hierarchy process weighted the factors, and the key performance indicators were developed based on the literature and regulation of the electric energy sector. The model was applied in a centralized photovoltaic energy generation project, which presented a performance index of 41.91%, and the sensitivity analysis and prioritization matrix comprised the post-application study of the model. Our model can help planners improve the competitiveness of photovoltaic projects in auctions by observing underperforming indicators.
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