ارزش پیش بینی روزانه برای فتوولتائیک در بازار برق اسپانیا

In this study, we analyze various day-ahead production forecasts for a 1.86 MW photovoltaic plant considering different techniques and sets of inputs. A nRMSE of 22.54% was obtained for a Support Vector Regression model trained by numerical weather predictions (NWP). This model produced the most benefits. An annual forecasting value of 4788€ with respect to a persistence model was obtained for trading in the Iberian (Spain and Portugal) day-ahead electricity market. Annual value added by the NWP service totaled 2801€ and room for improvement regarding NWP variables rose to 3877€. As a general trend, it was found that smaller errors (RMSE) generated higher incomes. For each 1 kW h improvement in RMSE, the annual value of forecasting increased 22.32€. Nevertheless, some models that gave larger errors than others also brought greater benefits. Thus, market conditions must be considered to accurately evaluate model economic performance.