The potential of publicly available weather forecasts for market operations in aggregated photovoltaic plants

Abstract

Uncertainty in solar generation forecasts affects electricity market operations, forcing producers to bid conservatively and, consequently, reducing the amount of solar energy fed into the grid. This study analyses the potential of aggregated forecasts to reduce the errors of energy generation in medium-sized PV plants. To this objective, publicly available forecasts from the Global Forecasting System were processed with a basic neural network to generate hourly energy forecasts for individual PV plants of 1.1 MW and for the aggregated production of three of them (3.3 MW). The validation was carried out considering typical day-ahead and intraday market horizons, two zones with different atmospheric complexity, and discerning three types of days in terms of the received irradiation. Results show that the aggregation of forecasts would be beneficial as a general strategy in all cases, but especially in the zone of complex atmospheric dynamics and for the day-ahead horizons (36-42 h).