This paper analyses the degradation that is experienced by different types of Li-ion batteries when used as home solar storage systems controlled to minimize the electricity bill of the corresponding household. Simulating the annual operation of photovoltaic (PV) residential systems with batteries at different locations was undertaken to perform the study and it uses actual consumption values and real PV production profiles, as well as validated semi-empirical ageing models of the batteries. Therefore, the work provides a realistic prognosis around the lifetime expectancies for the different Li-ion chemistries.

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This work analyses the minimum energy capacity requirements to be demanded to battery energy storage systems used in megawatt-range merchant solar PV plants to grant capacity firming. The operation of such a plant is simulated (with a 2-minute time step, at three different locations of the Iberian Peninsula, and for different battery sizes) after solving a quadratic programming optimization problem. The control algorithm takes into account the irradiance forecast and the intraday electricity market configuration, which presents certain peculiarities in the Iberian region with regard to other European markets. The analysis has been performed in an annual basis and current irradiance measured values have been used.

This paper introduces deep learning-based forecasting models for the continuous prediction of the aggregated production generated by CSP plants in Spain. These models use as inputs the expected top of atmosphere irradiance values and available weather conditions forecasts for the locations where the main CSP power plants are installed. The performances of the forecast models are analysed and compared by means of the most extended metrics in the literature for a whole year of CSP energy production.