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A basic battery management system (BMS) permits the safe charge/discharge of the batteries and the supply of loads. Batteries are protected to avoid fast degradation: the minimum and maximum state-of-charge (SOC) limits are not exceeded and fast charge/discharge cycles are not permitted. A more sophisticated BMS connected to a photovoltaic (PV) generator could also work with the double purpose of protecting storage and reducing peak demand. Peak reduction by storage generally requires the forecast of consumption and PV generation profiles to perform a provisional energy balance. To do it, it is required to have accurate information about production profiles, that is, to have at disposal accurate weather forecasts, which are not easily available. In the present work, an efficient BMS in grid-connected PV plants for residential users is described. Starting from raw 1-day ahead weather forecast and prediction of consumption, the proposed BMS preserves battery charge when it is expected high load and low PV production and performs peak shaving with a negligible reduction in self-sufficiency.

Availability of effective estimation of the power profiles of photovoltaic systems is essential for studying how to increase the share of intermittent renewable sources in the electricity mix of many countries. For this purpose, weather forecasts, together with historical data of the meteorological quantities, provide fundamental information. The weak point of the forecasts depends on variable sky conditions, when the clouds successively cover and uncover the solar disc. This causes remarkable positive and negative variations in the irradiance pattern measured at the photovoltaic (PV) site location. This paper starts from 1 to 3 days-ahead solar irradiance forecasts available during one year, with a few points for each day. These forecasts are interpolated to obtain more irradiance estimations per day. The estimated irradiance data are used to classify the sky conditions into clear, variable or cloudy. The results are compared with the outcomes of the same classification carried out with the irradiance measured in meteorological stations at two real PV sites. The occurrence of irradiance spikes in “broken cloud” conditions is identified and discussed. From the measured irradiance, the Alternating Current (AC) power injected into the grid at two PV sites is estimated by using a PV energy conversion model. The AC power errors resulting from the PV model with respect to on-site AC power measurements are shown and discussed.