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A wide range of electronic equipment uses Uninterruptible Power System units in order to continue operating in case there is loss of power supply. Due to their battery, the Uninterruptible Power Systems guarantee that the electronic device will operate autonomously for a certain period of time. In this work, an automatic charger/regulator circuit for a lead-acid battery is developed. The charger/regulator circuit consists of the battery charger, the electronic circuit that supplies the load with DC voltage and the circuit that protects the battery from deep discharge.The specifications of the aforementioned circuit are appropriate for the DC voltage supply of a pharos's lighting device (fluorescent lamps). The charger/regulator circuit charges the battery via the 230V AC mains voltage in order to supply the lighting device (load) with 12V DC. In case the mains voltage is interrupted, the battery continues to supply the load with 12V DC. The battery stops to supply the load when its voltage becomes less than 9.5V, in order to avoid damage due to deep discharge. Index Terms -Uninterruptible Power Supply (UPS),Battery's protection.

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During the last decades, renewable energy sources (RES) have been established as one of the main solutions in coping with the future energy needs, without the negative effects caused by the use of fossil fuels. The exploitation of RES however, faces serious difficulties concerning the penetration limits in the electrical grid due to its stochastic and variable availability. One of the main parameters affecting the reliability of the RES system, compared to the local conventional power station, is the ability to forecast the RES availability for a few hours ahead. The main goal of this work is the forecasting of global solar irradiation (GSI) on an horizontal plane, in hourly bases, 24hours ahead based only on historical meteorological data and artificial neural networks (ANN) modeling techniques. For that purpose, appropriate meteorological data have been recorded on minute intervals by a meteorological mast installed in Tilos Island, Greece from 17/03/2015 up to 20/12/2015. According to the forecasting results, the coefficient of determination ranges between 0.500 and 0.851 as well as the root mean square error ranges between 0.065kWh/m 2 and 0.105kWh/m 2. Finally, the proposed forecasting ANN model shows a fairly good forecasting ability which is crucial for a better management of solar energy systems.