Grid-connected low voltage photovoltaic power plants cover most of the power capacity installed in Italy. They offer an important contribution to the power demand of the utilities connected but, due to the nature of the solar resource, the night-time consumption can be satisfied only withdrawing the energy by the national grid, at the price of the energy distributor. Thanks to the improvement of storage technologies, the installation of a system of battery looks like a promising solution by giving the possibility to increase auto-consumption dramatically. In this paper, a model-based approach to analyze and discuss the performance and the economic feasibility of grid-connected domestic photovoltaic power plants with a storage system is presented. Using as input to the model the historical series (2008–2017) of the main ambient variables, the proposed model, based on Stochastic Hybrid Fault Tree Automaton, allowed us to simulate and compare two alternative technical solutions characterized by different environmental conditions, in the north and in the south of Italy. The performances of these systems were compared and an economic analysis, addressing the convenience of the storage systems was carried out, considering the characteristic useful-life time, 20 years, of a photovoltaic power plant. To this end the Net Present Value and the payback time were evaluated, considering the main characteristics of the Italian market scenario.

The contribution of renewable energies to the reduction of the impact of fossil fuels sources and especially energy supply in remote areas has occupied a role more and more important during last decades. The estimation of renewable power plants performances by means of deterministic models is usually limited by the innate variability of the energy resources. The accuracy of energy production forecasting results may be inadequate. An accurate feasibility analysis requires taking into account the randomness of the primary resource operations and the effect of component failures in the energy production process. This paper treats a novel approach to the estimation of energy production in a real photovoltaic power plant by means of dynamic reliability analysis based on Stochastic Hybrid Fault Tree Automaton (SHyFTA). The comparison between real data, deterministic model and SHyFTA model confirm how the latter better estimate energy production than deterministic model.

This paper focuses on the analysis of the energy production of building integrated photovoltaic systems. All the PV systems are located in the south part of Italy - Sicily. A comparison has been made between two different conversion technologies: string-inverter versus micro-inverter.The two string-inverter systems analyzed have different azimuth angle, no shadowing, different peak power and different types of photovoltaic modules (monocrystalline and polycrystalline silicon). The four micro-inverter systems have different shadowing percentage, different azimuth. All systems have fixed tilt angle and fixed azimuth angle. The experimental data were treated for almost one year. In order to analyze the performance of the systems, the most common Indexes (the Energy Yield Yf, the Reference Yield YR, the Performance Ratio PR and Efficiency η) have been used. This allowed to obtain a correct comparison even with different Irradiance values and different Peak Powers.The main goal of the analysis has been to evaluate the performances of the micro-inverter systems at different shadowing conditions. The results of the comparison have confirmed that micro-inverter systems present better performances both at shadowed and “not-shadowed” conditions.By comparing not-shadowed systems with the two different conversion technologies and similar azimuth and tilt angle it has been shown how, with almost the same values of Irradiance, micro-inverter systems maximize the energy production.Furthermore, the highest percentage of produced energy could justify the more expensive cost of this new conversion technology