Nowadays, we are moving forward to more sustainable societies, where a crucial issue consists in reducing footprint and greenhouse emissions. This transition can be achieved by increasing the penetration of distributed renewable energy sources together with a smarter use of energy. To achieve it, new tools are needed to plan the deployment of such renewable systems by modeling variability and uncertainty of their generation profiles. In this paper, we present a distributed software infrastructure for modeling and simulating energy production of photovoltaic (PV) systems in urban context. In its core, it performs simulations in a spatio-temporal domain exploiting geographic information systems together with meteorological data to estimate PV generation profiles in real operating conditions. This solution provides results in real-sky conditions with different time intervals: yearly, monthly, and subhourly. To evaluate the accuracy of our simulations, we tested the proposed software infrastructure in a real-world case study. Finally, experimental results are presented and compared with real energy production data collected from PV systems deployed in the case study area.
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Bottaccioli et al. (2017) studied this question.
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