Abstract
In recent years, optimization-based design techniques are proposed for urban PV systems. These systems are subject to an inter-play of shading and self-consumption issues such that it makes sense to determine the functional capacity and positioning for the system before to simulate it. This study analyzes the effectiveness of one optimization approach and matches it against traditional dimensioning methods. Three design methods are described and compared to an ideal design: the minimum capacity required by the current Italian law, the PV capacity whose annual cumulative production equals the cumulative demand of the building and an optimization technique using a constant energy demand. The methods were all tested on a residential building located in Firenze (Italy). The case study is currently undergoing energy refurbishment for experimental purposes within H2020 EnergyMatching project. The results show that the optimization approach outperforms the other methods despite the simplified input data. The optimization method, even when fed simplified data, still leads to an improvement of NPV (Net Present Value) up to +85% compared to the other methods and can achieve >93% of the actual optimum. In countries where net billing (or net metering) incentives are still in place the optimization technique is not so vital.