Abstract
Solar photovoltaic (PV) is a promising and effective energy generation resource to produce on-site electricity that covers part of buildings’ demand on urban scales. Design optimization is identified as a proper approach to improve PV systems' techno-economic feasibility and tackle the challenges of exchanging electricity with the grid. This study uses a multi-objective optimization approach to find the optimum PV system design that generates electricity based on the aggregated demand pattern of commercial buildigs. The goal is to improve the correlation between the PV electricity production and demand patterns by optimizing the PV panels’ range of orientations and the number of panels on each orientation. The PV system is optimized to in a way to maximize self-consumption (SC) and self-sufficiency (SS), and minimize payback period (PB) and load variance over the grid. The optimization objectives are examined in four different scenarios for commercial buildings located in the downtown Los Angeles, California. The results show that the demand pattern of commercial neighborhoods is somehow flat and has no spikes. Thus, the production pattern of optimum PV systems will be normally distributed around noon, with slightly higher production in the afternoon. While the system size is dependent on the objectives considered in the optimization, considering multiple objectives simultaneously leads to beneficial and reasonable results. The SS values obtained in all optimization scenarios range between 4.4 and 44.1 %, the SC ranges between 84.9 and 100 %, the PB is between 8.55 and 14.7 years, and the RMSD ranges between 1652 and 2418 KW/h. In addition to PV system optimization, the results indicate the importance of finding the optimum energy storage system for a better match between the demand and supply profiles.