The influence of electricity transaction models on the optimal design of PV and PV-BESS systems

A shift toward more deployment of renewable energy resources has been noticed in the residential sector. Solar photovoltaic (PV) systems, supported by battery energy storage systems (BESS), are considered the most used renewable energy resource at urban scales as they utilize the buildings’ roof and facades to install PV panels. In order to better match the PV electricity solar production pattern with buildings’ demand pattern, multi-objective optimization is used in existing studies. This is extremely important in the residential sector as the time of peak solar production does not coincide with the peak demand occurring in the evening. To this end, this study employs a two-phase optimization framework to explore the influence of the different electricity transaction models on the optimal design of PV and PV-BESS systems when performing the optimization process. A residential neighborhood in downtown Los Angeles, California, is used as a case study to find the optimal system in terms of maximum self-consumption (SC) and self-sufficiency (SS) and minimum payback period (BP) and the load variance over the grid. The results indicate that selling surplus electricity to the grid at Time of Use (TOU) rates used in California influences the optimal configuration of PV and PV-BESS systems. Selling surplus electricity results in more PV panels on the south-west orientations and less on the south-east orientations compared to the scenarios that do not consider trading with the grid. Selling surplus production also impacts the optimal number of batteries needed in PV-BESS systems when the decision maker prefers the payback period objective. In some cases, acheiving higher SS is possible using batteries. However, this may lead to unexpected pressure over the grid. This is due to a huge surplus exported to the grid within a short period of time when batteries are fully charged. The results show that using batteries lowers the load variance over the grid in general and achieves the highest percentage of SS. The scenarios in which there are no batteries added to the system and selling surplus PV production is allowed over the grid achieved the least PB. The scenarios in which the batteries are used and the selling of surplus PV is not allowed, achieved the highest percentage of SC.