Battery Size Optimization With Customer PV Installations and Domestic Load Profile

Photovoltaic (PV) is a highly feasible solution for modern renewable energy-powered residential buildings in terms of deployment and cost reduction of utility bills. The installation of solar PV systems along with optimal battery energy storage systems (BESS) size is the most popular energy cost minimization solution and will continue to increase rapidly in the coming years considering the European Union (EU) framework for nearly zero energy buildings (nZEBs). The current methods lack BESS size optimization and a comprehensive solution to charge/discharge BESS from PV and the grid. The main goal is to be self-sufficient and sustainable while having minimal dependence on the electrical grid. Therefore, this paper presents an efficient energy management model and optimal size of the BESS as two key factors to effectively minimize the total energy consumption cost of the nZEBs while having a minimum dependence on the grid. The energy management system is developed using linear programming and solved using simplex and interior-point methods. In addition, a heuristic algorithm is presented to determine the optimized charging and discharging schedule for nZEBs. A detailed techno-economic analysis of the proposed system is conducted for the whole year (covering all four seasons summer, winter, spring, and autumn) considering three common residential building cases and three different electricity pricing methods. We determined that seasonal electricity pricing is the favorable and economical option to schedule charging and discharging of BESS from the grid in several terms such as, minimum total hours of grid usage, the maximum number of charging hours of BESS from the solar PV system, maximum BESS discharging hours to sell energy, the minimum number of BESS charging hours from the grid, maximum number of discharging hours for energy usage within nZEBs, maximum revenue earned, and peak electrical load reduction for the grid.

Automated summary

This paper presents an efficient energy management model and optimal size of the BESS as two key factors to effectively minimize the total energy consumption cost of the nZEBs while having a minimum dependence on the grid. The system utilizes linear programming and a heuristic algorithm to optimize the charging and discharging schedule for the BESS. A detailed techno-economic analysis is conducted to evaluate the system's performance in different scenarios.