Abstract
•This paper considers NSGA-II method for sizing a standalone PV and battery system.•This paper presented techno-economic optimization based on losses of load probability and cost of energy.•The proposed model in this paper includes the Depth of Discharge (DOD) of battery through the determination of battery life loss cost.•The results shows that the proposed method produces high solar PV energy because it involves all potential loss factors and has excellent efficiency according to computation and hourly environmental data for one year.
In this paper, we propose a multi-objective optimization model that considers the loss of load probability (LLP) and the cost of energy (COE) together with the battery life loss cost and the costs of operation, replacement, and maintenance. These factors form the projected operating framework of the off-grid system for which we utilize the non-dominated sorting genetic algorithm (NSGA-II) method. The proposed model includes the depth of discharge (DOD) of the battery, which is determined based on the battery life loss cost. In addition, in the optimal model, the amount of energy flow from the battery bank during the charging and discharging cycles must satisfy the load demand at the lowest cost and with the highest reliability. The results show that the optimal DOD value for a battery in the solar PV system being investigated is 70%, with LLP = 0% and COE = 0.20594 USD/kWh.