Optimal sizing of a hybrid solar energy system using particle swarm optimization algorithm based on cost and pollution criteria

Abstract

Sizing of hybrid energy systems is primarily determined based on either cost criterion or produced pollution criterion. Optimization of a hybrid energy system for a typical house in Tunisia is investigated using particle swarm optimization (PSO). To the best of our knowledge, PSO algorithm has not been used for PV/batteries bank/diesel generator energy system optimization. Different parameters—namely, cost, required maintenance of the parts, lifetime of each components, and pollution produced by the diesel generator—are investigated simultaneously as objectives for optimal design of the hybrid system. Different designs are considered for the hybrid system where CO2 emission is measured and system total cost is calculated. It is crucial to choose proper ranges of the parameters used in the PSO algorithm to achieve stable and global optimal solution. It is found that the cost of the system optimized using minimum pollution criterion has about 0.3% extra overall cost compared to the system optimized using minimum overall system cost criterion.New and simple method is proposed in this work to select the range of the PV panels' number to achieve optimal solution of PSO algorithm. This method is based on calculating the number of PV panels under different conditions of solar radiation and load values. The considered conditions are maximum solar radiation, 50% of maximum radiation, and the radiation at 9:00 AM for maximum and minimum load values. The choice of these conditions was arbitrary and contemplated to cover a wide range of different possible solar radiation in the year. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13055, 2019