Eco-economie sizing of autonomous hybrid energy system (AHES) using particle swarm optimization (PSO)

Deployment of distributed energy resources has brought the concept of autonomous hybrid power systems at community levels and remote areas into limelight. In such systems, proper sizing of energy resources at design stage is very crucial to meet energy requirements at minimum cost. Other than technical and economic constraints, system sizing should abide the preservation of environmental interests pertaining to sustainability needs. To investigate this problem, a sizing methodology preserving both economic and environmental interests is proposed in this paper. The problem for component sizing is formulated as an optimization problem with cost minimization objective including both cost and emissions. Particle swarm optimization (PSO) method is then applied to arrive at optimal solution, minimizing the dual objectives i.e., of system cost and embedded emissions. The proposed optimal sizing methodology is simulated for an autonomous hybrid power system renewable energy sources (photovoltaic, wind energy), conventional sources (diesel generator) and energy storage (battery systems). The dual objective function is optimized with different weightages for cost and emissions and the results demonstrates that, mutual exclusive nature of cost and emissions can be addressed with the tradeoff solution.