Research Area:  Metaheuristic Computing

Abstract:

Renewable energy sources are freely available, pollution free and their application is increasing rapidly. The main requirement of hybrid renewable energy system (HES) is proper sizing because renewable sources are intermittent in nature. A bi-objective model has been developed for optimal sizing of stand-alone HES. The problem formulation considers minimization of levelized cost of energy and maximization of emission curtailment. This complex problem is optimized using a new population based powerful metaheuristic, tunicate swarm algorithm (TSA). Tests are also carried out for single objective optimization of stand-alone and grid connected configurations. It has been observed that a grid-connected setup is more economical and reliable as compared to stand-alone HES. A brief comparison of TSA with popular metaheuristic methods and traditional solver is carried out.

Keywords:  
Hybrid energy system (HES)
Tunicate swarm algorithm (TSA)
Levelized cost of energy (LCE)
Emission curtailment (EMC)
Differential evolution (DE) Particle swarm optimization (PSO)

Author(s) Name:  Poonam Singh; Manjaree Pandit; Laxmi Srivastava

Publisher name:  IEEE

DOI:  10.1109/ICEPES52894.2021.9699525

Volume Information:  

Paper Link:   https://ieeexplore.ieee.org/abstract/document/9699525