Paper Info
Title
A Comparative Study of GA and APSO Algorithm for an Optimal Design of a Standalone PV/Battery System
Abstract
Renewable energy consumption is growing by several percent per year, and recent developments in electricity market deregulation require cost management and optimization of generation capacity. For these reasons, an optimal design process for a standalone renewable energy power generation system is recommended in this study. Due to the efficiency of the economic criterion to determine the most optimal configuration size of photovoltaic system, this paper investigates a detailed economic analysis that involves investments, replacements and operation calculating costs. The aim of this paper is to determine the optimal size of stand - alone PV/Battery system with minimum annualized cost using evolutionary optimization approaches. Thus, a comparative study was presented between the Genetic Algorithm (GA) and the Accelerated Particle Swarm Optimization (APSO) algorithm for an optimal sizing of system's components. The economic formulation problem will be, then, implemented using Matlab software and the simulation results will be discussed and compared for these chosen optimization algorithms.
Year
DOI
Venue
2018
10.1109/SSD.2018.8570449
2018 15th International Multi-Conference on Systems, Signals & Devices (SSD)
Keywords
DocType
ISSN
Renewable enrgy,Stand-alone system,Optimal design,Evolutionary algorithms
Conference
2474-0438
ISBN
Citations 
PageRank 
978-1-5386-5306-7
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Mariem Elloumi100.34
Kallel, R.201.01
Boukettaya, G.302.03