Optimal Sizing and Operation of Standalone Power Systems for Remote Industrial Applications

^* New Prince Shri Bhavani college of Engineering and Technology, Anna University .
^† Department of Electrical & Electronics Engineering, IES College of Technology, India 462044. IES University, MP 462044 India, Bhopal, Madhya Pradesh .
^‡ Department of CSE, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai - 127
^§ College of technical engineering, The Islamic university, Najaf, Iraq .
^** Department of Civil Engineering, Uttaranchal Institute of Technology, Uttaranchal University Dehradun-248007, India .
⁶ Associate Professor, Dr. D. Y. Patil Institute of Technology, Pimpri, subhash.gadhave@dypvp.edu.in .

^* Corresponding Author: dhilip.r@newprinceshribhavani.com
^† research@iesbpl.ac.in
^‡ princyrufina_cse@psvpec.in
^§ L.hussien.jasim@gmail.com
^** vinodbalmiki111@gmail.com

Abstract

This paper reviews the work in the areas of optimal sizing and operation of standalone power systems for remote industrial applications. The first study delves into an innovative approach applied to sizing in a hybrid power system, focusing on meeting the demands of a residential area in south-east Iran. This system integrates fuel cells, wind units, electrolysers, a reformer, an anaerobic reactor, and hydrogen tanks, utilizing biomass as an energy resource. The system’s design ensures that power produced from wind turbines and fuel cells meets the demand, with excess power directed to the electrolyser and shortages supplemented by stored hydrogen. The primary objective is cost minimization using the PSO algorithm. The subsequent studies emphasize the accelerated development of eco-friendly technologies shaping the future of electric power generation. They present a methodology for capacity optimization of a residential standalone microgrid, incorporating renewable energy sources, diesel generators, and battery storage systems. The microgrid caters to both typical residential loads and electric vehicle charging demands. Through intricate optimization, the studies aim to minimize costs, reduce greenhouse gas emissions, and limit dump energy. The research also explores the impact of load shifting on distributed generators and storage systems, offering valuable insights for decision-makers and policy developers.