A Comprehensive Investigation of Optimal Sizing of Hybrid Renewable Energy Resources for Micro Distributed Systems

• Published in: 2023 International Conference on Next Generation Electronics (NEleX) pp. 1 - 7
• Main Authors: Kasi, Shanmuganatha Vadivel, Das, Narottam, Alahakoon, Sanath, Hassan, Nur
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.12.2023
• Subjects: Artificial intelligence; Artificial Intelligence (AI); Distributed Generation; Energy management; Energy resolution; Microgrids; Microgrids (MGs); Optimal Sizing; Power Generation; Reliability; Renewable energy sources; Renewable Energy Sources (RES)
• DOI: 10.1109/NEleX59773.2023.10421117

Renewable Energy Sources (RES) are rapidly increasing for the generation of electrical power due to the high demand for green electrical power and reduced dependency on conventional energy resources. Using the RES is considered to be crucial as they are scalable, eco-friendly, abundant in nature, and can be applied in different applications, such as residential, agriculture, commercial, and industrial areas. It can increase the system's reliability and thus reduce the cost of energy generation. However, the RES demonstrate inadequate load following and are not transportable. This issue can be overcome by implementing a microgrid system that is used to generate, transfer, and store electricity economically and efficiently. The Hybrid Renewable System (HRS) integrated with a microgrid system is considered to be a promising energy source and it is feasible. The primary objective of HRS is an enhancement of aspects to resolve the issues related to optimal sizing of HRS components by considering load supply incessantly. Considering the growing importance of such HRS and the increasing number of research activities, a Systematic Literature Review (SLR) is conducted to investigate the research based on optimal sizing of HRS integrated microgrid distributed generation with a focus on techno-economic reliability. This SLR reveals the articles published during 2019 to 2023. Through the SLR, the features of traditional methods, hybrid algorithms, and Artificial Intelligence (AI) based techniques are assessed and address the recent trends and development of optimal sizing of the HRS integrated microgrid distributed generation.