Version 1
: Received: 15 July 2024 / Approved: 15 July 2024 / Online: 15 July 2024 (12:49:52 CEST)
How to cite:
Žigman, D.; Tvorić, S.; Lonić, M. Comparative PSO Optimization of Microgrid Management Models in Island Operation to Minimise Cost. Preprints2024, 2024071174. https://doi.org/10.20944/preprints202407.1174.v1
Žigman, D.; Tvorić, S.; Lonić, M. Comparative PSO Optimization of Microgrid Management Models in Island Operation to Minimise Cost. Preprints 2024, 2024071174. https://doi.org/10.20944/preprints202407.1174.v1
Žigman, D.; Tvorić, S.; Lonić, M. Comparative PSO Optimization of Microgrid Management Models in Island Operation to Minimise Cost. Preprints2024, 2024071174. https://doi.org/10.20944/preprints202407.1174.v1
APA Style
Žigman, D., Tvorić, S., & Lonić, M. (2024). Comparative PSO Optimization of Microgrid Management Models in Island Operation to Minimise Cost. Preprints. https://doi.org/10.20944/preprints202407.1174.v1
Chicago/Turabian Style
Žigman, D., Stjepan Tvorić and Manuel Lonić. 2024 "Comparative PSO Optimization of Microgrid Management Models in Island Operation to Minimise Cost" Preprints. https://doi.org/10.20944/preprints202407.1174.v1
Abstract
The rapid progress in renewable energy sources and the increasing complexity of energy distribution networks have highlighted the need for efficient and intelligent energy management systems. This paper presents a comparative analysis of two optimisation algorithms, P and M70, used for the optimal control of the operation of microgrids in islanded mode. The main objective is to minimise production costs while ensuring a reliable energy supply. Algorithm P prioritises the use of photovoltaic (PV) and battery storage and operates the diesel generator at minimum capacity to reduce fuel consumption and maximise the use of renewable energy sources. Algorithm M70, on the other hand, uses a heuristic approach to adaptively manage energy resources in real time. In this study, the performance of both algorithms is evaluated through simulation in different operating scenarios. The results show that both algorithms significantly improve the efficiency of the microgrid, with the M70 algorithm showing better adaptability and cost efficiency in dynamic environments. This research contributes to ongoing efforts to develop robust and scalable energy management systems for future smart grids.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
