Comparative PSO Optimisation of Microgrid Management Models in Island Operation to Minimise Cost

Dubravko Žigman (), Stjepan Tvorić and Manuel Lonić
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Dubravko Žigman: Department of Electrical Engineering, Zagreb University of Applied Sciences, Konavoska 2, 10000 Zagreb, Croatia
Stjepan Tvorić: Department of Electrical Engineering, Zagreb University of Applied Sciences, Konavoska 2, 10000 Zagreb, Croatia
Manuel Lonić: Department of Electrical Engineering, Zagreb University of Applied Sciences, Konavoska 2, 10000 Zagreb, Croatia

Energies, 2024, vol. 17, issue 16, 1-19

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.

Keywords: microgrid; energy management; optimisation algorithms; predictive control; heuristic approach; renewable energy; islanding; cost minimisation; smart grids (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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