Optimized control of industrial microgrid energy storage using particle swarm techniques

• Autorzy: Kaczorowska Dominika , Rezmer Jacek , Kostyła Paweł , Sikorski Tomasz

Identyfikatory

DOI

10.24425/aee.2025.154988

• Języki publikacji: EN

Abstrakty

EN

Renewable energy sources have rapidly developed over the past few years. The stochastic nature of the generated energy in photovoltaic systems (PV) and wind power plants is causing more interest in energy storage systems (ESS). In commercial installations, deterministic methods are used to control the power of the storage, which is not efficient. Developing algorithms that optimize economic and technical aspects is necessary. Methods based on computational intelligence (CI) can be a solution. The paper presents a novel CI algorithm for optimizing power flow in microgrids using the particle swarm optimization (PSO) method. The economic and technical efficiency of control is achieved by combining multiple criteria in the objective function. The solution is universal, scalable, and can be applied to any industrial or residential microgrid. The method uses short-term forecasts of local generation and load and specifications of ESS, ensuring that technological constraints are maintained. Analyses were conducted for a whole year for a real industrial microgrid. The paper presents the selected results of the study. The efficiency of the proposed algorithm is compared with the results obtained by a deterministic algorithm aimed at maximizing autoconsumption. Using the PSO algorithm resulted in an economic effect of =C6 635 with 461 full discharge cycles, compared to =C2 287 and 110 cycles for the deterministic approach, meaning an increase of more than 2.5 times. However, such storage operation requires more intensive work, affecting its lifetime. Further research can develop objective functions that, without compromising economic effects, support microgrid operation: improving power quality, minimizing voltage fluctuations.

Słowa kluczowe

EN

computational intelligence; control optimization; economic efficiency; energy storage system; microgrid

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2025
• Tom: Vol. 74, nr 3
• Strony: 631--652
• Opis fizyczny: Bibliogr 36 poz., rys., tab., wykr., wz.

Twórcy

autor

Kaczorowska Dominika

• Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland

• https://orcid.org/0000-0002-2312-2903

autor

Rezmer Jacek

• Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland

• https://orcid.org/0000-0002-2822-7595

autor

Kostyła Paweł

• Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland

• https://orcid.org/0000-0002-4259-9950

autor

Sikorski Tomasz

• Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland

• https://orcid.org/0000-0002-4423-7216

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).