Design of a Fuzzy Logic Control System for a Battery Energy Storage System in a Photovoltaic Power Plant to Enhance Frequency Stability

The increasing penetration of photovoltaic (PV) generation in power systems is progressively displacing traditional synchronous generators, leading to a significant reduction in the system’s equivalent inertia. This decline undermines the system’s ability to withstand rapid frequency variations, adversely affecting its dynamic stability. In this context, battery energy storage systems (BESS) have emerged as a viable alternative for providing synthetic inertia and enhancing the system’s response to frequency disturbances. This paper proposes the design and implementation of an adaptive fuzzy logic controller aimed at frequency regulation in PV-BESS systems. The controller uses frequency deviation (Δf), rate of change of frequency (ROCOF), and battery state of charge (SOC) as input variables, with the objective of improving the system’s response to frequency variations. The controller’s performance was evaluated through simulations conducted in the MATLAB environment, considering various operating conditions and disturbance scenarios. The results demonstrate that the proposed controller achieves the lowest maximum frequency deviation across all analyzed scenarios when the initial SOC is 50%, outperforming other comparative methods. Finally, compliance with primary frequency regulation (PFR) was verified in accordance with the Technical Procedure PR-21 related to spinning reserve, issued by the Peruvian Committee for Economic Operation of the System.

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Publication Details

Journal
Energies
Published
2025-08-27
DOI
https://doi.org/10.3390/en18174550
Citations
2
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
2.43
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article

Design of a Fuzzy Logic Control System for a Battery Energy Storage System in a Photovoltaic Power Plant to Enhance Frequency Stability

A. R. Silva, Mauro Amaro Pinazo, Jorge Mírez
2 citations
Energies
Microgrid Control and Optimization
2.43
article

Design of a Fuzzy Logic Control System for a Battery Energy Storage System in a Photovoltaic Power Plant to Enhance Frequency Stability

A. R. Silva, Mauro Amaro Pinazo, Jorge Mírez
article en
2 citations

Abstract

The increasing penetration of photovoltaic (PV) generation in power systems is progressively displacing traditional synchronous generators, leading to a significant reduction in the system’s equivalent inertia. This decline undermines the system’s ability to withstand rapid frequency variations, adversely affecting its dynamic stability. In this context, battery energy storage systems (BESS) have emerged as a viable alternative for providing synthetic inertia and enhancing the system’s response to frequency disturbances. This paper proposes the design and implementation of an adaptive fuzzy logic controller aimed at frequency regulation in PV-BESS systems. The controller uses frequency deviation (Δf), rate of change of frequency (ROCOF), and battery state of charge (SOC) as input variables, with the objective of improving the system’s response to frequency variations. The controller’s performance was evaluated through simulations conducted in the MATLAB environment, considering various operating conditions and disturbance scenarios. The results demonstrate that the proposed controller achieves the lowest maximum frequency deviation across all analyzed scenarios when the initial SOC is 50%, outperforming other comparative methods. Finally, compliance with primary frequency regulation (PFR) was verified in accordance with the Technical Procedure PR-21 related to spinning reserve, issued by the Peruvian Committee for Economic Operation of the System.

EnergiesVol. 18(17)
Numerical Method (China) (CN), National University of Engineering (PE), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 10%
Microgrid Control and Optimization
2.43
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Design of a Fuzzy Logic Control System for a Battery Energy Storage System in a Photovoltaic Power Plant to Enhance Frequency Stability — A. R. Silva, Mauro Amaro Pinazo, et al. · Energies (2025) | TGRS Research Map | TGRS