Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control

Alexandra Falcón-Mendoza; Sebastián Velásquez; Mayra Pacheco-Cunduri; Jorge Hernández-Ambato; Esteban Guevara-Cabezas; Victor Herrera-Perez

doi:10.1007/978-3-031-73921-7_22

Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control

Alexandra Falcón-Mendoza
, Sebastián Velásquez
, Mayra Pacheco-Cunduri
, Jorge Hernández-Ambato
, Esteban Guevara-Cabezas
, Victor Herrera-Perez^*

^*Autor correspondiente de este trabajo

Montebello Academy
Universidad de Sevilla
Escuela Superior Politécnica de Chimborazo

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

This paper presents the design of a fuzzy-based energy management strategy (EMS) which considers a sliding forward window approach to estimate the future energy generated (by a 4 kWp photovoltaic system) and consumed (by a group of lighting loads). The EMS was validated under different solar generation conditions (sunny, cloudy and rainy) and load consumption scenarios. Based on the operation of the proposed fuzzy-based EMS, a current setpoint was determined for the charge/discharge of the battery and applied as control target in the inverter of the photovoltaic (PV) installation. The experimental results showed that, applying the proposed setpoint, the autonomy of the battery can increase in around 85% from the operation with the default control.

Idioma original	Inglés
Título de la publicación alojada	ELECTRIMACS 2024 - Selected Papers
Editores	Enrique Belenguer, Hector Beltran
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	275-290
Número de páginas	16
ISBN (versión impresa)	9783031739200
DOI	https://doi.org/10.1007/978-3-031-73921-7_22
Estado	Publicada - 2025
Evento	International Conference of the TC Electrimacs Committee, ELECTRIMACS 2024 - Castelló de la Plana, Espana Duración: 27 may 2024 → 30 may 2024

Serie de la publicación

Nombre	Lecture Notes in Electrical Engineering
Volumen	1275 LNEE
ISSN (versión impresa)	1876-1100
ISSN (versión digital)	1876-1119

Conferencia

Conferencia	International Conference of the TC Electrimacs Committee, ELECTRIMACS 2024
País/Territorio	Espana
Ciudad	Castelló de la Plana
Período	27/05/24 → 30/05/24

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 7: Energía asequible y no contaminante

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10.1007/978-3-031-73921-7_22

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Falcón-Mendoza, A., Velásquez, S., Pacheco-Cunduri, M., Hernández-Ambato, J., Guevara-Cabezas, E., & Herrera-Perez, V. (2025). Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control. En E. Belenguer, & H. Beltran (Eds.), ELECTRIMACS 2024 - Selected Papers (pp. 275-290). (Lecture Notes in Electrical Engineering; Vol. 1275 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-73921-7_22

Falcón-Mendoza, Alexandra ; Velásquez, Sebastián ; Pacheco-Cunduri, Mayra et al. / Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control. ELECTRIMACS 2024 - Selected Papers. editor / Enrique Belenguer ; Hector Beltran. Springer Science and Business Media Deutschland GmbH, 2025. pp. 275-290 (Lecture Notes in Electrical Engineering).

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title = "Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control",

abstract = "This paper presents the design of a fuzzy-based energy management strategy (EMS) which considers a sliding forward window approach to estimate the future energy generated (by a 4 kWp photovoltaic system) and consumed (by a group of lighting loads). The EMS was validated under different solar generation conditions (sunny, cloudy and rainy) and load consumption scenarios. Based on the operation of the proposed fuzzy-based EMS, a current setpoint was determined for the charge/discharge of the battery and applied as control target in the inverter of the photovoltaic (PV) installation. The experimental results showed that, applying the proposed setpoint, the autonomy of the battery can increase in around 85\% from the operation with the default control.",

author = "Alexandra Falc{\'o}n-Mendoza and Sebasti{\'a}n Vel{\'a}squez and Mayra Pacheco-Cunduri and Jorge Hern{\'a}ndez-Ambato and Esteban Guevara-Cabezas and Victor Herrera-Perez",

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Falcón-Mendoza, A, Velásquez, S, Pacheco-Cunduri, M, Hernández-Ambato, J, Guevara-Cabezas, E & Herrera-Perez, V 2025, Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control. En E Belenguer & H Beltran (eds.), ELECTRIMACS 2024 - Selected Papers. Lecture Notes in Electrical Engineering, vol. 1275 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 275-290, International Conference of the TC Electrimacs Committee, ELECTRIMACS 2024, Castelló de la Plana, Espana, 27/05/24. https://doi.org/10.1007/978-3-031-73921-7_22

Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control. / Falcón-Mendoza, Alexandra; Velásquez, Sebastián; Pacheco-Cunduri, Mayra et al.
ELECTRIMACS 2024 - Selected Papers. ed. / Enrique Belenguer; Hector Beltran. Springer Science and Business Media Deutschland GmbH, 2025. p. 275-290 (Lecture Notes in Electrical Engineering; Vol. 1275 LNEE).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control

AU - Falcón-Mendoza, Alexandra

AU - Velásquez, Sebastián

AU - Pacheco-Cunduri, Mayra

AU - Hernández-Ambato, Jorge

AU - Guevara-Cabezas, Esteban

AU - Herrera-Perez, Victor

PY - 2025

Y1 - 2025

N2 - This paper presents the design of a fuzzy-based energy management strategy (EMS) which considers a sliding forward window approach to estimate the future energy generated (by a 4 kWp photovoltaic system) and consumed (by a group of lighting loads). The EMS was validated under different solar generation conditions (sunny, cloudy and rainy) and load consumption scenarios. Based on the operation of the proposed fuzzy-based EMS, a current setpoint was determined for the charge/discharge of the battery and applied as control target in the inverter of the photovoltaic (PV) installation. The experimental results showed that, applying the proposed setpoint, the autonomy of the battery can increase in around 85% from the operation with the default control.

AB - This paper presents the design of a fuzzy-based energy management strategy (EMS) which considers a sliding forward window approach to estimate the future energy generated (by a 4 kWp photovoltaic system) and consumed (by a group of lighting loads). The EMS was validated under different solar generation conditions (sunny, cloudy and rainy) and load consumption scenarios. Based on the operation of the proposed fuzzy-based EMS, a current setpoint was determined for the charge/discharge of the battery and applied as control target in the inverter of the photovoltaic (PV) installation. The experimental results showed that, applying the proposed setpoint, the autonomy of the battery can increase in around 85% from the operation with the default control.

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DO - 10.1007/978-3-031-73921-7_22

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BT - ELECTRIMACS 2024 - Selected Papers

A2 - Belenguer, Enrique

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ER -

Falcón-Mendoza A, Velásquez S, Pacheco-Cunduri M, Hernández-Ambato J, Guevara-Cabezas E, Herrera-Perez V. Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control. En Belenguer E, Beltran H, editores, ELECTRIMACS 2024 - Selected Papers. Springer Science and Business Media Deutschland GmbH. 2025. p. 275-290. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-3-031-73921-7_22

Design and Validation of an Optimized Energy Management Strategy for an Off-Grid PV System Based on an Adaptive Fuzzy Control

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