Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago

G. Ampuño-Avilés; R. López-Marcillo; D. Andrade-Núñez

doi:10.1007/978-981-19-6347-6_5

Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago

G. Ampuño-Avilés, R. López-Marcillo, D. Andrade-Núñez

Sustainability, Management And Regulation Of Telecommunications And Energy (SMART-TECH)

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

Resumen

In this paper, an energy management system EMS hourly energy management system for a renewable energy system (HRES) is presented. The proposed HRES is composed of hybrid wind turbine (WT), solar photovoltaic (PV) panels, a diesel generator (DG) and a Distributed Collector System (DCS), as primary energy sources. In turn, an energy storage system (ESS), which is a battery sub-system. The wind turbine, PV panels and DCS system are made to work at peak power, while the battery acts as storage. The EMS uses intelligent rule-based controllers and optimizers to meet the energy demanded by the load and maintain the state of charge (SOC) of the battery between certain target margins, while trying to optimize the utilization cost and lifetime of the BESS. Simulation results show that optimization-based control meets the objectives set for the HRES EMS and achieves a total cost savings of 23.5% over other simpler control state-based EMSs.

Idioma original	Inglés
Título de la publicación alojada	Communication and Applied Technologies - Proceedings of ICOMTA 2022
Editores	Paulo Carlos López-López, Ángel Torres-Toukoumidis, Andrea De-Santis, Óscar Avilés, Daniel Barredo
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	47-57
Número de páginas	11
ISBN (versión impresa)	9789811963469
DOI	https://doi.org/10.1007/978-981-19-6347-6_5
Estado	Publicada - 2023
Evento	International Conference on Communication and Applied Technologies, ICOMTA 2022 - Cuenca, Ecuador Duración: 7 sep. 2022 → 9 sep. 2022

Serie de la publicación

Nombre	Smart Innovation, Systems and Technologies
Volumen	318
ISSN (versión impresa)	2190-3018
ISSN (versión digital)	2190-3026

Conferencia

Conferencia	International Conference on Communication and Applied Technologies, ICOMTA 2022
País/Territorio	Ecuador
Ciudad	Cuenca
Período	7/09/22 → 9/09/22

Nota bibliográfica

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1007/978-981-19-6347-6_5

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Ampuño-Avilés, G., López-Marcillo, R., & Andrade-Núñez, D. (2023). Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago. En P. C. López-López, Á. Torres-Toukoumidis, A. De-Santis, Ó. Avilés, & D. Barredo (Eds.), Communication and Applied Technologies - Proceedings of ICOMTA 2022 (pp. 47-57). (Smart Innovation, Systems and Technologies; Vol. 318). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-6347-6_5

Ampuño-Avilés, G. ; López-Marcillo, R. ; Andrade-Núñez, D. / Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study : San Cristobal Island, Galapagos Archipelago. Communication and Applied Technologies - Proceedings of ICOMTA 2022. editor / Paulo Carlos López-López ; Ángel Torres-Toukoumidis ; Andrea De-Santis ; Óscar Avilés ; Daniel Barredo. Springer Science and Business Media Deutschland GmbH, 2023. pp. 47-57 (Smart Innovation, Systems and Technologies).

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title = "Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago",

abstract = "In this paper, an energy management system EMS hourly energy management system for a renewable energy system (HRES) is presented. The proposed HRES is composed of hybrid wind turbine (WT), solar photovoltaic (PV) panels, a diesel generator (DG) and a Distributed Collector System (DCS), as primary energy sources. In turn, an energy storage system (ESS), which is a battery sub-system. The wind turbine, PV panels and DCS system are made to work at peak power, while the battery acts as storage. The EMS uses intelligent rule-based controllers and optimizers to meet the energy demanded by the load and maintain the state of charge (SOC) of the battery between certain target margins, while trying to optimize the utilization cost and lifetime of the BESS. Simulation results show that optimization-based control meets the objectives set for the HRES EMS and achieves a total cost savings of 23.5% over other simpler control state-based EMSs.",

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Ampuño-Avilés, G, López-Marcillo, R & Andrade-Núñez, D 2023, Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago. En PC López-López, Á Torres-Toukoumidis, A De-Santis, Ó Avilés & D Barredo (eds.), Communication and Applied Technologies - Proceedings of ICOMTA 2022. Smart Innovation, Systems and Technologies, vol. 318, Springer Science and Business Media Deutschland GmbH, pp. 47-57, International Conference on Communication and Applied Technologies, ICOMTA 2022, Cuenca, Ecuador, 7/09/22. https://doi.org/10.1007/978-981-19-6347-6_5

Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago. / Ampuño-Avilés, G.; López-Marcillo, R.; Andrade-Núñez, D.
Communication and Applied Technologies - Proceedings of ICOMTA 2022. ed. / Paulo Carlos López-López; Ángel Torres-Toukoumidis; Andrea De-Santis; Óscar Avilés; Daniel Barredo. Springer Science and Business Media Deutschland GmbH, 2023. p. 47-57 (Smart Innovation, Systems and Technologies; Vol. 318).

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

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T1 - Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study

T2 - International Conference on Communication and Applied Technologies, ICOMTA 2022

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AU - López-Marcillo, R.

AU - Andrade-Núñez, D.

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N2 - In this paper, an energy management system EMS hourly energy management system for a renewable energy system (HRES) is presented. The proposed HRES is composed of hybrid wind turbine (WT), solar photovoltaic (PV) panels, a diesel generator (DG) and a Distributed Collector System (DCS), as primary energy sources. In turn, an energy storage system (ESS), which is a battery sub-system. The wind turbine, PV panels and DCS system are made to work at peak power, while the battery acts as storage. The EMS uses intelligent rule-based controllers and optimizers to meet the energy demanded by the load and maintain the state of charge (SOC) of the battery between certain target margins, while trying to optimize the utilization cost and lifetime of the BESS. Simulation results show that optimization-based control meets the objectives set for the HRES EMS and achieves a total cost savings of 23.5% over other simpler control state-based EMSs.

AB - In this paper, an energy management system EMS hourly energy management system for a renewable energy system (HRES) is presented. The proposed HRES is composed of hybrid wind turbine (WT), solar photovoltaic (PV) panels, a diesel generator (DG) and a Distributed Collector System (DCS), as primary energy sources. In turn, an energy storage system (ESS), which is a battery sub-system. The wind turbine, PV panels and DCS system are made to work at peak power, while the battery acts as storage. The EMS uses intelligent rule-based controllers and optimizers to meet the energy demanded by the load and maintain the state of charge (SOC) of the battery between certain target margins, while trying to optimize the utilization cost and lifetime of the BESS. Simulation results show that optimization-based control meets the objectives set for the HRES EMS and achieves a total cost savings of 23.5% over other simpler control state-based EMSs.

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KW - Fuzzy logic control

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SN - 9789811963469

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Ampuño-Avilés G, López-Marcillo R, Andrade-Núñez D. Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago. En López-López PC, Torres-Toukoumidis Á, De-Santis A, Avilés Ó, Barredo D, editores, Communication and Applied Technologies - Proceedings of ICOMTA 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 47-57. (Smart Innovation, Systems and Technologies). doi: 10.1007/978-981-19-6347-6_5

Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago

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