Fuzzy Logic-Based Online Energy Management System for Residential Microgrids

Jingxuan  Wu; Shuting  Li; Yonghao  Gui; Milos Cvetkovic; Juan C.  Vasquez; Josep M. Guerrero

doi:10.1109/IECON51785.2023.10312171

Fuzzy Logic-Based Online Energy Management System for Residential Microgrids

Jingxuan Wu, Shuting Li, Yonghao Gui, Milos Cvetkovic, Juan C. Vasquez, Josep M. Guerrero

Intelligent Electrical Power Grids

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

A fuzzy logic based online energy management system (FLEMS) is designed in this paper to achieve the optimal electricity cost in a residential Microgrid (MG). The proposed FLEMS is combined by a local energy price model (LEPM) and a fuzzy-logic strategy. The LEPM will preprocess the sampling data to estimate the electricity market and local MG status. The fuzzy-logic mimics the artificial intelligent assessment to economic issues and make decision for the charging and discharging operation for energy storage system (ESS). In the FLEMS, not only electricity price and supply-demand balance, but also ESS state of charge are considered for the efficient and stable operations. The proposed method does not relay on the accurate prediction of renewable energy source and local loads. Historical experience of the system is involved by the LEPM and guides the ESS operation in the fuzzy-logic. A real-world data based household-level residential MG model is established to validate the performance of the FLEMS. A hourly-resolution-Particle swarm optimization (PSO) with perfect day-ahead prediction is implemented as the baseline to verify the superiority of the proposed method.

Original language	English
Title of host publication	Proceedings of the IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	979-8-3503-3182-0
ISBN (Print)	979-8-3503-3183-7
DOIs	https://doi.org/10.1109/IECON51785.2023.10312171
Publication status	Published - 2023
Event	IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society - Singapore, Singapore Duration: 16 Oct 2023 → 19 Oct 2023

Publication series

Name	Proceedings of the Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
ISSN (Print)	1553-572X
ISSN (Electronic)	2577-1647

Conference

Conference	IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
Country/Territory	Singapore
City	Singapore
Period	16/10/23 → 19/10/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

EMS
energy storage
electricity cost
fuzzy logic
microgrid

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IECON51785.2023.10312171

Cite this

Wu, J., Li, S., Gui, Y., Cvetkovic, M., Vasquez, J. C., & Guerrero, J. M. (2023). Fuzzy Logic-Based Online Energy Management System for Residential Microgrids. In Proceedings of the IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society). IEEE. https://doi.org/10.1109/IECON51785.2023.10312171

@inproceedings{b8ee7373a8404bfab59eb2274c3bd20f,

title = "Fuzzy Logic-Based Online Energy Management System for Residential Microgrids",

abstract = "A fuzzy logic based online energy management system (FLEMS) is designed in this paper to achieve the optimal electricity cost in a residential Microgrid (MG). The proposed FLEMS is combined by a local energy price model (LEPM) and a fuzzy-logic strategy. The LEPM will preprocess the sampling data to estimate the electricity market and local MG status. The fuzzy-logic mimics the artificial intelligent assessment to economic issues and make decision for the charging and discharging operation for energy storage system (ESS). In the FLEMS, not only electricity price and supply-demand balance, but also ESS state of charge are considered for the efficient and stable operations. The proposed method does not relay on the accurate prediction of renewable energy source and local loads. Historical experience of the system is involved by the LEPM and guides the ESS operation in the fuzzy-logic. A real-world data based household-level residential MG model is established to validate the performance of the FLEMS. A hourly-resolution-Particle swarm optimization (PSO) with perfect day-ahead prediction is implemented as the baseline to verify the superiority of the proposed method.",

keywords = "EMS, energy storage, electricity cost, fuzzy logic, microgrid",

author = "Jingxuan Wu and Shuting Li and Yonghao Gui and Milos Cvetkovic and Vasquez, {Juan C.} and Guerrero, {Josep M.}",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society ; Conference date: 16-10-2023 Through 19-10-2023",

year = "2023",

doi = "10.1109/IECON51785.2023.10312171",

language = "English",

isbn = "979-8-3503-3183-7",

series = "Proceedings of the Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

booktitle = "Proceedings of the IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society",

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Wu, J, Li, S, Gui, Y, Cvetkovic, M, Vasquez, JC & Guerrero, JM 2023, Fuzzy Logic-Based Online Energy Management System for Residential Microgrids. in Proceedings of the IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. Proceedings of the Annual Conference of the IEEE Industrial Electronics Society, IEEE, IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society, Singapore, Singapore, 16/10/23. https://doi.org/10.1109/IECON51785.2023.10312171

Fuzzy Logic-Based Online Energy Management System for Residential Microgrids. / Wu, Jingxuan ; Li, Shuting ; Gui, Yonghao et al.
Proceedings of the IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2023. (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Fuzzy Logic-Based Online Energy Management System for Residential Microgrids

AU - Wu, Jingxuan

AU - Li, Shuting

AU - Gui, Yonghao

AU - Cvetkovic, Milos

AU - Vasquez, Juan C.

AU - Guerrero, Josep M.

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2023

Y1 - 2023

N2 - A fuzzy logic based online energy management system (FLEMS) is designed in this paper to achieve the optimal electricity cost in a residential Microgrid (MG). The proposed FLEMS is combined by a local energy price model (LEPM) and a fuzzy-logic strategy. The LEPM will preprocess the sampling data to estimate the electricity market and local MG status. The fuzzy-logic mimics the artificial intelligent assessment to economic issues and make decision for the charging and discharging operation for energy storage system (ESS). In the FLEMS, not only electricity price and supply-demand balance, but also ESS state of charge are considered for the efficient and stable operations. The proposed method does not relay on the accurate prediction of renewable energy source and local loads. Historical experience of the system is involved by the LEPM and guides the ESS operation in the fuzzy-logic. A real-world data based household-level residential MG model is established to validate the performance of the FLEMS. A hourly-resolution-Particle swarm optimization (PSO) with perfect day-ahead prediction is implemented as the baseline to verify the superiority of the proposed method.

AB - A fuzzy logic based online energy management system (FLEMS) is designed in this paper to achieve the optimal electricity cost in a residential Microgrid (MG). The proposed FLEMS is combined by a local energy price model (LEPM) and a fuzzy-logic strategy. The LEPM will preprocess the sampling data to estimate the electricity market and local MG status. The fuzzy-logic mimics the artificial intelligent assessment to economic issues and make decision for the charging and discharging operation for energy storage system (ESS). In the FLEMS, not only electricity price and supply-demand balance, but also ESS state of charge are considered for the efficient and stable operations. The proposed method does not relay on the accurate prediction of renewable energy source and local loads. Historical experience of the system is involved by the LEPM and guides the ESS operation in the fuzzy-logic. A real-world data based household-level residential MG model is established to validate the performance of the FLEMS. A hourly-resolution-Particle swarm optimization (PSO) with perfect day-ahead prediction is implemented as the baseline to verify the superiority of the proposed method.

KW - EMS

KW - energy storage

KW - electricity cost

KW - fuzzy logic

KW - microgrid

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U2 - 10.1109/IECON51785.2023.10312171

DO - 10.1109/IECON51785.2023.10312171

M3 - Conference contribution

SN - 979-8-3503-3183-7

T3 - Proceedings of the Annual Conference of the IEEE Industrial Electronics Society

BT - Proceedings of the IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

T2 - IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

Y2 - 16 October 2023 through 19 October 2023

ER -

Fuzzy Logic-Based Online Energy Management System for Residential Microgrids

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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