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Fuzzy logic-based energy management for isolated microgrid using meta-heuristic optimization algorithms

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  • Rodriguez, Mauricio
  • Arcos–Aviles, Diego
  • Martinez, Wilmar

Abstract

Rural areas have increased directly with the growth of the world population. Although, isolated rural areas do not have the energy infrastructure to supply essential services such as electricity. In Ecuador, as in the rest of the world, these areas of the rural population usually present access problems due to the topography of the place. This makes the construction of power lines to connect them to the Interconnected National Energy System unfeasible. In this regard, isolated microgrids have emerged as a great solution to cover the energy demands in these locations. However, an optimal implementation of isolated microgrids depends on several factors, such as geographical location, weather conditions, sizing, load demand, operating costs, and social impacts. Therefore, this study proposes the design of a new energy management system (EMS) for isolated microgrids comprising a photovoltaic system, diesel generator, and battery energy storage system (ESS). Since fuzzy logic control (FLC) has proven to be a powerful tool for dealing with the nonlinearities of a microgrid and the application of fuzzy-based EMS for isolated microgrids is rarely reported in the literature, this study proposes the application of an FLC for the EMS's design of an isolated microgrid. The proposed fuzzy-based EMS uses generation and demand forecasts, enhances the operating time of diesel generators (DLG), and takes advantage of the available solar resource to supply the energy required by a community while preserving the ESS lifetime. An adjustment of the FLC parameters by Particle Swarm Optimization (PSO) and Cuckoo Search (CS) algorithms is performed to improve the behavior of the proposed EMS. Furthermore, a battery degradation model is applied to estimate the ESS State of Health (SOH). To highlight the advantages of the proposed approach, a case study in a specific community in Ecuador is presented. In this location, the proposed EMS is compared with an EMS without parameter adjustment developed in previous work, demonstrating improved performance in DLG limits, preserving the battery lifespan by controlling the battery SOC limits more efficiently, and minimizing the microgrid operating costs by maximizing the use of photovoltaic power (i.e., reducing the wasted photovoltaic energy). The results provide evidence that the EMS adjusted with the PSO algorithm presents an enhanced behavior than the one adjusted by the CS algorithm. Finally, the fuzzy-EMS is validated using Matlab® and Hardware-in-the-Loop Typhoon HIL-402 device. Results demonstrate that the proposed approach limits DLG usage, make the most of the available solar resources, and extends the battery life by controlling overcharges and deep discharges.

Suggested Citation

  • Rodriguez, Mauricio & Arcos–Aviles, Diego & Martinez, Wilmar, 2023. "Fuzzy logic-based energy management for isolated microgrid using meta-heuristic optimization algorithms," Applied Energy, Elsevier, vol. 335(C).
  • Handle: RePEc:eee:appene:v:335:y:2023:i:c:s0306261923001356
    DOI: 10.1016/j.apenergy.2023.120771
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    References listed on IDEAS

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    1. Mbungu, Nsilulu T. & Bansal, Ramesh C. & Naidoo, Raj M. & Bettayeb, Maamar & Siti, Mukwanga W. & Bipath, Minnesh, 2020. "A dynamic energy management system using smart metering," Applied Energy, Elsevier, vol. 280(C).
    2. Marqusee, Jeffrey & Ericson, Sean & Jenket, Don, 2021. "Impact of emergency diesel generator reliability on microgrids and building-tied systems," Applied Energy, Elsevier, vol. 285(C).
    3. Shehab Al-Sakkaf & Mahmoud Kassas & Muhammad Khalid & Mohammad A. Abido, 2019. "An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch," Energies, MDPI, vol. 12(8), pages 1-25, April.
    4. Arcos-Aviles, Diego & Pascual, Julio & Guinjoan, Francesc & Marroyo, Luis & Sanchis, Pablo & Marietta, Martin P., 2017. "Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting," Applied Energy, Elsevier, vol. 205(C), pages 69-84.
    5. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    6. Danny Espín-Sarzosa & Rodrigo Palma-Behnke & Oscar Núñez-Mata, 2020. "Energy Management Systems for Microgrids: Main Existing Trends in Centralized Control Architectures," Energies, MDPI, vol. 13(3), pages 1-32, January.
    7. Meng, Lexuan & Sanseverino, Eleonora Riva & Luna, Adriana & Dragicevic, Tomislav & Vasquez, Juan C. & Guerrero, Josep M., 2016. "Microgrid supervisory controllers and energy management systems: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1263-1273.
    8. Banal-Estañol, Albert & Calzada, Joan & Jordana, Jacint, 2017. "How to achieve full electrification: Lessons from Latin America," Energy Policy, Elsevier, vol. 108(C), pages 55-69.
    9. Sharma, Pavitra & Dutt Mathur, Hitesh & Mishra, Puneet & Bansal, Ramesh C., 2022. "A critical and comparative review of energy management strategies for microgrids," Applied Energy, Elsevier, vol. 327(C).
    10. Mariam, Lubna & Basu, Malabika & Conlon, Michael F., 2016. "Microgrid: Architecture, policy and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 477-489.
    11. San Martín, Idoia & Berrueta, Alberto & Sanchis, Pablo & Ursúa, Alfredo, 2018. "Methodology for sizing stand-alone hybrid systems: A case study of a traffic control system," Energy, Elsevier, vol. 153(C), pages 870-881.
    12. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    13. Berrueta, Alberto & Heck, Michael & Jantsch, Martin & Ursúa, Alfredo & Sanchis, Pablo, 2018. "Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants," Applied Energy, Elsevier, vol. 228(C), pages 1-11.
    14. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    15. Shaterabadi, Mohammad & Jirdehi, Mehdi Ahmadi, 2020. "Multi-objective stochastic programming energy management for integrated INVELOX turbines in microgrids: A new type of turbines," Renewable Energy, Elsevier, vol. 145(C), pages 2754-2769.
    16. Zachar, Michael & Daoutidis, Prodromos, 2015. "Understanding and predicting the impact of location and load on microgrid design," Energy, Elsevier, vol. 90(P1), pages 1005-1023.
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    Cited by:

    1. Zheng Shi & Lu Yan & Yingying Hu & Yao Wang & Wenping Qin & Yan Liang & Haibo Zhao & Yongming Jing & Jiaojiao Deng & Zhi Zhang, 2024. "Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective," Energies, MDPI, vol. 17(18), pages 1-20, September.
    2. Richard Guanoluisa & Diego Arcos-Aviles & Marco Flores-Calero & Wilmar Martinez & Francesc Guinjoan, 2023. "Photovoltaic Power Forecast Using Deep Learning Techniques with Hyperparameters Based on Bayesian Optimization: A Case Study in the Galapagos Islands," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    3. Rodriguez, Mauricio & Arcos-Aviles, Diego & Guinjoan, Francesc, 2024. "Simple fuzzy logic-based energy management for power exchange in isolated multi-microgrid systems: A case study in a remote community in the Amazon region of Ecuador," Applied Energy, Elsevier, vol. 357(C).
    4. Ju, Fei & Du, Wei & Zhuang, Weichao & Li, Bingbing & Wang, Tao & Wang, Weiwei & Ma, Huijie, 2024. "Profit-effective component sizing for electric delivery trucks with dual motor coupling powertrain," Energy, Elsevier, vol. 296(C).
    5. Ana Gabriela Haro-Baez & Diego Chavez & Cristina Camino & Diego Arcos-Aviles, 2023. "Seismic and Tsunami Risk Analysis for Installing Resilient Power Systems Based on Isolated Microgrids on Buildings: The Case of Puerto Ayora in Santa Cruz Island, Galapagos," Sustainability, MDPI, vol. 15(18), pages 1-17, September.
    6. Erdal Irmak & Ersan Kabalci & Yasin Kabalci, 2023. "Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity," Energies, MDPI, vol. 16(12), pages 1-58, June.

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