IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i14p5262-d1190114.html
   My bibliography  Save this article

Battery Storage Systems Control Strategies with Intelligent Algorithms in Microgrids with Dynamic Pricing

Author

Listed:
  • Guilherme Henrique Alves

    (Faculty of Electrical Engineering, Federal University of Uberlândia, Uberlândia 38400-902, MG, Brazil
    Airport Campus, University of Uberaba, Uberaba 38055-500, MG, Brazil)

  • Geraldo Caixeta Guimarães

    (Faculty of Electrical Engineering, Federal University of Uberlândia, Uberlândia 38400-902, MG, Brazil)

  • Fabricio Augusto Matheus Moura

    (Unit 2, Institute of Technological and Exact Sciences, Electrical Engineering Department, Federal University of Triangle Mineiro, Uberaba 38025-180, MG, Brazil)

Abstract

The current microgrid (MG) needs alternatives to raise the management level and avoid waste. This approach is important for developing the modern electrical system, as it allows for better integration of distributed generation (DG) and battery energy storage systems (BESSs). Using algorithms based on artificial intelligence (AI) for the energy management system (EMS) can help improve the MG operation to achieve the lowest possible cost in buying and selling electricity and, consequently, increase energy conservation levels. With this, the research proposes two strategies for managing energy in the MG to determine the instants of charge and discharge of the BESS. A heuristic method is employed as a reference point for comparison purposes with the fuzzy logic (FL) operation developed. Furthermore, other algorithms based on artificial neural networks (ANNs) are proposed using the non-linear autoregressive technique to predict the MG variables. During the research, the developed algorithms were evaluated through extensive case studies, with simulations that used data from the PV system, load demands, and electricity prices. For all cases, the AI algorithms for predictions and actions managed to reduce the cost and daily consumption of electricity in the main electricity grids compared with the heuristic method or with the MG without using BESSs. This indicates that the developed power management strategies can be applied to reduce the costs of grid-connected MG operations. It is important to highlight that the simulations were executed in an adequate time, allowing the use of the proposed algorithms in dynamic real-time situations to contribute to developing more efficient and sustainable electrical systems.

Suggested Citation

  • Guilherme Henrique Alves & Geraldo Caixeta Guimarães & Fabricio Augusto Matheus Moura, 2023. "Battery Storage Systems Control Strategies with Intelligent Algorithms in Microgrids with Dynamic Pricing," Energies, MDPI, vol. 16(14), pages 1-30, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5262-:d:1190114
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/14/5262/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/14/5262/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Syed Muhammad Mohsin & Tahir Maqsood & Sajjad Ahmed Madani, 2022. "Solar and Wind Energy Forecasting for Green and Intelligent Migration of Traditional Energy Sources," Sustainability, MDPI, vol. 14(23), pages 1-20, December.
    2. 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.
    3. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    4. Mahmoud Saleh & Yusef Esa & Mohamed El Hariri & Ahmed Mohamed, 2019. "Impact of Information and Communication Technology Limitations on Microgrid Operation," Energies, MDPI, vol. 12(15), pages 1-24, July.
    5. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    6. Stefano Massucco & Gabriele Mosaico & Matteo Saviozzi & Federico Silvestro, 2019. "A Hybrid Technique for Day-Ahead PV Generation Forecasting Using Clear-Sky Models or Ensemble of Artificial Neural Networks According to a Decision Tree Approach," Energies, MDPI, vol. 12(7), pages 1-21, April.
    7. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    8. Ênio Costa Resende & Henrique Tannús de Moura Carvalho & Luiz Carlos Gomes Freitas, 2022. "Implementation and Critical Analysis of the Active Phase Jump with Positive Feedback Anti-Islanding Algorithm," Energies, MDPI, vol. 15(13), pages 1-27, June.
    9. Abdulla I. M. Almadi & Rabia Emhamed Al Mamlook & Yahya Almarhabi & Irfan Ullah & Arshad Jamal & Nishantha Bandara, 2022. "A Fuzzy-Logic Approach Based on Driver Decision-Making Behavior Modeling and Simulation," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    10. Zina Boussaada & Octavian Curea & Ahmed Remaci & Haritza Camblong & Najiba Mrabet Bellaaj, 2018. "A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation," Energies, MDPI, vol. 11(3), pages 1-21, March.
    11. Donghun Lee & Kwanho Kim, 2019. "Recurrent Neural Network-Based Hourly Prediction of Photovoltaic Power Output Using Meteorological Information," Energies, MDPI, vol. 12(2), pages 1-22, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Konrad Świrski & Piotr Błach, 2024. "Energy Storage Management Using Artificial Intelligence to Maximize Polish Energy Market Profits," Energies, MDPI, vol. 17(19), pages 1-17, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    2. Hamdi Abdi, 2022. "A Brief Review of Microgrid Surveys, by Focusing on Energy Management System," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    3. Thi Ngoc Nguyen & Felix Musgens, 2021. "What drives the accuracy of PV output forecasts?," Papers 2111.02092, arXiv.org.
    4. Nguyen, Thi Ngoc & Müsgens, Felix, 2022. "What drives the accuracy of PV output forecasts?," Applied Energy, Elsevier, vol. 323(C).
    5. Augusto M. S. Alonso & Luis De Oro Arenas & Danilo I. Brandao & Elisabetta Tedeschi & Ricardo Q. Machado & Fernando P. Marafão, 2022. "Current-Based Coordination of Distributed Energy Resources in a Grid-Connected Low-Voltage Microgrid: An Experimental Validation of Adverse Operational Scenarios," Energies, MDPI, vol. 15(17), pages 1-26, September.
    6. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    7. 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.
    8. Sabadus, Andreea & Blaga, Robert & Hategan, Sergiu-Mihai & Calinoiu, Delia & Paulescu, Eugenia & Mares, Oana & Boata, Remus & Stefu, Nicoleta & Paulescu, Marius & Badescu, Viorel, 2024. "A cross-sectional survey of deterministic PV power forecasting: Progress and limitations in current approaches," Renewable Energy, Elsevier, vol. 226(C).
    9. Evgeny Solomin & Shanmuga Priya Selvanathan & Sudhakar Kumarasamy & Anton Kovalyov & Ramyashree Maddappa Srinivasa, 2021. "The Comparison of Solar-Powered Hydrogen Closed-Cycle System Capacities for Selected Locations," Energies, MDPI, vol. 14(9), pages 1-18, May.
    10. Wei Li & Hui Ren & Ping Chen & Yanyang Wang & Hailong Qi, 2020. "Key Operational Issues on the Integration of Large-Scale Solar Power Generation—A Literature Review," Energies, MDPI, vol. 13(22), pages 1-25, November.
    11. Farhat Afzah Samoon & Ikhlaq Hussain & Sheikh Javed Iqbal, 2023. "ILA Optimisation Based Control for Enhancing DC Link Voltage with Seamless and Adaptive VSC Control in a PV-BES Based AC Microgrid," Energies, MDPI, vol. 16(21), pages 1-23, October.
    12. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    13. Hussain Abdalla Sajwani & Bassel Soudan & Abdul Ghani Olabi, 2024. "Empowering Sustainability: Understanding Determinants of Consumer Investment in Microgrid Technology in the UAE," Energies, MDPI, vol. 17(9), pages 1-28, May.
    14. Ciurea Iulia-Cristina, 2024. "The Impact of the EU AI Act on the UN Sustainable Development Goals for 2030 – A Text Analysis," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 2857-2870.
    15. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski & Ibrahim Alhamrouni, 2024. "AI Applications to Enhance Resilience in Power Systems and Microgrids—A Review," Sustainability, MDPI, vol. 16(12), pages 1-35, June.
    16. Ray, Manojit & Chakraborty, Basab, 2022. "Impact of demand flexibility and tiered resilience on solar photovoltaic adoption in humanitarian settlements," Renewable Energy, Elsevier, vol. 193(C), pages 895-912.
    17. Dimitrios Trigkas & Chrysovalantou Ziogou & Spyros Voutetakis & Simira Papadopoulou, 2021. "Virtual Energy Storage in RES-Powered Smart Grids with Nonlinear Model Predictive Control," Energies, MDPI, vol. 14(4), pages 1-22, February.
    18. Jihed Hmad & Azeddine Houari & Allal El Moubarek Bouzid & Abdelhakim Saim & Hafedh Trabelsi, 2023. "A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids," Energies, MDPI, vol. 16(13), pages 1-41, June.
    19. Matija Kostelac & Lin Herenčić & Tomislav Capuder, 2022. "Planning and Operational Aspects of Individual and Clustered Multi-Energy Microgrid Options," Energies, MDPI, vol. 15(4), pages 1-17, February.
    20. Ahmed Y. Hatata & Mohamed A. Essa & Bishoy E. Sedhom, 2022. "Implementation and Design of FREEDM System Differential Protection Method Based on Internet of Things," Energies, MDPI, vol. 15(15), pages 1-24, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5262-:d:1190114. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.