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Energy Management Scheduling for Microgrids in the Virtual Power Plant System Using Artificial Neural Networks

Author

Listed:
  • Maher G. M. Abdolrasol

    (Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia)

  • Mahammad Abdul Hannan

    (Department of Electrical Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • S. M. Suhail Hussain

    (Fukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, Japan)

  • Taha Selim Ustun

    (Fukushima Renewable Energy Institute, AIST (FREA), National Institute of Advanced Industrial Science and Technology (AIST), Koriyama 963-0298, Japan)

  • Mahidur R. Sarker

    (Institute of IR 4.0, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia)

  • Pin Jern Ker

    (Department of Electrical Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

Abstract

This study uses an artificial neural network (ANN) as an intelligent controller for the management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP). Two ANN-based scheduling control approaches are presented: the ANN-based backtracking search algorithm (ANN-BBSA) and ANN-based binary practical swarm optimization (ANN-BPSO) algorithm. Both algorithms provide the optimal schedule for every distribution generation (DG) to limit fuel consumption, reduce CO2 emission, and increase the system efficiency towards smart and economic VPP operation as well as grid decarbonization. Different test scenarios are executed to evaluate the controllers’ robustness and performance under changing system conditions. The test cases are different load curves to evaluate the ANN’s performance on untrained data. The untrained and trained load models used are real-load parameter data recorders in northern parts of Malaysia. The test results are analyzed to investigate the performance of these controllers under varying power system conditions. Additionally, a comparative study is performed to compare their performances with other solutions available in the literature based on several parameters. Results show the superiority of the ANN-based controllers in terms of cost reduction and efficiency.

Suggested Citation

  • Maher G. M. Abdolrasol & Mahammad Abdul Hannan & S. M. Suhail Hussain & Taha Selim Ustun & Mahidur R. Sarker & Pin Jern Ker, 2021. "Energy Management Scheduling for Microgrids in the Virtual Power Plant System Using Artificial Neural Networks," Energies, MDPI, vol. 14(20), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6507-:d:653510
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    1. Yiqi Li & Jing Zhang & Zhoujun Ma & Yang Peng & Shuwen Zhao, 2021. "An Energy Management Optimization Method for Community Integrated Energy System Based on User Dominated Demand Side Response," Energies, MDPI, vol. 14(15), pages 1-22, July.
    2. Partha Pratim Dey & Dulal Chandra Das & Abdul Latif & S. M. Suhail Hussain & Taha Selim Ustun, 2020. "Active Power Management of Virtual Power Plant under Penetration of Central Receiver Solar Thermal-Wind Using Butterfly Optimization Technique," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
    3. Roslan, M.F. & Hannan, M.A. & Jern Ker, Pin & Begum, R.A. & Indra Mahlia, TM & Dong, Z.Y., 2021. "Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction," Applied Energy, Elsevier, vol. 292(C).
    4. Elattar, Ehab E., 2018. "Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources," Energy, Elsevier, vol. 159(C), pages 496-507.
    5. S. Hr. Aghay Kaboli & Amer Al Hinai & A.H. Al-Badi & Yassine Charabi & Abdulrahim Al Saifi, 2019. "Prediction of Metallic Conductor Voltage Owing to Electromagnetic Coupling Via a Hybrid ANFIS and Backtracking Search Algorithm," Energies, MDPI, vol. 12(19), pages 1-18, September.
    6. Mojtaba Ahmadieh Khanesar & Jingyi Lu & Thomas Smith & David Branson, 2021. "Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach," Energies, MDPI, vol. 14(12), pages 1-18, June.
    7. Anurag Chauhan & Subho Upadhyay & Mohd. Tauseef Khan & S. M. Suhail Hussain & Taha Selim Ustun, 2021. "Performance Investigation of a Solar Photovoltaic/Diesel Generator Based Hybrid System with Cycle Charging Strategy Using BBO Algorithm," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    8. Xiaoyu Lin & Hang Yu & Meng Wang & Chaoen Li & Zi Wang & Yin Tang, 2021. "Electricity Consumption Forecast of High-Rise Office Buildings Based on the Long Short-Term Memory Method," Energies, MDPI, vol. 14(16), pages 1-21, August.
    9. Duarte Kazacos Winter & Rahul Khatri & Michael Schmidt, 2021. "Decentralized Prosumer-Centric P2P Electricity Market Coordination with Grid Security," Energies, MDPI, vol. 14(15), pages 1-17, August.
    10. Aiman J. Albarakati & Younes Boujoudar & Mohamed Azeroual & Reda Jabeur & Ayman Aljarbouh & Hassan El Moussaoui & Tijani Lamhamdi & Najat Ouaaline, 2021. "Real-Time Energy Management for DC Microgrids Using Artificial Intelligence," Energies, MDPI, vol. 14(17), pages 1-16, August.
    11. Shishir Gaur & Sudheer Ch & Didier Graillot & B. Chahar & D. Kumar, 2013. "Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 927-941, February.
    12. Izabela Zoltowska & Jeremy Lin, 2021. "Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids," Energies, MDPI, vol. 14(16), pages 1-18, August.
    13. Amar Kumar Barik & Dulal Chandra Das & Abdul Latif & S. M. Suhail Hussain & Taha Selim Ustun, 2021. "Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning," Energies, MDPI, vol. 14(10), pages 1-26, May.
    14. Po-Chen Cheng & Bo-Rei Peng & Yi-Hua Liu & Yu-Shan Cheng & Jia-Wei Huang, 2015. "Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique," Energies, MDPI, vol. 8(6), pages 1-23, June.
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