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A Centralized Smart Decision-Making Hierarchical Interactive Architecture for Multiple Home Microgrids in Retail Electricity Market

Author

Listed:
  • Masoumeh Javadi

    (Department of Electrical Power Engineering, Guilan Science and Research Branch, Islamic Azad University, Rasht 4147654919, Iran
    Department of Electrical Power Engineering, Rasht Branch, Islamic Azad University, Rasht 4147654919, Iran)

  • Mousa Marzband

    (Faculty of Engineering and Environment, Department of Maths, Physics and Electrical Engineering, Northumbria University Newcastle, Newcastle upon Tyne NE1 8ST, UK
    Department of Electrical Engineering, Lahijan Branch, Islamic Azad University, Lahijan 4416939515, Iran)

  • Mudathir Funsho Akorede

    (Department of Electrical & Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, P.M.B. 1515 Ilorin, Nigeria)

  • Radu Godina

    (Centre for Aerospace Science and Technologies—Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilhã, Portugal)

  • Ameena Saad Al-Sumaiti

    (Electrical and Computer Engineering, Khalifa University, Abu Dhabi 127788, UAE)

  • Edris Pouresmaeil

    (Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland)

Abstract

The principal aim of this study is to devise a combined market operator and a distribution network operator structure for multiple home-microgrids (MH-MGs) connected to an upstream grid. Here, there are three distinct types of players with opposite intentions that can participate as a consumer and/or prosumer (as a buyer or seller) in the market. All players that are price makers can compete with each other to obtain much more possible profitability while consumers aim to minimize the market-clearing price. For modeling the interactions among partakers and implementing this comprehensive structure, a multi-objective function problem is solved by using a static, non-cooperative game theory. The propounded structure is a hierarchical bi-level controller, and its accomplishment in the optimal control of MH-MGs with distributed energy resources has been evaluated. The outcome of this algorithm provides the best and most suitable power allocation among different players in the market while satisfying each player’s goals. Furthermore, the amount of profit gained by each player is ascertained. Simulation results demonstrate 169% increase in the total payoff compared to the imperialist competition algorithm. This percentage proves the effectiveness, extensibility and flexibility of the presented approach in encouraging participants to join the market and boost their profits.

Suggested Citation

  • Masoumeh Javadi & Mousa Marzband & Mudathir Funsho Akorede & Radu Godina & Ameena Saad Al-Sumaiti & Edris Pouresmaeil, 2018. "A Centralized Smart Decision-Making Hierarchical Interactive Architecture for Multiple Home Microgrids in Retail Electricity Market," Energies, MDPI, vol. 11(11), pages 1-22, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3144-:d:182658
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    References listed on IDEAS

    as
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    2. 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.
    3. Guang, Fengtao & He, Yongxiu & Wen, Le, 2019. "Impacts of hybrid time-varying tariffs on residential electricity demand: The case of Zhejiang Province," Utilities Policy, Elsevier, vol. 61(C).
    4. Jafari, Amirreza & Ganjeh Ganjehlou, Hamed & Khalili, Tohid & Bidram, Ali, 2020. "A fair electricity market strategy for energy management and reliability enhancement of islanded multi-microgrids," Applied Energy, Elsevier, vol. 270(C).
    5. Antonio Bracale & Guido Carpinelli & Pasquale De Falco, 2019. "Developing and Comparing Different Strategies for Combining Probabilistic Photovoltaic Power Forecasts in an Ensemble Method," Energies, MDPI, vol. 12(6), pages 1-16, March.
    6. Saif Ul Islam & Kamran Zeb & Soobae Kim, 2022. "Design of Robust Fuzzy Logic Controller Based on Gradient Descent Algorithm with Parallel-Resonance Type Fault Current Limiter for Grid-Tied PV System," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
    7. Weiliang Wang & Dan Wang & Liu Liu & Hongjie Jia & Yunqiang Zhi & Zhengji Meng & Wei Du, 2019. "Research on Modeling and Hierarchical Scheduling of a Generalized Multi-Source Energy Storage System in an Integrated Energy Distribution System," Energies, MDPI, vol. 12(2), pages 1-28, January.
    8. Md Shafiul Alam & Mohammad Ali Yousef Abido & Alaa El-Din Hussein & Ibrahim El-Amin, 2019. "Fault Ride through Capability Augmentation of a DFIG-Based Wind Integrated VSC-HVDC System with Non-Superconducting Fault Current Limiter," Sustainability, MDPI, vol. 11(5), pages 1-23, February.
    9. Julian Garcia-Guarin & Diego Rodriguez & David Alvarez & Sergio Rivera & Camilo Cortes & Alejandra Guzman & Arturo Bretas & Julio Romero Aguero & Newton Bretas, 2019. "Smart Microgrids Operation Considering a Variable Neighborhood Search: The Differential Evolutionary Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 12(16), pages 1-13, August.
    10. Lihui Zhang & He Xin & Zhinan Kan, 2019. "Sustainability Performance Evaluation of Hybrid Energy System Using an Improved Fuzzy Synthetic Evaluation Approach," Sustainability, MDPI, vol. 11(5), pages 1-19, February.
    11. Ameena Saad Al-Sumaiti & Abdollah Kavousi-Fard & Magdy Salama & Motahareh Pourbehzadi & Srikanth Reddy & Muhammad Babar Rasheed, 2020. "Economic Assessment of Distributed Generation Technologies: A Feasibility Study and Comparison with the Literature," Energies, MDPI, vol. 13(11), pages 1-28, June.
    12. Arsalan Najafi & Mousa Marzband & Behnam Mohamadi-Ivatloo & Javier Contreras & Mahdi Pourakbari-Kasmaei & Matti Lehtonen & Radu Godina, 2019. "Uncertainty-Based Models for Optimal Management of Energy Hubs Considering Demand Response," Energies, MDPI, vol. 12(8), pages 1-20, April.
    13. Raheela Jamal & Baohui Men & Noor Habib Khan & Muhammad Asif Zahoor Raja, 2019. "Hybrid Bio-Inspired Computational Heuristic Paradigm for Integrated Load Dispatch Problems Involving Stochastic Wind," Energies, MDPI, vol. 12(13), pages 1-23, July.

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