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Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies

Author

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  • José Luis Ruiz Duarte

    (Department of Marketing and Business Analytics, San Jose State University, San Jose, CA 95192, USA)

  • Neng Fan

    (Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ 85721, USA)

Abstract

The international community has set ambitious targets to replace the use of fossil fuels for electricity generation with renewable energy sources. The use of large-scale (e.g., solar farms) and small-scale solutions (e.g., onsite green technologies) represents one way to achieve these goals. This paper presents a mathematical optimization framework to coordinate the energy decisions between the distribution network and the networked microgrids embedded within it. Utility-scale renewable and conventional generators are considered in the distribution network, while the microgrids include onsite renewable generation and energy storage. The distribution network operator utilizes demand-side management policies to improve the network’s efficiency, and the microgrids operate under these programs by reducing their energy usage, scheduling the electricity usage under dynamic tariffs, and supplying energy to the grid. The uncertainty of renewable energy sources is addressed by robust optimization. The decisions of the distribution network and the microgrids are made independently, whereas the proposed collaboration scheme allows for the alignment of the systems’ objectives. A case study is analyzed to show the capability of the model to assess multiple configurations, eliminating the necessity of load shedding, and increasing the power supplied by the microgrids (22.3 MW) and the renewable energy share by up to 5.03%.

Suggested Citation

  • José Luis Ruiz Duarte & Neng Fan, 2022. "Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies," Energies, MDPI, vol. 15(7), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2350-:d:777923
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    References listed on IDEAS

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    1. Ruiz Duarte, José Luis & Fan, Neng & Jin, Tongdan, 2020. "Multi-process production scheduling with variable renewable integration and demand response," European Journal of Operational Research, Elsevier, vol. 281(1), pages 186-200.
    2. Sławomir Zator, 2021. "Power Scheduling Scheme for DSM in Smart Homes with Photovoltaic and Energy Storage," Energies, MDPI, vol. 14(24), pages 1-20, December.
    3. Behrangrad, Mahdi, 2015. "A review of demand side management business models in the electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 270-283.
    4. Fang, Xinli & Ma, Shihao & Yang, Qiang & Zhang, Jintao, 2016. "Cooperative energy dispatch for multiple autonomous microgrids with distributed renewable sources and storages," Energy, Elsevier, vol. 99(C), pages 48-57.
    5. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    6. Fang, Xinli & Yang, Qiang & Wang, Jianhui & Yan, Wenjun, 2016. "Coordinated dispatch in multiple cooperative autonomous islanded microgrids," Applied Energy, Elsevier, vol. 162(C), pages 40-48.
    7. Lv, Tianguang & Ai, Qian, 2016. "Interactive energy management of networked microgrids-based active distribution system considering large-scale integration of renewable energy resources," Applied Energy, Elsevier, vol. 163(C), pages 408-422.
    8. Kou, Peng & Liang, Deliang & Gao, Lin, 2017. "Distributed EMPC of multiple microgrids for coordinated stochastic energy management," Applied Energy, Elsevier, vol. 185(P1), pages 939-952.
    9. Kumar, R. Seshu & Raghav, L. Phani & Raju, D. Koteswara & Singh, Arvind R., 2021. "Intelligent demand side management for optimal energy scheduling of grid connected microgrids," Applied Energy, Elsevier, vol. 285(C).
    10. Haddadian, Hossein & Noroozian, Reza, 2017. "Multi-microgrids approach for design and operation of future distribution networks based on novel technical indices," Applied Energy, Elsevier, vol. 185(P1), pages 650-663.
    11. Anjos, Miguel F. & Brotcorne, Luce & Gomez-Herrera, Juan A., 2021. "Optimal setting of time-and-level-of-use prices for an electricity supplier," Energy, Elsevier, vol. 225(C).
    12. Vasileios M. Laitsos & Dimitrios Bargiotas & Aspassia Daskalopulu & Athanasios Ioannis Arvanitidis & Lefteri H. Tsoukalas, 2021. "An Incentive-Based Implementation of Demand Side Management in Power Systems," Energies, MDPI, vol. 14(23), pages 1-24, November.
    13. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Demand side management in microgrid: A critical review of key issues and recent trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    14. Seshu Kumar, R. & Phani Raghav, L. & Koteswara Raju, D. & Singh, Arvind R., 2021. "Impact of multiple demand side management programs on the optimal operation of grid-connected microgrids," Applied Energy, Elsevier, vol. 301(C).
    15. Arshad Mohammad & Mohd Zuhaib & Imtiaz Ashraf & Marwan Alsultan & Shafiq Ahmad & Adil Sarwar & Mali Abdollahian, 2021. "Integration of Electric Vehicles and Energy Storage System in Home Energy Management System with Home to Grid Capability," Energies, MDPI, vol. 14(24), pages 1-27, December.
    16. 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.
    17. Giulio Ferro & Riccardo Minciardi & Luca Parodi & Michela Robba & Mansueto Rossi, 2020. "Optimal Control of Multiple Microgrids and Buildings by an Aggregator," Energies, MDPI, vol. 13(5), pages 1-23, February.
    18. Yoldaş, Yeliz & Önen, Ahmet & Muyeen, S.M. & Vasilakos, Athanasios V. & Alan, İrfan, 2017. "Enhancing smart grid with microgrids: Challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 205-214.
    19. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2016. "Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage," Applied Energy, Elsevier, vol. 163(C), pages 93-104.
    20. Gomez-Herrera, Juan A. & Anjos, Miguel F., 2018. "Optimal collaborative demand-response planner for smart residential buildings," Energy, Elsevier, vol. 161(C), pages 370-380.
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    2. Santanu Kumar Dash & Suprava Chakraborty & Michele Roccotelli & Umesh Kumar Sahu, 2022. "Hydrogen Fuel for Future Mobility: Challenges and Future Aspects," Sustainability, MDPI, vol. 14(14), pages 1-22, July.

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