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Renewable energy resources short-term scheduling and dynamic network reconfiguration for sustainable energy consumption

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  • Gutiérrez-Alcaraz, G.
  • Galván, E.
  • González-Cabrera, N.
  • Javadi, M.S.

Abstract

This paper proposes a two-phase approach for optimal short-term operational scheduling with intermittent renewable energy resources (RES) in an active distribution system. The first phase determines the amounts of purchased power from the market and the unit status of distributed generation (DG) and feeds the data into the second phase, a real-time scheduling coordination with hourly network reconfiguration. The two-phase proposed approach is applied to a case study of a sixteen-bus test system that uses synthetic data from renewable power generators and forecasts local user demands with a sampling time of five minutes.

Suggested Citation

  • Gutiérrez-Alcaraz, G. & Galván, E. & González-Cabrera, N. & Javadi, M.S., 2015. "Renewable energy resources short-term scheduling and dynamic network reconfiguration for sustainable energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 256-264.
    • Handle: RePEc:eee:rensus:v:52:y:2015:i:c:p:256-264
    DOI: 10.1016/j.rser.2015.07.105
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    3. Mansouri, Seyed Amir & Ahmarinejad, Amir & Javadi, Mohammad Sadegh & Catalão, João P.S., 2020. "Two-stage stochastic framework for energy hubs planning considering demand response programs," Energy, Elsevier, vol. 206(C).
    4. César Hernández-Hernández & Francisco Rodríguez & José Carlos Moreno & Paulo Renato Da Costa Mendes & Julio Elias Normey-Rico & José Luis Guzmán, 2017. "The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management," Energies, MDPI, vol. 10(7), pages 1-24, June.
    5. Saeid Esmaeili & Amjad Anvari-Moghaddam & Shahram Jadid & Josep M. Guerrero, 2018. "A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems," Energies, MDPI, vol. 11(7), pages 1-19, July.
    6. Santos, Sérgio F. & Fitiwi, Desta Z. & Cruz, Marco R.M. & Cabrita, Carlos M.P. & Catalão, João P.S., 2017. "Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems," Applied Energy, Elsevier, vol. 185(P1), pages 44-55.
    7. Fatma Yaprakdal & M. Berkay Yılmaz & Mustafa Baysal & Amjad Anvari-Moghaddam, 2020. "A Deep Neural Network-Assisted Approach to Enhance Short-Term Optimal Operational Scheduling of a Microgrid," Sustainability, MDPI, vol. 12(4), pages 1-27, February.
    8. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    9. Marzal, Silvia & Salas, Robert & González-Medina, Raúl & Garcerá, Gabriel & Figueres, Emilio, 2018. "Current challenges and future trends in the field of communication architectures for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3610-3622.
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