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Tactical and operational management of wind energy systems with storage using a probabilistic forecast of the energy resource

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  • Azcárate, Cristina
  • Mallor, Fermín
  • Mateo, Pedro

Abstract

The storage of energy facilitates the management of renewable energy systems by reducing the mismatch between the supplied energy and the forecasted production due to forecasting errors. The storage increases the reliability of the renewable energy system and enables participation in the electricity market by committing to the sale of electricity for the following day. Nevertheless, the inclusion of the energy storage capacity requires the development of new management policies. In this paper, we propose a management strategy for a renewable energy system with storage capacity that integrates tactical and operational decisions in a single mathematical model that makes use of an updated probabilistic wind speed forecast. Management policies are obtained by solving a sequence of rolling-horizon stochastic optimization problems whose formulation is inspired by the Stochastic Approximation Average technique. The management policies are illustrated by their application to wind-farms using hydrogen as the energy storage medium.

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  • Azcárate, Cristina & Mallor, Fermín & Mateo, Pedro, 2017. "Tactical and operational management of wind energy systems with storage using a probabilistic forecast of the energy resource," Renewable Energy, Elsevier, vol. 102(PB), pages 445-456.
    • Handle: RePEc:eee:renene:v:102:y:2017:i:pb:p:445-456
    DOI: 10.1016/j.renene.2016.10.064
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    Cited by:

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    3. Cassettari, Lucia & Bendato, Ilaria & Mosca, Marco & Mosca, Roberto, 2017. "Energy Resources Intelligent Management using on line real-time simulation: A decision support tool for sustainable manufacturing," Applied Energy, Elsevier, vol. 190(C), pages 841-851.
    4. Maria Acuna & Carlos Silva & Andrés Tocaruncho & Diana Vargas & Diego Patiño & David Barrera & Johan Peña, 2021. "Operational Planning of Energy for Non-Interconnected Zones: A Simulation-Optimization Approach and a Case Study to Tackle Energy Poverty in Colombia," Energies, MDPI, vol. 14(10), pages 1-16, May.
    5. Appino, Riccardo Remo & González Ordiano, Jorge Ángel & Mikut, Ralf & Faulwasser, Timm & Hagenmeyer, Veit, 2018. "On the use of probabilistic forecasts in scheduling of renewable energy sources coupled to storages," Applied Energy, Elsevier, vol. 210(C), pages 1207-1218.
    6. Vatanpour, Mohsen & Sadeghi Yazdankhah, Ahmad, 2018. "The impact of energy storage modeling in coordination with wind farm and thermal units on security and reliability in a stochastic unit commitment," Energy, Elsevier, vol. 162(C), pages 476-490.
    7. Farihan Mohamad & Jiashen Teh & Ching-Ming Lai & Liang-Rui Chen, 2018. "Development of Energy Storage Systems for Power Network Reliability: A Review," Energies, MDPI, vol. 11(9), pages 1-19, August.
    8. Md Sumon Reza & Shammya Afroze & Kairat Kuterbekov & Asset Kabyshev & Kenzhebatyr Zh. Bekmyrza & Md Naimul Haque & Shafi Noor Islam & Md Aslam Hossain & Mahbub Hassan & Hridoy Roy & Md Shahinoor Islam, 2023. "Advanced Applications of Carbonaceous Materials in Sustainable Water Treatment, Energy Storage, and CO 2 Capture: A Comprehensive Review," Sustainability, MDPI, vol. 15(11), pages 1-56, May.

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