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Stochastic Rating of Storage Systems in Isolated Networks with Increasing Wave Energy Penetration

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  • Elisabetta Tedeschi

    (Marine Energy Area, Tecnalia Research & Innovation, Parque Tecnológico de Bizkaia, C/Geldo, Edificio 700, Derio 48160, Spain
    Department of Electric Power Engineering, Norwegian University of Science and Technology (NTNU), O.S. Bragstads plass 2, Trondheim 7491, Norway)

  • Jonas Sjolte

    (Department of Electric Power Engineering, Norwegian University of Science and Technology (NTNU), O.S. Bragstads plass 2, Trondheim 7491, Norway
    Fred Olsen, Fred. Olsens Gate 2, Oslo 0152, Norway)

  • Marta Molinas

    (Department of Electric Power Engineering, Norwegian University of Science and Technology (NTNU), O.S. Bragstads plass 2, Trondheim 7491, Norway)

  • Maider Santos

    (Marine Energy Area, Tecnalia Research & Innovation, Parque Tecnológico de Bizkaia, C/Geldo, Edificio 700, Derio 48160, Spain)

Abstract

The future success of wave energy in the renewable energy mix depends on the technical advancements of the specific components and systems, on the grid access availability and, ultimately, on the economical profitability of the investment. Small and remote islands represent an ideal framework for wave energy exploitation, due both to resource availability and to the current high cost of electricity that mostly relies on diesel generation. Energy storage can be the enabling technology to match the intermittent power generation from waves to the energy needs of the local community. In this paper real data from La Palma, in the Canary Islands, are used as a basis for the considered test case. As a first step the study quantifies the expected power production from Wave Energy Converter (WEC) arrays, based on data from the Lifesaver point absorber developed by Fred. Olsen. Then, a stochastic optimization approach is applied to evaluate the convenience of energy storage introduction for reducing the final cost of energy and to define the corresponding optimal rating of the storage devices.

Suggested Citation

  • Elisabetta Tedeschi & Jonas Sjolte & Marta Molinas & Maider Santos, 2013. "Stochastic Rating of Storage Systems in Isolated Networks with Increasing Wave Energy Penetration," Energies, MDPI, vol. 6(5), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:5:p:2481-2500:d:25731
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    References listed on IDEAS

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    1. Fusco, Francesco & Nolan, Gary & Ringwood, John V., 2010. "Variability reduction through optimal combination of wind/wave resources – An Irish case study," Energy, Elsevier, vol. 35(1), pages 314-325.
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    1. Carlos Suazo-Martínez & Eduardo Pereira-Bonvallet & Rodrigo Palma-Behnke, 2014. "A Simulation Framework for Optimal Energy Storage Sizing," Energies, MDPI, vol. 7(5), pages 1-23, May.
    2. Haas, J. & Nowak, W. & Palma-Behnke, R., 2019. "Multi-objective planning of energy storage technologies for a fully renewable system: Implications for the main stakeholders in Chile," Energy Policy, Elsevier, vol. 126(C), pages 494-506.
    3. Haas, J. & Cebulla, F. & Cao, K. & Nowak, W. & Palma-Behnke, R. & Rahmann, C. & Mancarella, P., 2017. "Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 603-619.
    4. José A. Domínguez-Navarro & Elisabetta Tedeschi, 2016. "Evaluation of the Fluid Model Approach for the Sizing of Energy Storage in Wave-Wind Energy Systems," Energies, MDPI, vol. 9(3), pages 1-19, March.

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