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An Optimization Framework for Investment Evaluation of Complex Renewable Energy Systems

Author

Listed:
  • David Olave-Rojas

    (DSc Program on Complex Engineering Systems, Universidad de Talca, Curicó 3341717, Chile;)

  • Eduardo Álvarez-Miranda

    (Department of Industrial Engineering, Universidad de Talca, Curicó 3341717, Chile)

  • Alejandro Rodríguez

    (Department of Industrial Engineering, Universidad de Talca, Curicó 3341717, Chile)

  • Claudio Tenreiro

    (Department of Industrial Technologies, Universidad de Talca, Curicó 3341717, Chile)

Abstract

Enhancing the role of renewable energies in existing power systems is one of the most crucial challenges that society faces today. However, the high variability of their generation potential and the temporal disparity between the demand and the generation potential represent technological and operational gaps that burden the massive incorporation of renewable sources into power systems. Energy storage technologies are an alternative to tackle this gap; nonetheless, their incorporation within large-scale power grids calls for decision-making tools that ensure an appropriate design and sizing of power systems that exploit the benefits of incorporating storage facilities along with renewable generation power. In this paper, we present an optimization framework for aiding the evaluation of the strategic design of complex renewable power systems. The developed tool relies on an optimization problem, the generation, transmission, storage energy location and sizing problem, which allows one to compute economically-attractive investment plans given by the location and sizing of generation and storage energy systems, along with the corresponding layout of transmission lines. Results on a real case study (located in the central region of Chile), characterized by carefully-curated data, show the potential of the developed tool for aiding long-term investment planning.

Suggested Citation

  • David Olave-Rojas & Eduardo Álvarez-Miranda & Alejandro Rodríguez & Claudio Tenreiro, 2017. "An Optimization Framework for Investment Evaluation of Complex Renewable Energy Systems," Energies, MDPI, vol. 10(7), pages 1-26, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:1062-:d:105588
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    References listed on IDEAS

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    1. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2005. "Bootstrap prediction intervals for power-transformed time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 219-235.
    2. Berrada, Asmae & Loudiyi, Khalid, 2016. "Operation, sizing, and economic evaluation of storage for solar and wind power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1117-1129.
    3. Claudia Rahmann & Rodrigo Palma-Behnke, 2013. "Optimal Allocation of Wind Turbines by Considering Transmission Security Constraints and Power System Stability," Energies, MDPI, vol. 6(1), pages 1-18, January.
    4. Lorenzo Pascual & Juan Romo & Esther Ruiz, 2004. "Bootstrap predictive inference for ARIMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 449-465, July.
    5. Wei Qi & Yong Liang & Zuo-Jun Max Shen, 2015. "Joint Planning of Energy Storage and Transmission for Wind Energy Generation," Operations Research, INFORMS, vol. 63(6), pages 1280-1293, December.
    6. Bradbury, Kyle & Pratson, Lincoln & Patiño-Echeverri, Dalia, 2014. "Economic viability of energy storage systems based on price arbitrage potential in real-time U.S. electricity markets," Applied Energy, Elsevier, vol. 114(C), pages 512-519.
    7. 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.
    8. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
    9. Jae Ho Kim & Warren B. Powell, 2011. "Optimal Energy Commitments with Storage and Intermittent Supply," Operations Research, INFORMS, vol. 59(6), pages 1347-1360, December.
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    Cited by:

    1. Olave-Rojas, David & Álvarez-Miranda, Eduardo, 2021. "Towards a complex investment evaluation framework for renewable energy systems: A 2-level heuristic approach," Energy, Elsevier, vol. 228(C).
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    3. Nikolaos E. Koltsaklis & Athanasios S. Dagoumas, 2021. "A power system scheduling model with carbon intensity and ramping capacity constraints," Operational Research, Springer, vol. 21(1), pages 647-687, March.
    4. Ali Elkamel, 2018. "Energy Production Systems," Energies, MDPI, vol. 11(10), pages 1-4, September.

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