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A Generation Expansion Planning model for integrating high shares of renewable energy: A Meta-Model Assisted Evolutionary Algorithm approach

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  • Vrionis, Constantinos
  • Tsalavoutis, Vasilios
  • Tolis, Athanasios

Abstract

This study presents a complementary model for Generation Expansion Planning (GEP). A GEP problem commonly determines optimal investment decisions in new power generation plants by minimizing total cost over a mid towards long planning horizon subjected by a set of constraints. The model aims to capture operational challenges arising when a transition towards higher shares of intermittent renewable generation is considered. It embeds a computationally expensive Operational Cost Simulation Model (OCSM), which may exhibit a high level of temporal and technical representation of the short-term operation of a power system to model the unit commitment. The emerging computationally expensive integer non-linear programming constrained optimization model is solved by a problem-customized Meta-model Assisted Evolutionary Algorithm (MAEA). The MAEA employs, off-line trained and on-line refined, approximation models to estimate the output of an OCSM to attain a near-optimal solution by utilizing a limited number of computationally expensive OCSM simulations. The approach is applied on an illustrative test case for a 15 year planning period considering the short-term operation of thermal, hydroelectric and storage units and generation from renewable energy sources. Moreover, the impact of technical resolution is examined through a simple comparative study. The results reveal the efficiency of the proposed problem-customized MAEA. Moreover, the trained approximation models exhibit a low relative error indicating that they may adequately approximate the true output of the OCSM. It is demonstrated that neglecting technical limitations of thermal units may underestimate the utilization of flexible units, i.e. thermal and non-thermal units, affecting the attained investment decisions.

Suggested Citation

  • Vrionis, Constantinos & Tsalavoutis, Vasilios & Tolis, Athanasios, 2020. "A Generation Expansion Planning model for integrating high shares of renewable energy: A Meta-Model Assisted Evolutionary Algorithm approach," Applied Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919317726
    DOI: 10.1016/j.apenergy.2019.114085
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    1. Georgopoulou, Chariklia A. & Giannakoglou, Kyriakos C., 2010. "Metamodel-assisted evolutionary algorithms for the unit commitment problem with probabilistic outages," Applied Energy, Elsevier, vol. 87(5), pages 1782-1792, May.
    2. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    3. Collins, Seán & Deane, John Paul & Poncelet, Kris & Panos, Evangelos & Pietzcker, Robert C. & Delarue, Erik & Ó Gallachóir, Brian Pádraig, 2017. "Integrating short term variations of the power system into integrated energy system models: A methodological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 839-856.
    4. Ignacio J. Perez-Arriaga and Pedro Linares, 2008. "Markets vs. Regulation: A Role for Indicative Energy Planning," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 149-164.
    5. Lara, Cristiana L. & Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Grossmann, Ignacio E., 2018. "Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1037-1054.
    6. Han, Xingning & Chen, Xinyu & McElroy, Michael B. & Liao, Shiwu & Nielsen, Chris P. & Wen, Jinyu, 2019. "Modeling formulation and validation for accelerated simulation and flexibility assessment on large scale power systems under higher renewable penetrations," Applied Energy, Elsevier, vol. 237(C), pages 145-154.
    7. Welsch, Manuel & Deane, Paul & Howells, Mark & Ó Gallachóir, Brian & Rogan, Fionn & Bazilian, Morgan & Rogner, Hans-Holger, 2014. "Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland," Applied Energy, Elsevier, vol. 135(C), pages 600-615.
    8. Puga, J. Nicolas, 0. "The Importance of Combined Cycle Generating Plants in Integrating Large Levels of Wind Power Generation," The Electricity Journal, Elsevier, vol. 23(7), pages 33-44, August.
    9. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2011. "Determining optimal electricity technology mix with high level of wind power penetration," Applied Energy, Elsevier, vol. 88(6), pages 2231-2238, June.
    10. Glotić, Arnel & Zamuda, Aleš, 2015. "Short-term combined economic and emission hydrothermal optimization by surrogate differential evolution," Applied Energy, Elsevier, vol. 141(C), pages 42-56.
    11. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    12. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2015. "A simplified optimization model to short-term electricity planning," Energy, Elsevier, vol. 93(P2), pages 2126-2135.
    13. Juliane Müller & Christine Shoemaker & Robert Piché, 2014. "SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications," Journal of Global Optimization, Springer, vol. 59(4), pages 865-889, August.
    14. Onwubolu, Godfrey & Davendra, Donald, 2006. "Scheduling flow shops using differential evolution algorithm," European Journal of Operational Research, Elsevier, vol. 171(2), pages 674-692, June.
    15. Morales-España, Germán & Ramírez-Elizondo, Laura & Hobbs, Benjamin F., 2017. "Hidden power system inflexibilities imposed by traditional unit commitment formulations," Applied Energy, Elsevier, vol. 191(C), pages 223-238.
    16. 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.
    17. Prebeg, Pero & Gasparovic, Goran & Krajacic, Goran & Duic, Neven, 2016. "Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles," Applied Energy, Elsevier, vol. 184(C), pages 1493-1507.
    18. Dagoumas, Athanasios S. & Koltsaklis, Nikolaos E., 2019. "Review of models for integrating renewable energy in the generation expansion planning," Applied Energy, Elsevier, vol. 242(C), pages 1573-1587.
    19. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2017. "Generation expansion planning optimisation with renewable energy integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 790-803.
    20. Zhang, Ning & Hu, Zhaoguang & Shen, Bo & He, Gang & Zheng, Yanan, 2017. "An integrated source-grid-load planning model at the macro level: Case study for China's power sector," Energy, Elsevier, vol. 126(C), pages 231-246.
    21. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2017. "Generation expansion planning with high share of renewables of variable output," Applied Energy, Elsevier, vol. 190(C), pages 1275-1288.
    22. Poncelet, Kris & Delarue, Erik & Six, Daan & Duerinck, Jan & D’haeseleer, William, 2016. "Impact of the level of temporal and operational detail in energy-system planning models," Applied Energy, Elsevier, vol. 162(C), pages 631-643.
    23. Hemmati, Reza & Saboori, Hedayat & Jirdehi, Mehdi Ahmadi, 2016. "Multistage generation expansion planning incorporating large scale energy storage systems and environmental pollution," Renewable Energy, Elsevier, vol. 97(C), pages 636-645.
    24. Ueckerdt, Falko & Brecha, Robert & Luderer, Gunnar & Sullivan, Patrick & Schmid, Eva & Bauer, Nico & Böttger, Diana & Pietzcker, Robert, 2015. "Representing power sector variability and the integration of variable renewables in long-term energy-economy models using residual load duration curves," Energy, Elsevier, vol. 90(P2), pages 1799-1814.
    25. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Georgiadis, Michael C. & Papaioannou, George & Dikaiakos, Christos, 2016. "A mid-term, market-based power systems planning model," Applied Energy, Elsevier, vol. 179(C), pages 17-35.
    26. Pineda, Salvador & Boomsma, Trine K. & Wogrin, Sonja, 2018. "Renewable generation expansion under different support schemes: A stochastic equilibrium approach," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1086-1099.
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