IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v84y2019ics0140988319302385.html
   My bibliography  Save this article

A two-stage stochastic optimization planning framework to decarbonize deeply electric power systems

Author

Listed:
  • Boffino, Luigi
  • Conejo, Antonio J.
  • Sioshansi, Ramteen
  • Oggioni, Giorgia

Abstract

In 2015, 195 countries signed the Paris Agreement under the United Nations Framework Convention on Climate Change. To achieve the ambitious greenhouse gas-reduction targets therein, the electric power sector must be transformed fundamentally. To this end, we develop a two-stage stochastic optimization model. The proposed model determines the optimal mix of generation and transmission capacity to build to serve future demands at least cost, while respecting technical constraints and climate-related considerations. The model uses a mix of AC and high-voltage DC transmission lines, conventional and renewable generation, and different types of energy-storage units to meet these objectives. Short- and long-term uncertainties are modeled using operating conditions and scenarios, respectively.

Suggested Citation

  • Boffino, Luigi & Conejo, Antonio J. & Sioshansi, Ramteen & Oggioni, Giorgia, 2019. "A two-stage stochastic optimization planning framework to decarbonize deeply electric power systems," Energy Economics, Elsevier, vol. 84(C).
  • Handle: RePEc:eee:eneeco:v:84:y:2019:i:c:s0140988319302385
    DOI: 10.1016/j.eneco.2019.07.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319302385
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2019.07.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Qi, Tianyu & Weng, Yuyan & Zhang, Xiliang & He, Jiankun, 2016. "An analysis of the driving factors of energy-related CO2 emission reduction in China from 2005 to 2013," Energy Economics, Elsevier, vol. 60(C), pages 15-22.
    2. Graves, Frank & Jenkin, Thomas & Murphy, Dean, 1999. "Opportunities for Electricity Storage in Deregulating Markets," The Electricity Journal, Elsevier, vol. 12(8), pages 46-56, October.
    3. Drury, Easan & Denholm, Paul & Sioshansi, Ramteen, 2011. "The value of compressed air energy storage in energy and reserve markets," Energy, Elsevier, vol. 36(8), pages 4959-4973.
    4. Calderón, Silvia & Alvarez, Andrés Camilo & Loboguerrero, Ana María & Arango, Santiago & Calvin, Katherine & Kober, Tom & Daenzer, Kathryn & Fisher-Vanden, Karen, 2016. "Achieving CO2 reductions in Colombia: Effects of carbon taxes and abatement targets," Energy Economics, Elsevier, vol. 56(C), pages 575-586.
    5. Haisheng Chen & Xinjing Zhang & Jinchao Liu & Chunqing Tan, 2013. "Compressed Air Energy Storage," Chapters, in: Ahmed F. Zobaa (ed.), Energy Storage - Technologies and Applications, IntechOpen.
    6. Greenblatt, Jeffery B. & Succar, Samir & Denkenberger, David C. & Williams, Robert H. & Socolow, Robert H., 2007. "Baseload wind energy: modeling the competition between gas turbines and compressed air energy storage for supplemental generation," Energy Policy, Elsevier, vol. 35(3), pages 1474-1492, March.
    7. Gauthier DE MAERE D’AERTRYCKE & Andreas EHRENMANN & Yves SMEERS, 2017. "Investment with incomplete markets for risk: the need for long-term contracts," LIDAM Reprints CORE 2849, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Graf, Christoph & Marcantonini, Claudio, 2017. "Renewable energy and its impact on thermal generation," Energy Economics, Elsevier, vol. 66(C), pages 421-430.
    9. Draxl, Caroline & Clifton, Andrew & Hodge, Bri-Mathias & McCaa, Jim, 2015. "The Wind Integration National Dataset (WIND) Toolkit," Applied Energy, Elsevier, vol. 151(C), pages 355-366.
    10. de Maere d’Aertrycke, Gauthier & Ehrenmann, Andreas & Smeers, Yves, 2017. "Investment with incomplete markets for risk: The need for long-term contracts," Energy Policy, Elsevier, vol. 105(C), pages 571-583.
    11. Hartmann, Niklas & Vöhringer, O. & Kruck, C. & Eltrop, L., 2012. "Simulation and analysis of different adiabatic Compressed Air Energy Storage plant configurations," Applied Energy, Elsevier, vol. 93(C), pages 541-548.
    12. Sioshansi, Ramteen & Denholm, Paul & Jenkin, Thomas & Weiss, Jurgen, 2009. "Estimating the value of electricity storage in PJM: Arbitrage and some welfare effects," Energy Economics, Elsevier, vol. 31(2), pages 269-277, March.
    13. Baringo, L. & Conejo, A.J., 2013. "Correlated wind-power production and electric load scenarios for investment decisions," Applied Energy, Elsevier, vol. 101(C), pages 475-482.
    14. Ramteen Sioshansi & Paul Denholm & Thomas Jenkin, 2012. "Market and Policy Barriers to Deployment of Energy Storage," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    15. Sioshansi, Ramteen & Denholm, Paul & Jenkin, Thomas, 2011. "A comparative analysis of the value of pure and hybrid electricity storage," Energy Economics, Elsevier, vol. 33(1), pages 56-66, January.
    16. Sciacovelli, Adriano & Li, Yongliang & Chen, Haisheng & Wu, Yuting & Wang, Jihong & Garvey, Seamus & Ding, Yulong, 2017. "Dynamic simulation of Adiabatic Compressed Air Energy Storage (A-CAES) plant with integrated thermal storage – Link between components performance and plant performance," Applied Energy, Elsevier, vol. 185(P1), pages 16-28.
    17. Johan Lilliestam & Mercè Labordena & Anthony Patt & Stefan Pfenninger, 2017. "Empirically observed learning rates for concentrating solar power and their responses to regime change," Nature Energy, Nature, vol. 2(7), pages 1-6, July.
    18. Di Sbroiavacca, Nicolás & Nadal, Gustavo & Lallana, Francisco & Falzon, James & Calvin, Katherine, 2016. "Emissions reduction scenarios in the Argentinean Energy Sector," Energy Economics, Elsevier, vol. 56(C), pages 552-563.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Möbius, Thomas & Riepin, Iegor & Müsgens, Felix & van der Weijde, Adriaan H., 2023. "Risk aversion and flexibility options in electricity markets," Energy Economics, Elsevier, vol. 126(C).
    2. Kang, Jidong & Wu, Zhuochun & Ng, Tsan Sheng & Su, Bin, 2023. "A stochastic-robust optimization model for inter-regional power system planning," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1234-1248.
    3. Kang, Jidong & Ng, Tsan Sheng & Su, Bin & Milovanoff, Alexandre, 2021. "Electrifying light-duty passenger transport for CO2 emissions reduction: A stochastic-robust input–output linear programming model," Energy Economics, Elsevier, vol. 104(C).
    4. Kang, Jidong & Ng, Tsan Sheng & Su, Bin, 2020. "Optimizing electricity mix for CO2 emissions reduction: A robust input-output linear programming model," European Journal of Operational Research, Elsevier, vol. 287(1), pages 280-292.
    5. Kenjiro Yagi & Ramteen Sioshansi, 2023. "Simplifying capacity planning for electricity systems with hydroelectric and renewable generation," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
    6. Li, Carmen & Chyong, Chi Kong & Reiner, David M. & Roques, Fabien, 2024. "Taking a Portfolio approach to wind and solar deployment: The case of the National Electricity Market in Australia," Applied Energy, Elsevier, vol. 369(C).
    7. Barrera-Santana, J. & Sioshansi, Ramteen, 2023. "An optimization framework for capacity planning of island electricity systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    8. Michael C. Ferris & Andy Philpott, 2023. "Renewable electricity capacity planning with uncertainty at multiple scales," Computational Management Science, Springer, vol. 20(1), pages 1-40, December.
    9. García-Cerezo, Álvaro & Baringo, Luis & García-Bertrand, Raquel, 2021. "Robust transmission network expansion planning considering non-convex operational constraints," Energy Economics, Elsevier, vol. 98(C).
    10. Felder, F.A. & Kumar, P., 2021. "A review of existing deep decarbonization models and their potential in policymaking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    11. Domínguez, Ruth & Carrión, Miguel & Vitali, Sebastiano, 2024. "Investments in transmission lines and storage units considering second-order stochastic dominance constraints," Energy Economics, Elsevier, vol. 134(C).
    12. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    13. Han Wang & Zhenghui Fu & Shulan Wang & Wenjie Zhang, 2021. "Analysis of CO 2 Emissions in the Whole Production Process of Coal-Fired Power Plant," Sustainability, MDPI, vol. 13(19), pages 1-13, October.
    14. Iacopo Savelli & Thomas Morstyn, 2020. "Electricity prices and tariffs to keep everyone happy: a framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Papers 2001.04283, arXiv.org, revised Jun 2021.
    15. Côté, Elizabeth & Salm, Sarah, 2022. "Risk-adjusted preferences of utility companies and institutional investors for battery storage and green hydrogen investment," Energy Policy, Elsevier, vol. 163(C).
    16. Wojciech Drożdż & Grzegorz Kinelski & Marzena Czarnecka & Magdalena Wójcik-Jurkiewicz & Anna Maroušková & Grzegorz Zych, 2021. "Determinants of Decarbonization—How to Realize Sustainable and Low Carbon Cities?," Energies, MDPI, vol. 14(9), pages 1-19, May.
    17. Jixian Cui & Chenghao Liao & Ling Ji & Yulei Xie & Yangping Yu & Jianguang Yin, 2021. "A Short-Term Hybrid Energy System Robust Optimization Model for Regional Electric-Power Capacity Development Planning under Different Pollutant Control Pressures," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    18. Hannan, M.A. & Faisal, M. & Jern Ker, Pin & Begum, R.A. & Dong, Z.Y. & Zhang, C., 2020. "Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    19. Carvallo, Claudio & Jalil-Vega, Francisca & Moreno, Rodrigo, 2023. "A multi-energy multi-microgrid system planning model for decarbonisation and decontamination of isolated systems," Applied Energy, Elsevier, vol. 343(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Foley, A. & Díaz Lobera, I., 2013. "Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio," Energy, Elsevier, vol. 57(C), pages 85-94.
    2. Ramteen Sioshansi & Paul Denholm & Thomas Jenkin, 2012. "Market and Policy Barriers to Deployment of Energy Storage," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    3. Zakeri, Behnam & Syri, Sanna, 2015. "Electrical energy storage systems: A comparative life cycle cost analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 569-596.
    4. Guo, Cong & Xu, Yujie & Zhang, Xinjing & Guo, Huan & Zhou, Xuezhi & Liu, Chang & Qin, Wei & Li, Wen & Dou, Binlin & Chen, Haisheng, 2017. "Performance analysis of compressed air energy storage systems considering dynamic characteristics of compressed air storage," Energy, Elsevier, vol. 135(C), pages 876-888.
    5. McConnell, Dylan & Forcey, Tim & Sandiford, Mike, 2015. "Estimating the value of electricity storage in an energy-only wholesale market," Applied Energy, Elsevier, vol. 159(C), pages 422-432.
    6. Sioshansi, Ramteen & Denholm, Paul & Jenkin, Thomas, 2011. "A comparative analysis of the value of pure and hybrid electricity storage," Energy Economics, Elsevier, vol. 33(1), pages 56-66, January.
    7. Loisel, Rodica & Simon, Corentin, 2021. "Market strategies for large-scale energy storage: Vertical integration versus stand-alone player," Energy Policy, Elsevier, vol. 151(C).
    8. Luo, Xing & Dooner, Mark & He, Wei & Wang, Jihong & Li, Yaowang & Li, Decai & Kiselychnyk, Oleh, 2018. "Feasibility study of a simulation software tool development for dynamic modelling and transient control of adiabatic compressed air energy storage with its electrical power system applications," Applied Energy, Elsevier, vol. 228(C), pages 1198-1219.
    9. Ding, Jie & Xu, Yujie & Chen, Haisheng & Sun, Wenwen & Hu, Shan & Sun, Shuang, 2019. "Value and economic estimation model for grid-scale energy storage in monopoly power markets," Applied Energy, Elsevier, vol. 240(C), pages 986-1002.
    10. Zhou, Qian & Du, Dongmei & Lu, Chang & He, Qing & Liu, Wenyi, 2019. "A review of thermal energy storage in compressed air energy storage system," Energy, Elsevier, vol. 188(C).
    11. Berrada, Asmae & Loudiyi, Khalid & Zorkani, Izeddine, 2016. "Valuation of energy storage in energy and regulation markets," Energy, Elsevier, vol. 115(P1), pages 1109-1118.
    12. Zafirakis, Dimitrios & Chalvatzis, Konstantinos J. & Baiocchi, Giovanni & Daskalakis, George, 2013. "Modeling of financial incentives for investments in energy storage systems that promote the large-scale integration of wind energy," Applied Energy, Elsevier, vol. 105(C), pages 138-154.
    13. Barbry, Adrien & Anjos, Miguel F. & Delage, Erick & Schell, Kristen R., 2019. "Robust self-scheduling of a price-maker energy storage facility in the New York electricity market," Energy Economics, Elsevier, vol. 78(C), pages 629-646.
    14. Barrera-Santana, J. & Sioshansi, Ramteen, 2023. "An optimization framework for capacity planning of island electricity systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    15. Daniel R. Jiang & Warren B. Powell, 2015. "Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 525-543, August.
    16. Shafiee, Soroush & Zamani-Dehkordi, Payam & Zareipour, Hamidreza & Knight, Andrew M., 2016. "Economic assessment of a price-maker energy storage facility in the Alberta electricity market," Energy, Elsevier, vol. 111(C), pages 537-547.
    17. He, Wei & Dooner, Mark & King, Marcus & Li, Dacheng & Guo, Songshan & Wang, Jihong, 2021. "Techno-economic analysis of bulk-scale compressed air energy storage in power system decarbonisation," Applied Energy, Elsevier, vol. 282(PA).
    18. Jidai Wang & Kunpeng Lu & Lan Ma & Jihong Wang & Mark Dooner & Shihong Miao & Jian Li & Dan Wang, 2017. "Overview of Compressed Air Energy Storage and Technology Development," Energies, MDPI, vol. 10(7), pages 1-22, July.
    19. 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.
    20. Du, Ruxue & He, Yang & Chen, Haisheng & Xu, Yujie & Li, Wen & Deng, Jianqiang, 2022. "Performance and economy of trigenerative adiabatic compressed air energy storage system based on multi-parameter analysis," Energy, Elsevier, vol. 238(PA).

    More about this item

    Keywords

    Generation-expansion planning; Transmission-expansion planning; Stochastic optimization; Climate policy; Energy storage;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:84:y:2019:i:c:s0140988319302385. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.