IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v276y2020ics0306261920310217.html
   My bibliography  Save this article

Distributionally robust optimization for power trading of waste-to-energy plants under uncertainty

Author

Listed:
  • Hu, Chenlian
  • Liu, Xiao
  • Lu, Jie
  • Wang, Chi-Hwa

Abstract

Waste-to-energy (WTE) plants are operated worldwide to address the management of municipal solid waste. Against this background, an increasing number of WTE plants serve as combined heat and power (CHP) producers that supply heat to the heating systems in local districts and trade electricity in the regional power markets. This paper studies a short-term operation planning problem of determining effective power trading strategies for WTE CHP plants that participate in day-ahead markets. A two-stage distributionally robust optimization (DRO) model is developed with the consideration of uncertain electricity prices, waste supply, and district heating demand. These different kinds of uncertainty are captured by an ambiguity set that contains a collection of possible probability distributions of the uncertain parameters. The two-stage DRO model seeks to ascertain a power trading strategy that maximizes the expected profit of a WTE CHP plant on a regular operating day under the worst-case distribution in the ambiguity set. As the DRO model is intractable, a solution method based on linear decision rule techniques is designed to reformulate the model as a tractable robust linear program. To test the applicability of the DRO model, a case study with real-world data is conducted. The computational results show that the two-stage DRO model can facilitate a WTE CHP plant in obtaining economical and robust power trading strategies for regular operating days in a day-ahead market. Furthermore, the impacts of the parameters in the ambiguity set on deriving robust power trading strategies for WTE CHP plants are investigated.

Suggested Citation

  • Hu, Chenlian & Liu, Xiao & Lu, Jie & Wang, Chi-Hwa, 2020. "Distributionally robust optimization for power trading of waste-to-energy plants under uncertainty," Applied Energy, Elsevier, vol. 276(C).
    • Handle: RePEc:eee:appene:v:276:y:2020:i:c:s0306261920310217
    DOI: 10.1016/j.apenergy.2020.115509
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920310217
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.115509?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. Kumbartzky, Nadine & Schacht, Matthias & Schulz, Katrin & Werners, Brigitte, 2017. "Optimal operation of a CHP plant participating in the German electricity balancing and day-ahead spot market," European Journal of Operational Research, Elsevier, vol. 261(1), pages 390-404.
    2. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    3. Barigozzi, G. & Perdichizzi, A. & Ravelli, S., 2014. "Performance prediction and optimization of a waste-to-energy cogeneration plant with combined wet and dry cooling system," Applied Energy, Elsevier, vol. 115(C), pages 65-74.
    4. Rong, Aiying & Lahdelma, Risto, 2007. "Efficient algorithms for combined heat and power production planning under the deregulated electricity market," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1219-1245, January.
    5. Gu, Tianbao & Yin, Chungen & Ma, Wenchao & Chen, Guanyi, 2019. "Municipal solid waste incineration in a packed bed: A comprehensive modeling study with experimental validation," Applied Energy, Elsevier, vol. 247(C), pages 127-139.
    6. Tomić, Tihomir & Dominković, Dominik Franjo & Pfeifer, Antun & Schneider, Daniel Rolph & Pedersen, Allan Schrøder & Duić, Neven, 2017. "Waste to energy plant operation under the influence of market and legislation conditioned changes," Energy, Elsevier, vol. 137(C), pages 1119-1129.
    7. Wolfram Wiesemann & Daniel Kuhn & Melvyn Sim, 2014. "Distributionally Robust Convex Optimization," Operations Research, INFORMS, vol. 62(6), pages 1358-1376, December.
    8. Zhang, Jingxin & Mao, Liwei & Nithya, Karthikeyan & Loh, Kai-Chee & Dai, Yanjun & He, Yiliang & Wah Tong, Yen, 2019. "Optimizing mixing strategy to improve the performance of an anaerobic digestion waste-to-energy system for energy recovery from food waste," Applied Energy, Elsevier, vol. 249(C), pages 28-36.
    9. Makkonen, Simo & Lahdelma, Risto, 2006. "Non-convex power plant modelling in energy optimisation," European Journal of Operational Research, Elsevier, vol. 171(3), pages 1113-1126, June.
    10. Joel Goh & Melvyn Sim, 2010. "Distributionally Robust Optimization and Its Tractable Approximations," Operations Research, INFORMS, vol. 58(4-part-1), pages 902-917, August.
    11. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    12. Touš, Michal & Pavlas, Martin & Putna, Ondřej & Stehlík, Petr & Crha, Lukáš, 2015. "Combined heat and power production planning in a waste-to-energy plant on a short-term basis," Energy, Elsevier, vol. 90(P1), pages 137-147.
    13. Fang, Tingting & Lahdelma, Risto, 2016. "Optimization of combined heat and power production with heat storage based on sliding time window method," Applied Energy, Elsevier, vol. 162(C), pages 723-732.
    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. Wang, Zhimeng & Xuan, Ang & Shen, Xinwei & Du, Yunfei & Sun, Hongbin, 2023. "A robust planning model for offshore microgrid considering tidal power and desalination," Applied Energy, Elsevier, vol. 350(C).
    2. Afrouz Rahmandoust & Ashkan Hafezalkotob & Bijan Rahmani Parchikolaei & Amir Azizi, 2023. "Government intervention in municipal waste collection with a sustainable approach: a robust bi-level problem," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(4), pages 3323-3351, April.
    3. Elisabetta Allevi & Maria Elena Giuli & Ruth Domínguez & Giorgia Oggioni, 2023. "Evaluating the role of waste-to-energy and cogeneration units in district heatings and electricity markets," Computational Management Science, Springer, vol. 20(1), pages 1-49, December.
    4. Xu, Jiuping & Huang, Yidan & Shi, Yi & Li, Ruolan, 2022. "Reverse supply chain management approach for municipal solid waste with waste sorting subsidy policy," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    5. He, Shuaijia & Gao, Hongjun & Wang, Lingfeng & Xiang, Yingmeng & Liu, Junyong, 2020. "Distributionally robust planning for integrated energy systems incorporating electric-thermal demand response," Energy, Elsevier, vol. 213(C).
    6. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Li, Bingkang & Fei, Haoran & Zhang, Yiyue & Wang, Xuejie, 2023. "Multi-objective distributionally robust optimization for hydrogen-involved total renewable energy CCHP planning under source-load uncertainties," Applied Energy, Elsevier, vol. 342(C).
    7. Wu, Chuantao & Lin, Xiangning & Sui, Quan & Wang, Zhixun & Feng, Zhongnan & Li, Zhengtian, 2021. "Two-stage self-scheduling of battery swapping station in day-ahead energy and frequency regulation markets," Applied Energy, Elsevier, vol. 283(C).
    8. Li, Bingkang & Zhao, Huiru & Wang, Xuejie & Zhao, Yihang & Zhang, Yuanyuan & Lu, Hao & Wang, Yuwei, 2022. "Distributionally robust offering strategy of the aggregator integrating renewable energy generator and energy storage considering uncertainty and connections between the mid-to-long-term and spot elec," Renewable Energy, Elsevier, vol. 201(P1), pages 400-417.
    9. Gafti, Morteza & Sabouhi, Fatemeh & Bozorgi-Amiri, Ali & Jamili, Amin, 2023. "A multi-period location-routing model for waste-to-energy supply chain: A case study," Applied Energy, Elsevier, vol. 337(C).
    10. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    11. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Shi, Lin & Li, Bingkang, 2023. "TimeGAN based distributionally robust optimization for biomass-photovoltaic-hydrogen scheduling under source-load-market uncertainties," Energy, Elsevier, vol. 284(C).
    12. Cao, Jiaxin & Yang, Bo & Zhu, Shanying & Chung, Chi Yung & Guan, Xinping, 2022. "Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling," Applied Energy, Elsevier, vol. 311(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. Putna, Ondřej & Janošťák, František & Šomplák, Radovan & Pavlas, Martin, 2018. "Demand modelling in district heating systems within the conceptual design of a waste-to-energy plant," Energy, Elsevier, vol. 163(C), pages 1125-1139.
    2. Zhi Chen & Melvyn Sim & Huan Xu, 2019. "Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets," Operations Research, INFORMS, vol. 67(5), pages 1328-1344, September.
    3. Viet Anh Nguyen & Daniel Kuhn & Peyman Mohajerin Esfahani, 2018. "Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator," Papers 1805.07194, arXiv.org.
    4. L. Jeff Hong & Zhiyuan Huang & Henry Lam, 2021. "Learning-Based Robust Optimization: Procedures and Statistical Guarantees," Management Science, INFORMS, vol. 67(6), pages 3447-3467, June.
    5. Longsheng Sun & Mark H. Karwan & Changhyun Kwon, 2018. "Generalized Bounded Rationality and Robust Multicommodity Network Design," Operations Research, INFORMS, vol. 66(1), pages 42-57, 1-2.
    6. Antonio J. Conejo & Nicholas G. Hall & Daniel Zhuoyu Long & Runhao Zhang, 2021. "Robust Capacity Planning for Project Management," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1533-1550, October.
    7. Wang, Chong & Liu, Kaiyuan & Zhang, Canrong & Miao, Lixin, 2024. "Distributionally robust chance-constrained optimization for the integrated berth allocation and quay crane assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 182(C).
    8. Steffen Rebennack, 2022. "Data-driven stochastic optimization for distributional ambiguity with integrated confidence region," Journal of Global Optimization, Springer, vol. 84(2), pages 255-293, October.
    9. Yang, Yongjian & Yin, Yunqiang & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Dhamotharan, Lalitha, 2023. "Distributionally robust multi-period location-allocation with multiple resources and capacity levels in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1042-1062.
    10. Wang, Fan & Zhang, Chao & Zhang, Hui & Xu, Liang, 2021. "Short-term physician rescheduling model with feature-driven demand for mental disorders outpatients," Omega, Elsevier, vol. 105(C).
    11. Liu, Haiyan & Mao, Tiantian, 2022. "Distributionally robust reinsurance with Value-at-Risk and Conditional Value-at-Risk," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 393-417.
    12. Giuseppe Pinto & Elnaz Abdollahi & Alfonso Capozzoli & Laura Savoldi & Risto Lahdelma, 2019. "Optimization and Multicriteria Evaluation of Carbon-neutral Technologies for District Heating," Energies, MDPI, vol. 12(9), pages 1-19, April.
    13. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.
    14. Huyên Pham & Xiaoli Wei & Chao Zhou, 2022. "Portfolio diversification and model uncertainty: A robust dynamic mean‐variance approach," Mathematical Finance, Wiley Blackwell, vol. 32(1), pages 349-404, January.
    15. Ebenezer Fiifi Emire Atta Mills & Bo Yu & Kailin Zeng, 2019. "Satisfying Bank Capital Requirements: A Robustness Approach in a Modified Roy Safety-First Framework," Mathematics, MDPI, vol. 7(7), pages 1-20, July.
    16. Chen, Qingxin & Ma, Shoufeng & Li, Hongming & Zhu, Ning & He, Qiao-Chu, 2024. "Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    17. Postek, Krzysztof & Ben-Tal, A. & den Hertog, Dick & Melenberg, Bertrand, 2015. "Exact Robust Counterparts of Ambiguous Stochastic Constraints Under Mean and Dispersion Information," Other publications TiSEM d718e419-a375-4707-b206-e, Tilburg University, School of Economics and Management.
    18. Keivan Rahimi-Adli & Egidio Leo & Benedikt Beisheim & Sebastian Engell, 2021. "Optimisation of the Operation of an Industrial Power Plant under Steam Demand Uncertainty," Energies, MDPI, vol. 14(21), pages 1-28, November.
    19. Mohseni, Shayan & Pishvaee, Mir Saman, 2023. "Energy trading and scheduling in networked microgrids using fuzzy bargaining game theory and distributionally robust optimization," Applied Energy, Elsevier, vol. 350(C).
    20. Marla, Lavanya & Rikun, Alexander & Stauffer, Gautier & Pratsini, Eleni, 2020. "Robust modeling and planning: Insights from three industrial applications," Operations Research Perspectives, Elsevier, vol. 7(C).

    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:appene:v:276:y:2020:i:c:s0306261920310217. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.