IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v156y2020icp1089-1099.html
   My bibliography  Save this article

MATPLAN: A probability-based planning tool for cost-effective grid integration of renewable energy

Author

Listed:
  • Chen, Tao
  • Pipattanasomporn, Manisa
  • Rahman, Imran
  • Jing, Zejia
  • Rahman, Saifur

Abstract

This paper describes the developed MATPLAN - a probability-based production costing tool that treats renewable energy sources as candidates in a power system expansion planning study. Similar to the structure of the well-known Wien Automatic System Planning (WASP) package, MATPLAN comprises six modules: LOAD-CALC, EXIST-GEN, CANDI-GEN, CONFIG, OPTIMIZE and ELCC. MATPLAN takes into account the variable nature of renewable energy sources, including both solar and wind farms, and allows a user to consider renewable energy as options for expansion planning using a probability-based model. In contrast to the current practice that treats renewable energy sources as negative loads, MATPLAN enables system planners to take renewable sources as normal options for generation expansion planning problems, which can directly determine the optimal expansion policy and ELCC analysis of a system with high renewable penetration. MATPLAN is also designed as an open access software package which academics and practitioners can adapt to their specific situations and run many case studies as a screening tool. In the case studies, the tool was validated by comparing its resulting optimal expansion planning plan against that of the well-known WASP package and further tested using realistic field data. The complete MATPLAN code repository has been released under open-source licenses for public access, URL: https://github.com/wasp2019/MATPLAN. MATPLAN Wiki is also available, providing MATPLAN overview, features, user guides and developer resources.

Suggested Citation

  • Chen, Tao & Pipattanasomporn, Manisa & Rahman, Imran & Jing, Zejia & Rahman, Saifur, 2020. "MATPLAN: A probability-based planning tool for cost-effective grid integration of renewable energy," Renewable Energy, Elsevier, vol. 156(C), pages 1089-1099.
    • Handle: RePEc:eee:renene:v:156:y:2020:i:c:p:1089-1099
    DOI: 10.1016/j.renene.2020.04.145
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120306832
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.04.145?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. George, Mel & Banerjee, Rangan, 2011. "A methodology for analysis of impacts of grid integration of renewable energy," Energy Policy, Elsevier, vol. 39(3), pages 1265-1276, March.
    2. Ebers Broughel, Anna, 2019. "Impact of state policies on generating capacity for production of electricity and combined heat and power from forest biomass in the United States," Renewable Energy, Elsevier, vol. 134(C), pages 1163-1172.
    3. Voorspools, Kris R. & D'haeseleer, William D., 2006. "An analytical formula for the capacity credit of wind power," Renewable Energy, Elsevier, vol. 31(1), pages 45-54.
    4. Tapetado, Pablo & Usaola, Julio, 2019. "Capacity credits of wind and solar generation: The Spanish case," Renewable Energy, Elsevier, vol. 143(C), pages 164-175.
    5. Ueckerdt, Falko & Brecha, Robert & Luderer, Gunnar, 2015. "Analyzing major challenges of wind and solar variability in power systems," Renewable Energy, Elsevier, vol. 81(C), pages 1-10.
    6. 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.
    7. Pinto, Mauro S.S. & Miranda, Vladimiro & Saavedra, Osvaldo R., 2016. "Risk and unit commitment decisions in scenarios of wind power uncertainty," Renewable Energy, Elsevier, vol. 97(C), pages 550-558.
    8. Murphy, Sinnott & Apt, Jay & Moura, John & Sowell, Fallaw, 2018. "Resource adequacy risks to the bulk power system in North America," Applied Energy, Elsevier, vol. 212(C), pages 1360-1376.
    9. Dehghani, Hamed & Vahidi, Behrooz & Hosseinian, Seyed Hossein, 2017. "Wind farms participation in electricity markets considering uncertainties," Renewable Energy, Elsevier, vol. 101(C), pages 907-918.
    10. Zhou, Ella & Cole, Wesley & Frew, Bethany, 2018. "Valuing variable renewable energy for peak demand requirements," Energy, Elsevier, vol. 165(PA), pages 499-511.
    11. Zeng, Bo & Wei, Xuan & Zhao, Dongbo & Singh, Chanan & Zhang, Jianhua, 2018. "Hybrid probabilistic-possibilistic approach for capacity credit evaluation of demand response considering both exogenous and endogenous uncertainties," Applied Energy, Elsevier, vol. 229(C), pages 186-200.
    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. Daniel Icaza-Alvarez & Nestor Daniel Galan-Hernandez & Eber Enrique Orozco-Guillen & Francisco Jurado, 2023. "Smart Energy Planning in the Midst of a Technological and Political Change towards a 100% Renewable System in Mexico by 2050," Energies, MDPI, vol. 16(20), pages 1-26, October.
    2. Bromley-Dulfano, Isaac & Florez, Julian & Craig, Michael T., 2021. "Reliability benefits of wide-area renewable energy planning across the Western United States," Renewable Energy, Elsevier, vol. 179(C), pages 1487-1499.

    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. Wen, Lei & Song, Qianqian, 2023. "ELCC-based capacity value estimation of combined wind - storage system using IPSO algorithm," Energy, Elsevier, vol. 263(PB).
    2. Xu, Tingting & Gao, Weijun & Qian, Fanyue & Li, Yanxue, 2022. "The implementation limitation of variable renewable energies and its impacts on the public power grid," Energy, Elsevier, vol. 239(PA).
    3. Niina Helistö & Juha Kiviluoma & Hannele Holttinen & Jose Daniel Lara & Bri‐Mathias Hodge, 2019. "Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    4. Sanghyun Hong & Barry W. Brook, 2018. "Economic Feasibility of Energy Supply by Small Modular Nuclear Reactors on Small Islands: Case Studies of Jeju, Tasmania and Tenerife," Energies, MDPI, vol. 11(10), pages 1-11, September.
    5. Tsai, Chen-Hao & Figueroa-Acevedo, Armando & Boese, Maire & Li, Yifan & Mohan, Nihal & Okullo, James & Heath, Brandon & Bakke, Jordan, 2020. "Challenges of planning for high renewable futures: Experience in the U.S. midcontinent electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    6. Buchholz, Stefanie & Gamst, Mette & Pisinger, David, 2020. "Sensitivity analysis of time aggregation techniques applied to capacity expansion energy system models," Applied Energy, Elsevier, vol. 269(C).
    7. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Ruan, Yingjun, 2020. "Capacity credit and market value analysis of photovoltaic integration considering grid flexibility requirements," Renewable Energy, Elsevier, vol. 159(C), pages 908-919.
    8. Stefanie Buchholz & Mette Gamst & David Pisinger, 2020. "Finding a Portfolio of Near-Optimal Aggregated Solutions to Capacity Expansion Energy System Models," SN Operations Research Forum, Springer, vol. 1(1), pages 1-40, March.
    9. Kat, Bora, 2023. "Clean energy transition in the Turkish power sector: A techno-economic analysis with a high-resolution power expansion model," Utilities Policy, Elsevier, vol. 82(C).
    10. Moradi-Sepahvand, Mojtaba & Amraee, Turaj, 2021. "Integrated expansion planning of electric energy generation, transmission, and storage for handling high shares of wind and solar power generation," Applied Energy, Elsevier, vol. 298(C).
    11. Nayak-Luke, Richard & Bañares-Alcántara, René & Collier, Sam, 2021. "Quantifying network flexibility requirements in terms of energy storage," Renewable Energy, Elsevier, vol. 167(C), pages 869-882.
    12. Alexis Tantet & Philippe Drobinski, 2021. "A Minimal System Cost Minimization Model for Variable Renewable Energy Integration: Application to France and Comparison to Mean-Variance Analysis," Energies, MDPI, vol. 14(16), pages 1-38, August.
    13. Busiswe Skosana & Mukwanga W. Siti & Nsilulu T. Mbungu & Sonu Kumar & Willy Mulumba, 2023. "An Evaluation of Potential Strategies in Renewable Energy Systems and Their Importance for South Africa—A Review," Energies, MDPI, vol. 16(22), pages 1-27, November.
    14. Botor, Benjamin & Böcker, Benjamin & Kallabis, Thomas & Weber, Christoph, 2021. "Information shocks and profitability risks for power plant investments – impacts of policy instruments," Energy Economics, Elsevier, vol. 102(C).
    15. Banaei, Mohsen & Oloomi-Buygi, Majid & Zabetian-Hosseini, Seyed-Mahdi, 2018. "Strategic gaming of wind power producers joined with thermal units in electricity markets," Renewable Energy, Elsevier, vol. 115(C), pages 1067-1074.
    16. Marshman, Daniel & Brear, Michael & Ring, Brendan, 2022. "Impact of unit commitment and RoCoF constraints on revenue sufficiency in decarbonising wholesale electricity markets," Energy Economics, Elsevier, vol. 106(C).
    17. Haeseldonckx, Dries & D'haeseleer, William, 2008. "The environmental impact of decentralised generation in an overall system context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(2), pages 437-454, February.
    18. Peter, Jakob & Wagner, Johannes, 2018. "Optimal Allocation of Variable Renewable Energy Considering Contributions to Security of Supply," EWI Working Papers 2018-2, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    19. Sun, Yinong & Frew, Bethany & Dalvi, Sourabh & Dhulipala, Surya C., 2022. "Insights into methodologies and operational details of resource adequacy assessment: A case study with application to a broader flexibility framework," Applied Energy, Elsevier, vol. 328(C).
    20. Andrychowicz, Mateusz & Olek, Blazej & Przybylski, Jakub, 2017. "Review of the methods for evaluation of renewable energy sources penetration and ramping used in the Scenario Outlook and Adequacy Forecast 2015. Case study for Poland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 703-714.

    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:renene:v:156:y:2020:i:c:p:1089-1099. 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.journals.elsevier.com/renewable-energy .

    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.