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Optimizing design and dispatch of a renewable energy system

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  • Ogunmodede, Oluwaseun
  • Anderson, Kate
  • Cutler, Dylan
  • Newman, Alexandra

Abstract

Renewable energy technologies are becoming increasingly important due to their cost-competitiveness, and because of enhanced climate concerns. We demonstrate the capabilities of an integer-programming optimization model that minimizes capital (investment) and operational costs, and utility charges, while adhering to system sizing constraints, demand requirements, and interoperability characteristics of the systems chosen. The model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies, while simultaneously optimizing the corresponding dispatch strategy. Our case studies explore several venues, i.e., a small campus and a local hospital, with complex utility rate tariffs, multi-technology integration opportunities, and incentives for renewable power production. Using an optimization model, versus applying rules of thumb, can produce millions of dollars in savings over a 25-year time horizon and result in thousands of kilowatts of installed renewable energy.

Suggested Citation

  • Ogunmodede, Oluwaseun & Anderson, Kate & Cutler, Dylan & Newman, Alexandra, 2021. "Optimizing design and dispatch of a renewable energy system," Applied Energy, Elsevier, vol. 287(C).
    • Handle: RePEc:eee:appene:v:287:y:2021:i:c:s0306261921000829
    DOI: 10.1016/j.apenergy.2021.116527
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    as
    1. Cuesta, M.A. & Castillo-Calzadilla, T. & Borges, C.E., 2020. "A critical analysis on hybrid renewable energy modeling tools: An emerging opportunity to include social indicators to optimise systems in small communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    2. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.
    3. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    4. Mashayekh, Salman & Stadler, Michael & Cardoso, Gonçalo & Heleno, Miguel, 2017. "A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids," Applied Energy, Elsevier, vol. 187(C), pages 154-168.
    5. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    6. Sengupta, Manajit & Xie, Yu & Lopez, Anthony & Habte, Aron & Maclaurin, Galen & Shelby, James, 2018. "The National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 51-60.
    7. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    8. O'Shaughnessy, Eric & Cutler, Dylan & Ardani, Kristen & Margolis, Robert, 2018. "Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings," Applied Energy, Elsevier, vol. 213(C), pages 11-21.
    9. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    10. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    11. Upadhyay, Subho & Sharma, M.P., 2014. "A review on configurations, control and sizing methodologies of hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 47-63.
    12. Welder, Lara & Ryberg, D.Severin & Kotzur, Leander & Grube, Thomas & Robinius, Martin & Stolten, Detlef, 2018. "Spatio-temporal optimization of a future energy system for power-to-hydrogen applications in Germany," Energy, Elsevier, vol. 158(C), pages 1130-1149.
    13. 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.
    14. Guanglei Wang & Hassan Hijazi, 2018. "Mathematical programming methods for microgrid design and operations: a survey on deterministic and stochastic approaches," Computational Optimization and Applications, Springer, vol. 71(2), pages 553-608, November.
    15. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    16. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    17. Pruitt, Kristopher A. & Braun, Robert J. & Newman, Alexandra M., 2013. "Evaluating shortfalls in mixed-integer programming approaches for the optimal design and dispatch of distributed generation systems," Applied Energy, Elsevier, vol. 102(C), pages 386-398.
    18. Muratori, Matteo & Elgqvist, Emma & Cutler, Dylan & Eichman, Joshua & Salisbury, Shawn & Fuller, Zachary & Smart, John, 2019. "Technology solutions to mitigate electricity cost for electric vehicle DC fast charging," Applied Energy, Elsevier, vol. 242(C), pages 415-423.
    19. Lee, Kyoung-Ho & Lee, Dong-Won & Baek, Nam-Choon & Kwon, Hyeok-Min & Lee, Chang-Jun, 2012. "Preliminary determination of optimal size for renewable energy resources in buildings using RETScreen," Energy, Elsevier, vol. 47(1), pages 83-96.
    20. Atabay, Dennis, 2017. "An open-source model for optimal design and operation of industrial energy systems," Energy, Elsevier, vol. 121(C), pages 803-821.
    21. Merkel, Erik & McKenna, Russell & Fichtner, Wolf, 2015. "Optimisation of the capacity and the dispatch of decentralised micro-CHP systems: A case study for the UK," Applied Energy, Elsevier, vol. 140(C), pages 120-134.
    22. Pfenninger, Stefan & DeCarolis, Joseph & Hirth, Lion & Quoilin, Sylvain & Staffell, Iain, 2017. "The importance of open data and software: Is energy research lagging behind?," Energy Policy, Elsevier, vol. 101(C), pages 211-215.
    23. Neto, Pedro Bezerra Leite & Saavedra, Osvaldo R. & Oliveira, Denisson Q., 2020. "The effect of complementarity between solar, wind and tidal energy in isolated hybrid microgrids," Renewable Energy, Elsevier, vol. 147(P1), pages 339-355.
    24. Buoro, Dario & Pinamonti, Piero & Reini, Mauro, 2014. "Optimization of a Distributed Cogeneration System with solar district heating," Applied Energy, Elsevier, vol. 124(C), pages 298-308.
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    4. Yu, Wenjin & Zhou, Peijian & Miao, Zhouqian & Zhao, Haoru & Mou, Jiegang & Zhou, Wenqiang, 2024. "Energy performance prediction of pump as turbine (PAT) based on PIWOA-BP neural network," Renewable Energy, Elsevier, vol. 222(C).
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    6. Igogo, Tsisilile & Awuah-Offei, Kwame & Newman, Alexandra & Lowder, Travis & Engel-Cox, Jill, 2021. "Integrating renewable energy into mining operations: Opportunities, challenges, and enabling approaches," Applied Energy, Elsevier, vol. 300(C).
    7. Huang, Yan & Ju, Yuntao & Ma, Kang & Short, Michael & Chen, Tao & Zhang, Ruosi & Lin, Yi, 2022. "Three-phase optimal power flow for networked microgrids based on semidefinite programming convex relaxation," Applied Energy, Elsevier, vol. 305(C).
    8. Yuanyuan He & Luxin Wan & Manli Zhang & Huijuan Zhao, 2022. "Regional Renewable Energy Installation Optimization Strategies with Renewable Portfolio Standards in China," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    9. Kong, Xue & Wang, Hongye & Li, Nan & Mu, Hailin, 2022. "Multi-objective optimal allocation and performance evaluation for energy storage in energy systems," Energy, Elsevier, vol. 253(C).
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    11. Kazi Sifatul Islam & Samiul Hasan & Tamal Chowdhury & Hemal Chowdhury & Sadiq M. Sait, 2022. "Outage Survivability Investigation of a PV/Battery/CHP System in a Hospital Building in Texas," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
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    14. Macmillan, Madeline & Zolan, Alexander & Bazilian, Morgan & Villa, Daniel L., 2024. "Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty," Applied Energy, Elsevier, vol. 368(C).

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