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A Technology Selection and Operation (TSO) optimisation model for distributed energy systems: Mathematical formulation and case study

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  • Cedillos Alvarado, Dagoberto
  • Acha, Salvador
  • Shah, Nilay
  • Markides, Christos N.

Abstract

This paper presents a model which simultaneously optimises the selection and operation of technologies for distributed energy systems in buildings. The Technology Selection and Operation (TSO) model enables a new approach for the optimal selection and operation of energy system technologies that encompasses whole life costing, carbon emissions as well as real-time energy prices and demands; thus, providing a more comprehensive result than current methods. Utilizing historic metered energy demands, projected energy prices and a portfolio of available technologies, the mathematical model simultaneously solves for an optimal technology selection and operational strategy for a determined building based on a preferred objective: minimizing cost and/or minimizing carbon emissions. The TSO is a comprehensive and novel techno-economic model, capable of providing decision makers an optimal selection from a portfolio of available energy technologies. The current portfolio of available technologies is composed of various combined heat and power (CHP) and organic Rankine cycle (ORC) units. The TSO model framework is data-driven and therefore presents a high level of flexibility with respect to time granularity, period of analysis and the technology portfolio. A case study depicts the capabilities of the model; optimisation results under different temporal arrangements and technology options are showcased. Overall, the TSO model provides meaningful insights that allow stakeholders to make technology investment decisions with greater assurance.

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  • Cedillos Alvarado, Dagoberto & Acha, Salvador & Shah, Nilay & Markides, Christos N., 2016. "A Technology Selection and Operation (TSO) optimisation model for distributed energy systems: Mathematical formulation and case study," Applied Energy, Elsevier, vol. 180(C), pages 491-503.
  • Handle: RePEc:eee:appene:v:180:y:2016:i:c:p:491-503
    DOI: 10.1016/j.apenergy.2016.08.013
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    Cited by:

    1. Alberto Fichera & Alessandro Pluchino & Rosaria Volpe, 2020. "Modelling Energy Distribution in Residential Areas: A Case Study Including Energy Storage Systems in Catania, Southern Italy," Energies, MDPI, Open Access Journal, vol. 13(14), pages 1-21, July.
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    6. Le Brun, Niccolo & Simpson, Michael & Acha, Salvador & Shah, Nilay & Markides, Christos N., 2020. "Techno-economic potential of low-temperature, jacket-water heat recovery from stationary internal combustion engines with organic Rankine cycles: A cross-sector food-retail study," Applied Energy, Elsevier, vol. 274(C).
    7. Fichera, Alberto & Pluchino, Alessandro & Volpe, Rosaria, 2018. "A multi-layer agent-based model for the analysis of energy distribution networks in urban areas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 710-725.
    8. Gimelli, A. & Mottola, F. & Muccillo, M. & Proto, D. & Amoresano, A. & Andreotti, A. & Langella, G., 2019. "Optimal configuration of modular cogeneration plants integrated by a battery energy storage system providing peak shaving service," Applied Energy, Elsevier, vol. 242(C), pages 974-993.
    9. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    10. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Weng, Peifen & Ren, Jianxing, 2018. "Design and operation optimization of organic Rankine cycle coupled trigeneration systems," Energy, Elsevier, vol. 142(C), pages 666-677.
    11. Olympios, Andreas V. & Pantaleo, Antonio M. & Sapin, Paul & Markides, Christos N., 2020. "On the value of combined heat and power (CHP) systems and heat pumps incentralised and distributed heating systems: Lessons from multi-fidelitymodelling approaches," Applied Energy, Elsevier, vol. 274(C).
    12. Alberto Fichera & Mattia Frasca & Rosaria Volpe, 2020. "A cost-based approach for evaluating the impact of a network of distributed energy systems on the centralized energy supply," Energy & Environment, , vol. 31(1), pages 77-87, February.
    13. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    14. Delangle, Axelle & Lambert, Romain S.C. & Shah, Nilay & Acha, Salvador & Markides, Christos N., 2017. "Modelling and optimising the marginal expansion of an existing district heating network," Energy, Elsevier, vol. 140(P1), pages 209-223.
    15. Acha, Salvador & Mariaud, Arthur & Shah, Nilay & Markides, Christos N., 2018. "Optimal design and operation of distributed low-carbon energy technologies in commercial buildings," Energy, Elsevier, vol. 142(C), pages 578-591.
    16. Acha, Salvador & Le Brun, Niccolo & Damaskou, Maria & Fubara, Tekena Craig & Mulgundmath, Vinay & Markides, Christos N. & Shah, Nilay, 2020. "Fuel cells as combined heat and power systems in commercial buildings: A case study in the food-retail sector," Energy, Elsevier, vol. 206(C).
    17. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, Open Access Journal, vol. 11(4), pages 1-26, March.
    18. Simpson, Michael C. & Chatzopoulou, Maria Anna & Oyewunmi, Oyeniyi A. & Le Brun, Niccolo & Sapin, Paul & Markides, Christos N., 2019. "Technoeconomic analysis of internal combustion engine – organic Rankine cycle systems for combined heat and power in energy-intensive buildings," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    19. Nikunj Gangar & Sandro Macchietto & Christos N. Markides, 2020. "Recovery and Utilization of Low-Grade Waste Heat in the Oil-Refining Industry Using Heat Engines and Heat Pumps: An International Technoeconomic Comparison," Energies, MDPI, Open Access Journal, vol. 13(10), pages 1-29, May.
    20. Alfredo Gimelli & Massimiliano Muccillo, 2018. "The Key Role of the Vector Optimization Algorithm and Robust Design Approach for the Design of Polygeneration Systems," Energies, MDPI, Open Access Journal, vol. 11(4), pages 1-21, April.
    21. Mariaud, Arthur & Acha, Salvador & Ekins-Daukes, Ned & Shah, Nilay & Markides, Christos N., 2017. "Integrated optimisation of photovoltaic and battery storage systems for UK commercial buildings," Applied Energy, Elsevier, vol. 199(C), pages 466-478.
    22. Fichera, Alberto & Frasca, Mattia & Volpe, Rosaria, 2017. "Complex networks for the integration of distributed energy systems in urban areas," Applied Energy, Elsevier, vol. 193(C), pages 336-345.
    23. Chakrabarti, Auyon & Proeglhoef, Rafael & Turu, Gonzalo Bustos & Lambert, Romain & Mariaud, Arthur & Acha, Salvador & Markides, Christos N. & Shah, Nilay, 2019. "Optimisation and analysis of system integration between electric vehicles and UK decentralised energy schemes," Energy, Elsevier, vol. 176(C), pages 805-815.

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