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On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation

Author

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  • Antonio Piacentino

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy)

  • Roberto Gallea

    (Sistema Informativo di Ateneo, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy)

  • Pietro Catrini

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy)

  • Fabio Cardona

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy)

  • Domenico Panno

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy)

Abstract

Cogeneration and trigeneration plants are widely recognized as promising technologies for increasing energy efficiency in buildings. However, their overall potential is scarcely exploited, due to the difficulties in achieving economic viability and the risk of investment related to uncertainties in future energy loads and prices. Several stochastic optimization models have been proposed in the literature to account for uncertainties, but these instruments share in a common reliance on user-defined probability functions for each stochastic parameter. Being such functions hard to predict, in this paper an analysis of the influence of erroneous estimation of the uncertain energy loads and prices on the optimal plant design and operation is proposed. With reference to a hotel building, a number of realistic scenarios is developed, exploring all the most frequent errors occurring in the estimation of energy loads and prices. Then, profit-oriented optimizations are performed for the examined scenarios, by means of a deterministic mixed integer linear programming algorithm. From a comparison between the achieved results, it emerges that: (i) the plant profitability is prevalently influenced by the average “spark-spread” (i.e., ratio between electricity and fuel price) and, secondarily, from the shape of the daily price profiles; (ii) the “optimal sizes” of the main components are scarcely influenced by the daily load profiles, while they are more strictly related with the average “power to heat” and “power to cooling” ratios of the building.

Suggested Citation

  • Antonio Piacentino & Roberto Gallea & Pietro Catrini & Fabio Cardona & Domenico Panno, 2016. "On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimation," Energies, MDPI, vol. 9(12), pages 1-31, December.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:12:p:1049-:d:85085
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    References listed on IDEAS

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    1. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty: Part I: Multiple time frame approach," Applied Energy, Elsevier, vol. 88(4), pages 1059-1067, April.
    2. Chicco, Gianfranco & Mancarella, Pierluigi, 2008. "Assessment of the greenhouse gas emissions from cogeneration and trigeneration systems. Part I: Models and indicators," Energy, Elsevier, vol. 33(3), pages 410-417.
    3. Rong, Aiying & Lahdelma, Risto, 2005. "An efficient linear programming model and optimization algorithm for trigeneration," Applied Energy, Elsevier, vol. 82(1), pages 40-63, September.
    4. Hu, Mengqi & Cho, Heejin, 2014. "A probability constrained multi-objective optimization model for CCHP system operation decision support," Applied Energy, Elsevier, vol. 116(C), pages 230-242.
    5. Kavvadias, K.C., 2016. "Energy price spread as a driving force for combined generation investments: A view on Europe," Energy, Elsevier, vol. 115(P3), pages 1632-1639.
    6. Smith, Amanda D. & Mago, Pedro J. & Fumo, Nelson, 2011. "Emissions spark spread and primary energy spark spread – Environmental and energy screening parameters for combined heating and power systems," Applied Energy, Elsevier, vol. 88(11), pages 3891-3897.
    7. Ersoz, Ibrahim & Colak, Uner, 2016. "Combined cooling, heat and power planning under uncertainty," Energy, Elsevier, vol. 109(C), pages 1016-1025.
    8. Piacentino, Antonio & Barbaro, Chiara, 2013. "A comprehensive tool for efficient design and operation of polygeneration-based energy μgrids serving a cluster of buildings. Part II: Analysis of the applicative potential," Applied Energy, Elsevier, vol. 111(C), pages 1222-1238.
    9. Sanaye, Sepehr & Khakpaay, Navid, 2014. "Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems," Energy, Elsevier, vol. 72(C), pages 145-158.
    10. Mancarella, Pierluigi & Chicco, Gianfranco, 2008. "Assessment of the greenhouse gas emissions from cogeneration and trigeneration systems. Part II: Analysis techniques and application cases," Energy, Elsevier, vol. 33(3), pages 418-430.
    11. Carpaneto, Enrico & Chicco, Gianfranco & Mancarella, Pierluigi & Russo, Angela, 2011. "Cogeneration planning under uncertainty. Part II: Decision theory-based assessment of planning alternatives," Applied Energy, Elsevier, vol. 88(4), pages 1075-1083, April.
    12. Smith, Amanda D. & Fumo, Nelson & Mago, Pedro J., 2011. "Spark spread - A screening parameter for combined heating and power systems," Applied Energy, Elsevier, vol. 88(5), pages 1494-1499, May.
    13. Lai, Sau Man & Hui, Chi Wai, 2009. "Feasibility and flexibility for a trigeneration system," Energy, Elsevier, vol. 34(10), pages 1693-1704.
    14. Arcuri, P. & Beraldi, P. & Florio, G. & Fragiacomo, P., 2015. "Optimal design of a small size trigeneration plant in civil users: A MINLP (Mixed Integer Non Linear Programming Model)," Energy, Elsevier, vol. 80(C), pages 628-641.
    15. Piacentino, Antonio & Barbaro, Chiara & Cardona, Fabio & Gallea, Roberto & Cardona, Ennio, 2013. "A comprehensive tool for efficient design and operation of polygeneration-based energy μgrids serving a cluster of buildings. Part I: Description of the method," Applied Energy, Elsevier, vol. 111(C), pages 1204-1221.
    16. Lai, Sau Man & Hui, Chi Wai, 2010. "Integration of trigeneration system and thermal storage under demand uncertainties," Applied Energy, Elsevier, vol. 87(9), pages 2868-2880, September.
    17. Mauser, Ingo & Müller, Jan & Allerding, Florian & Schmeck, Hartmut, 2016. "Adaptive building energy management with multiple commodities and flexible evolutionary optimization," Renewable Energy, Elsevier, vol. 87(P2), pages 911-921.
    18. Siler-Evans, Kyle & Morgan, M. Granger & Azevedo, Inês Lima, 2012. "Distributed cogeneration for commercial buildings: Can we make the economics work?," Energy Policy, Elsevier, vol. 42(C), pages 580-590.
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    Cited by:

    1. Dumitrascu Gheorghe & Feidt Michel & Popescu Aristotel & Grigorean Stefan, 2019. "Endoreversible Trigeneration Cycle Design Based on Finite Physical Dimensions Thermodynamics," Energies, MDPI, vol. 12(16), pages 1-21, August.
    2. Volpe, R. & Catrini, P. & Piacentino, A. & Fichera, A., 2022. "An agent-based model to support the preliminary design and operation of heating and power grids with cogeneration units and photovoltaic panels in densely populated areas," Energy, Elsevier, vol. 261(PB).
    3. Onishi, Viviani C. & Antunes, Carlos H. & Fraga, Eric S. & Cabezas, Heriberto, 2019. "Stochastic optimization of trigeneration systems for decision-making under long-term uncertainty in energy demands and prices," Energy, Elsevier, vol. 175(C), pages 781-797.

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