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A regional energy planning methodology including renewable energy sources and environmental constraints

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  • Cormio, C.
  • Dicorato, M.
  • Minoia, A.
  • Trovato, M.
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    Abstract

    In this paper, a bottom-up energy system optimisation model is proposed in order to support planning policies for promoting the use of renewable energy sources. A linear programming optimisation methodology based on the energy flow optimisation model (EFOM) is adopted, detailing the primary energy sources exploitation (including biomass, solid waste, process by-products), power and heat generation, emissions and end-use sectors. The modelling framework is enhanced in order to adapt the model to the characteristics and requirements of the region under investigation. In particular, a detailed description of the industrial cogeneration system, that turns out to be the more efficient and increasingly spread, is incorporated in the regional model. The optimisation process, aiming to reduce environmental impact and economical efforts, provides feasible generation settlements that take into account the installation of combined cycle power plants, wind power, solid-waste and biomass exploitation together with industrial combined heat and power (CHP) systems. The proposed methodology is applied to case of the Apulia region in the Southern Italy.

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    Bibliographic Info

    Article provided by Elsevier in its journal Renewable and Sustainable Energy Reviews.

    Volume (Year): 7 (2003)
    Issue (Month): 2 (April)
    Pages: 99-130

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    Handle: RePEc:eee:rensus:v:7:y:2003:i:2:p:99-130

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    Related research

    Keywords: Regional energy planning Linear programming optimisation EFOM methodology Renewable energy Cogeneration systems;

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    Cited by:
    1. Nogueira, Carlos Eduardo Camargo & Vidotto, Magno Luiz & Niedzialkoski, Rosana Krauss & de Souza, Samuel Nelson Melegari & Chaves, Luiz Inácio & Edwiges, Thiago & Santos, Darlisson Bentes dos & Wernc, 2014. "Sizing and simulation of a photovoltaic-wind energy system using batteries, applied for a small rural property located in the south of Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 151-157.
    2. Liu, Y. & Huang, G.H. & Cai, Y.P. & Cheng, G.H. & Niu, Y.T. & An, K., 2009. "Development of an inexact optimization model for coupled coal and power management in North China," Energy Policy, Elsevier, vol. 37(11), pages 4345-4363, November.
    3. Raphaële Thery & Pascale Zarate, 2009. "Energy planning: a multi-level and multicriteria decision making structure proposal," Central European Journal of Operations Research, Springer, vol. 17(3), pages 265-274, September.
    4. Xiaohua, Wang & Zhenmin, Feng, 2005. "Study on affecting factors and standard of rural household energy consumption in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 9(1), pages 101-110, February.
    5. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    6. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    7. Ouammi, A. & Sacile, R. & Mimet, A., 2010. "Wind energy potential in Liguria region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 289-300, January.
    8. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Tan, Q., 2009. "Identification of optimal strategies for energy management systems planning under multiple uncertainties," Applied Energy, Elsevier, vol. 86(4), pages 480-495, April.
    9. Daniel, J. & Dicorato, M. & Forte, G. & Iniyan, S. & Trovato, M., 2009. "A methodology for the electrical energy system planning of Tamil Nadu state (India)," Energy Policy, Elsevier, vol. 37(3), pages 904-914, March.
    10. Koo, Jamin & Han, Kyusang & Yoon, En Sup, 2011. "Integration of CCS, emissions trading and volatilities of fuel prices into sustainable energy planning, and its robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 665-672, January.
    11. Hu, Qing & Huang, Guohe & Cai, Yanpeng & Huang, Ying, 2011. "Feasibility-based inexact fuzzy programming for electric power generation systems planning under dual uncertainties," Applied Energy, Elsevier, vol. 88(12), pages 4642-4654.
    12. Zhu, Y. & Li, Y.P. & Huang, G.H., 2013. "Planning carbon emission trading for Beijing's electric power systems under dual uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 113-128.
    13. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.

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