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Waste-to-energy based greenhouse heating: exploring viability conditions through optimisation models

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  • Chinese, Damiana
  • Meneghetti, Antonella
  • Nardin, Gioacchino

Abstract

An optimisation approach is proposed in order to assess the technical and economic feasibility of a renewable-energy-based greenhouse in North-Eastern Italy. A floor heating system that can exploit a low-temperature heat flow coming from the condenser of a waste-to-energy plant is chosen for the greenhouse and designed developing a non-linear optimisation model, solved by a genetic algorithm. In order to determine under what conditions the combination of a floor-heating-based greenhouse with a waste-to-energy plant can be profitable, a mixed integer optimisation model is introduced to allow selection of the minimum cost fuel solution as a function of different design variables of the greenhouse, such as indoor temperature settings and floor area. The ranges within which the renewable energy solution can lead to significant savings in comparison to traditional fossil fuel are identified both from the point of view of costs and of environmental impact. Furthermore, the sales prices for waste heat that would make investment in the renewable energy solution attractive for potential entrepreneurs are given.

Suggested Citation

  • Chinese, Damiana & Meneghetti, Antonella & Nardin, Gioacchino, 2005. "Waste-to-energy based greenhouse heating: exploring viability conditions through optimisation models," Renewable Energy, Elsevier, vol. 30(10), pages 1573-1586.
    • Handle: RePEc:eee:renene:v:30:y:2005:i:10:p:1573-1586
    DOI: 10.1016/j.renene.2004.11.008
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    References listed on IDEAS

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    1. Tari, Mehrdad Heidari & Soderstrom, Mats, 2002. "Optimisation modelling of industrial energy systems using MIND introducing the effect of material storage," European Journal of Operational Research, Elsevier, vol. 142(2), pages 419-433, October.
    2. Meneghetti, Antonella & Nardin, Gioacchino & Simeoni, Patrizia, 2002. "Waste-to-energy application in an industrial district," Applied Energy, Elsevier, vol. 72(1), pages 443-465, May.
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    1. Cai, Y.P. & Huang, G.H. & Tan, Q. & Yang, Z.F., 2009. "Planning of community-scale renewable energy management systems in a mixed stochastic and fuzzy environment," Renewable Energy, Elsevier, vol. 34(7), pages 1833-1847.
    2. Ajah, A.N. & Mesbah, A. & Grievink, J. & Herder, P.M. & Falcao, P.W. & Wennekes, S., 2008. "On the robustness, effectiveness and reliability of chemical and mechanical heat pumps for low-temperature heat source district heating: A comparative simulation-based analysis and evaluation," Energy, Elsevier, vol. 33(6), pages 908-929.
    3. Sayegh, M.A. & Danielewicz, J. & Nannou, T. & Miniewicz, M. & Jadwiszczak, P. & Piekarska, K. & Jouhara, H., 2017. "Trends of European research and development in district heating technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1183-1192.
    4. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
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    7. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Lin, Q.G. & Tan, Q., 2009. "Community-scale renewable energy systems planning under uncertainty--An interval chance-constrained programming approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 721-735, May.
    8. Chen, Yizhong & Lu, Hongwei & Li, Jing & Huang, Guohe & He, Li, 2016. "Regional planning of new-energy systems within multi-period and multi-option contexts: A case study of Fengtai, Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 356-372.
    9. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fu, D.Z., 2013. "Modeling for planning municipal electric power systems associated with air pollution control – A case study of Beijing," Energy, Elsevier, vol. 60(C), pages 168-186.
    10. Xie, Y.L. & Li, Y.P. & Huang, G.H. & Li, Y.F., 2010. "An interval fixed-mix stochastic programming method for greenhouse gas mitigation in energy systems under uncertainty," Energy, Elsevier, vol. 35(12), pages 4627-4644.
    11. Patrizio, P. & Chinese, D., 2016. "The impact of regional factors and new bio-methane incentive schemes on the structure, profitability and CO2 balance of biogas plants in Italy," Renewable Energy, Elsevier, vol. 99(C), pages 573-583.
    12. Leffler, Robert A. & Bradshaw, Craig R. & Groll, Eckhard A. & Garimella, Suresh V., 2012. "Alternative heat rejection methods for power plants," Applied Energy, Elsevier, vol. 92(C), pages 17-25.
    13. Rezaie, Behnaz & Rosen, Marc A., 2012. "District heating and cooling: Review of technology and potential enhancements," Applied Energy, Elsevier, vol. 93(C), pages 2-10.
    14. Ioan Aschilean & Gabriel Rasoi & Maria Simona Raboaca & Constantin Filote & Mihai Culcer, 2018. "Design and Concept of an Energy System Based on Renewable Sources for Greenhouse Sustainable Agriculture," Energies, MDPI, vol. 11(5), pages 1-12, May.
    15. Wu, Wei & Wang, Baolong & Shi, Wenxing & Li, Xianting, 2014. "Absorption heating technologies: A review and perspective," Applied Energy, Elsevier, vol. 130(C), pages 51-71.
    16. Hiremath, Rahul B. & Kumar, Bimlesh & Balachandra, P. & Ravindranath, N.H., 2010. "Bottom-up approach for decentralised energy planning: Case study of Tumkur district in India," Energy Policy, Elsevier, vol. 38(2), pages 862-874, February.
    17. Chae, Song Hwa & Kim, Sang Hun & Yoon, Sung-Geun & Park, Sunwon, 2010. "Optimization of a waste heat utilization network in an eco-industrial park," Applied Energy, Elsevier, vol. 87(6), pages 1978-1988, June.
    18. Nima Asgari & Matthew T. McDonald & Joshua M. Pearce, 2023. "Energy Modeling and Techno-Economic Feasibility Analysis of Greenhouses for Tomato Cultivation Utilizing the Waste Heat of Cryptocurrency Miners," Energies, MDPI, vol. 16(3), pages 1-42, January.

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