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Use of a probabilistic model to design energy transmission and distribution networks for low enthalpy geothermal multiple use schemes

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  • Gelegenis, John J.

Abstract

A probabilistic model is suggested for the design of transmission and distribution network of geothermal energy to potential consumption sites, in cases where the development of various competitive or complementary non-electrical uses is probable, within the broader area of a field. The model can be used to find out (a) the optimum network that may offer the best economic results to the agent who will undertake the development of the field, and (b) the corresponding selling price at which the thermal fluids will be supplied to the end users who are assumed to be other than the above agent. Model input data can be collected in the frame of an appropriate market study, which is roughly specified in this work and commented according to relevant experience from a Greek geothermal field. Finally, applicability of the model is demonstrated through an indicative example.

Suggested Citation

  • Gelegenis, John J., 2009. "Use of a probabilistic model to design energy transmission and distribution networks for low enthalpy geothermal multiple use schemes," Applied Energy, Elsevier, vol. 86(3), pages 284-289, March.
    • Handle: RePEc:eee:appene:v:86:y:2009:i:3:p:284-289
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    References listed on IDEAS

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    1. Haralambopoulos, D.A. & Polatidis, H., 2003. "Renewable energy projects: structuring a multi-criteria group decision-making framework," Renewable Energy, Elsevier, vol. 28(6), pages 961-973.
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    1. Daniilidis, Alexandros & Alpsoy, Betül & Herber, Rien, 2017. "Impact of technical and economic uncertainties on the economic performance of a deep geothermal heat system," Renewable Energy, Elsevier, vol. 114(PB), pages 805-816.
    2. Daniilidis, Alexandros & Scholten, Tjardo & Hooghiem, Joram & De Persis, Claudio & Herber, Rien, 2017. "Geochemical implications of production and storage control by coupling a direct-use geothermal system with heat networks," Applied Energy, Elsevier, vol. 204(C), pages 254-270.

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