Power Production Estimates from Geothermal Resources by Means of Small-Size Compact Climeon Heat Power Converters: Case Studies from Portugal (Sete Cidades, Azores and Longroiva Spa, Mainland)

António Trota, Pedro Ferreira, Luis Gomes, João Cabral and Peter Kallberg
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António Trota: Faculdade de Ciências e Tecnologia, Universidade dos Açores, Centro de Geociências FCTUC, 9500-801 Ponta Delgada, Portugal
Pedro Ferreira: Departamento de Engenharia Civil e Arquitetura, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
Luis Gomes: Departamento de Engenharia Civil e Arquitetura, Universidade da Beira Interior, GeoBioTec, 6201-001 Covilhã, Portugal
João Cabral: Faculdade de Ciências e Tecnologia, Universidade dos Açores, 9500-801 Ponta Delgada, Portugal
Peter Kallberg: Sylvander Trading Lda, 2765-189 Estoril, Portugal

Energies, 2019, vol. 12, issue 14, 1-16

Abstract: Renewable forms of energy are increasingly penetrating the electricity market, particularly, geothermal energy. A wide range of resource temperatures and fluid quality are converted mostly using traditional binary power plants and, recently, using Climeon modular units. Portuguese natural geothermal resources are far from precise estimations. Despite the parameter uncertainties, electric power resource estimations of two natural geothermal reservoirs are presented: a volcanic sourced heated high-enthalpy geothermal reservoir in Sete Cidades, São Miguel Island, Azores; and a low-enthalpy geothermal reservoir linked to a fractured zone in a granitic setting in Longroiva, in the northern part of the Portuguese mainland. Based on the volumetric method, we assessed the power potential of geothermal resources in Sete Cidades and Longroiva using a probabilistic methodology—Monte Carlo simulation. The average reserve estimations for Climeon module were 5.66 MWe and 0.64 MWe for Sete Cidades and Longroiva, respectively. This figure was by far higher when compared to traditional binary technology; those differences were mostly attributed to distinct conversions efficiency factors.

Keywords: geothermal; energy; binary power plants; Climeon module; Monte Carlo simulation; reserves (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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