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Article

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)

1
Faculdade de Ciências e Tecnologia, Universidade dos Açores, Centro de Geociências FCTUC, 9500-801 Ponta Delgada, Portugal
2
Departamento de Engenharia Civil e Arquitetura, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
3
Departamento de Engenharia Civil e Arquitetura, Universidade da Beira Interior, GeoBioTec, 6201-001 Covilhã, Portugal
4
Faculdade de Ciências e Tecnologia, Universidade dos Açores, 9500-801 Ponta Delgada, Portugal
5
Sylvander Trading Lda, 2765-189 Estoril, Portugal
*
Author to whom correspondence should be addressed.
Energies 2019, 12(14), 2838; https://doi.org/10.3390/en12142838
Submission received: 23 May 2019 / Revised: 15 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
(This article belongs to the Special Issue Innovation in Geothermal Energy Exploration and Production)

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.

Graphical Abstract

1. Introduction

Global warming is compelling Earth’s civilizations to move to renewable forms of energy. The use of renewable energy sources promotes local economies through the use of national and local natural resources and protects countries from unstable and unpredictable fluctuations in world energy markets, such as fossil fuels. Moreover, remote zones without access to energy grid systems can be supplied by local renewable energy, such as geothermal energy [1].
Among the renewable energy portfolio, geothermal energy holds a significant resource potential at Earth surface, available to harnesses in housing and industry by converting into electricity or by direct use. Geothermal energy uses heat from the Earth to deliver power. It is a clean, renewable, and stable resource used all over the world directly or by transforming thermal energy into electricity [1,2,3,4]. Moreover, cascade use of geothermal energy or hybrid plant systems using other renewable energies can considerably augment the use of this energy source.
Commercial competitive transformation of geothermal heat (i.e., water or steam) into electricity requires a design with good efficiency. Geothermal traditional binary power plants require a geothermal fluid operational minimum inlet temperature higher than 90 °C (with some special exceptions, such as the Chena Hot Springs geothermal power plant in Alaska, with an inlet temperature of 73.9 °C and an outlet of 10.0 °C). Lower inlet fluid temperatures of traditional binary power plants imply low to very low energy conversion efficiency, turning these power plants without commercial feasibility [5]. However, recently, new modular and easy to install small-size compact Climeon heat power converters (SCHPCs) have come on the market, mostly resulting in increased conversion efficiency [6,7]. With medium/low enthalpy inlet water or gas temperature in the range 70 °C to 120 °C, the technology enables excellent efficiency in the range of 10–14% under good conditions, with high inlet temperature and flow combined with a cooling source providing low temperature and good flow. Reasonable efficiency in the range of 5–10% can be obtained even at less favorable conditions, depending mostly on inlet temperature and flow and cooling source temperature and flow. The Climeon technology can be useful in a wide range of use cases, from the early stages to the very end of a geothermal reservoir’s exploitation, independent of the size and nature (natural or engineered) of the reservoir.
For large geothermal projects, before the adequate characterization of a reservoir’s extractable reserves (enthalpy, fluid quality, and available mass flow), when beginning geothermal exploration, well tests, and designing and fabricating the power plant, the Climeon modules can be quickly installed and powered into the market, thus allowing the owner to potentially generate a profit while waiting on other factors. In addition, modules can be added over time as required.
Knowing that most geothermal reservoirs are exploited using a heat mining approach, most of them experience reductions in temperature and pressure (mostly associated with general heat reserve depletion), and power generator modules can solve part of the problem by increasing heat extraction from a reservoir in a wide range of temperatures, particularly in the lower range.
The new Climeon modular power energy systems can also be used in reservoirs where temperatures are in the range 70 °C to 120 °C, the known temperature range (mostly inferred from chemical geothermometers) for most mainland Portuguese natural hydrothermal (geothermal) reservoirs. Moreover, synergies can be obtained by using the hydrothermal fluid in a cascade approach along with the use of rejected heat transferred to the cooling source.
The Climeon modular units can also be used on running power plants, namely, traditional binary power plants, by using hydrothermal fluids before being reinjected into the reservoir. Those fluids, for Azores binary power plants, are reinjected in the temperate range 87 °C to 95 °C, thus, the range of the Climeon units [8,9]. Before system implementation, the chemistry analysis and scaling potential of the pipeline system and reinjection well pipes must be performed, and the availability of the Climeon units’ cooling fluids (water) is also important.
In this study, we present an evaluation of the geothermal power potential in two sites in Portugal (Figure 1), with different geological and geodynamic settings, based on a volume estimation methodology using a Monte Carlo approach. The reservoir parameter estimations were based on published papers along with the authors’ data and interpretation of the results. We compared both Climeon modules and the traditional binary plants’ electric power potentials at the two sites (i.e., Sete Cidades and Longroiva) using different adequate efficiency energy conversion factors.
The investigated sites are located in Sete Cidades in São Miguel Island, Azores archipelago and in Longroiva Spa, in the northern part of mainland Portugal. Sete Cidades is an active large stratovolcano on São Miguel Island, which lies on the boundary between the Eurasia and Nubia tectonic plates [10]. The Longroiva zone, a well-known thermal and spa area in the northern part of Portugal, is traversed by an active large and deep fault zone which crosses the granitic craton, which gives rise to thermal hot springs. The Sete Cidades hydrothermal reservoir, heated by a volcanic source, probably corresponds to a liquid dominated system with temperatures up to 250 °C. The Longroiva Spa reservoir, heated by a natural earth geothermal gradient and the radiogenic heat of local granitic rocks, can attain reservoir temperatures up to 120 °C [11,12].

2. Power Production by Climeon Technology

The Small-Size Compact Climeon Heat Power Converter (SCHPC) converts low temperature geothermal fluids into electric power by exchanging heat from hot water or steam (Table 1). Compared to traditional systems, such as traditional binary power plants (TBPPs), the SCHPC is based on the Rankine cycle, but the condensation side is under vacuum, and no heat recuperation downstream of the turbine is required. The SCHPC runs at low pressure levels, is smaller, more efficient and resilient to weather conditions and can be coupled to a wide range of heat sources [6,7]. The working fluid is of a chemical nature, similar to alcohol, ketone, and even water, has no ozone depletion potential and a global warming potential close to zero [7]. Modules can be fabricated in a wide power range (150 kW to 50 MW) according to source size and flow rate fluctuations, without significantly reducing the efficiency.
Climeon heat power modules have been implemented on a commercial basis in several countries worldwide, mainly in the following three segments, in which strong future growth is expected: geothermal (Wendel in the USA; Baseload Power and Iwana Power GK in Japan; Varmaorka in Iceland), industrial (SSAB steel mill in Sweden), and maritime (Viking Line, in Sweden; Virgin Voyages/Fincantieri shipyard in Italy).

3. Case Studies

3.1. Power Potential Evaluation Methodology

Assessment of extractable heat reserves in geothermal reservoirs has been conducted using several approaches, such as the volumetric method and numerical models [14,15,16]. The volumetric method is by far the most used approach for the assessment of the power potential of geothermal resources, particularly for reservoirs without sound exploration and exploitation data. In order to evaluate the uncertainties of input parameters in the volumetric method, a probabilistic methodology is mandatory, as in the case of Monte Carlo simulation, which includes random numbers and probability by evaluating interactively a deterministic model.
The volumetric methodology estimates the extractable electrical energy of a geothermal reservoir by evaluating the reservoir heat content over a certain reservoir volume, assuming a heat percentage that can be recovered from reservoir to surface and by considering a power machine efficiency on the conversion of heat to electricity.
According to Sarmiento and Steingrímsson [15], the heat content in a reservoir can be estimated by:
H = A × h × ( H r + H w )
where,
  • H = Stored heat (kJ).
  • A = Resource area (m2).
  • h = Reservoir thickness (m).
  • The r and w subscripts symbolize rock and water (fluid).
The heat rock content is obtained by:
H r = ( T i T f ) × ( 1 ϕ ) × C r × ρ r
where,
  • Ti = Average reservoir temperature (°C).
  • Tf = Base (rejected or abandoned) temperature (°C).
  • C = Specific heat capacity (kJ/kg °C).
  • ρ = Density (kg/m3).
  • ϕ = Porosity.
The heat contained in the fluid (assumed liquid water at reservoir pressure) is given by:
H w = ( T i T f ) × ϕ × C w × ρ w
The calculation of the electric power plant capacity is then obtained using:
P = H × R f × η / ( F × L )
where,
  • P = Power plant capacity (kW).
  • Rf = Recovery factor.
  • η = Conversion efficiency.
  • F = Plant capacity factor.
  • L = Plant life (s).

3.2. Sete Cidades Site

The Sete Cidades volcano, located at the westernmost point of São Miguel Island (Azores), lies at the boundary of the Eurasia and Nubia tectonic plates [10,17], close to the Azores Triple Junction: place where the North American, Eurasia, and Nubia tectonic plates meet. The volcano–tectonic setting where the Sete Cidades volcano is located is rather complex. Interpretation of geological, tectonic, and seismic data include inverse, normal, and strike-slip fault mechanisms, thus showing a wide range of stress/strain regimes in the area. Mosteiros graben and caldera wall collapse are two of the most impressive morphological features throughout the region (Figure 2).
São Miguel Island was built by the accretion of diverse volcanic products over the last 0.88 Myr [18] or 4 Myr [19], with a general westward growing trend, from several polygenetic and monogenetic eruptive centers, ranging from low to moderate Hawaiian to Strombolian eruptive styles to highly explosive and dangerous Plinian events [10].
Sete Cidades is the most active stratovolcano in São Miguel Island [20] and has an approximately 6 km diameter circular summit caldera and a maximum elevation at Pico das Éguas (874 m). Several preserved volcanic edifices and landforms can be observed inside (pumice cones, maars, and domes) and outside (cinder and scoria cones; domes) caldera.
The geological deposits on the Sete Cidades volcano reveal intense volcanic activity, thus a repeated input of volcanic heat. Moore and Rubin [21] estimated that 400 years was the average quiescent interval over the past 3000 years, whereas Queiroz data [22], based on the records of 17 intra-caldera eruptions over the last 4600 BP calculated an overall average recurrence time interval of about 144 y, without considering outside volcanic activity. Beier et al. [23] reached the conclusion that the caldera eruptions were triggered by a mixture of deep relatively fast up-flow of basaltic hot magma into upper sited trachytic magma chambers.
Tectonic events on Sete Cidades are a complex superposition of slow and stable movements between the Nubia and Eurasia plates (approximately 4 mm/y in the NE direction) and climactic episodes of volcanic activity. According to Queiroz [22], the actual caldera, with an initial sub-aerial phase around 200,000 BP, was the result of three main collapse phases—36,000 BP; 29,000 BP; and 16,000 BP—the last one involving the north and northeast walls. Around 5000 BP, the activity inside the caldera altered from magmatic to mainly hydro-magmatic, with geological records of 17 eruptions [22]. Regardless of no land eruptions after settlement on the Sete Cidades volcano, offshore, a few eruptions were witnessed, the most remarkable being the Sabrina eruption, which occurred in 1811 (Figure 2) [24].
Recent volcanic eruptions in Sete Cidades along with seismic swarms, including small and major magnitude events, most of them concentrated over the Graben of Sete Cidades, evidence ongoing deformation, most of them by new fault formation and fault reactivation, and hot magma residence [10].
Heat flux transfer of magma to surrounding meteoric water and seawater could occur by small-size magma injections, as dike type or by huge magma chambers shallow sited on polygenetic volcanic systems as Sete Cidades. Machado [25] and later on Beier et al. [23] showed evidence of a probable magma chamber, around 3 km in depth. The cooling process of magma transfers energy to the cold downflowing percolating water, giving rise to a water temperature increase. Rock fracturation and rock alteration over time (the Sete Cidades volcano is almost 200,000 years old) have produced a well-developed geothermal natural reservoir. Sometimes, most of the natural hydrothermal features of those reservoirs (such as hot springs, fumaroles, and degassing) are hidden by the rock suite of volcanic piles and by the buffering systems of huge shallow-sited fresh water aquifers, perched (aquifers located at an altitude controlled mostly by impermeable layers), and basal (shell-like layer aquifers closed to sea-level salt water island interface), making it impossible for the reservoir fluid to reach high zones of the volcano surface. However, there are a few zones where gas emissions, as CO2 [22], were detected and some hot springs which discharge on sea cliffs, on Mosteiros and Ferraria [26,27,28].
Surface features such as hot springs, evidence of probable deep-sited geothermal reservoirs, can be observed in two coastal areas with similar geological settings: Ferraria and Mosteiros (Figure 2). Both zones correspond to a basaltic s.l. delta lava flow (locally called Fajã). The hot springs emerge on or nearby the coastline.
In Ferraria, the hot spring water emerges with a temperature of around 60 °C; the pH ranges from 5.4 to 6.2. The Ferraria water, classified as sodium chloride, is a mixture of an up-flowing hydrothermal CO2-enriched acid fluid with seawater [27]. The Ferraria water is intensely enriched with Sr and Mn but shows low concentrations in Al, Fe, and As [27]. Recent development and improvement of th Thermal Spa in Ferraria [27] included three shallow exploration geothermal wells, up to approximately 33 m depth. The temperature and chemistry of the water wells are similar to the existing hot springs.
In the Mosteiros area (Figure 2), two hot springs can be found, Mosteiros (43.0 °C) and São Lázaro (32.8 °C), with a similar chemical composition and geological settings as the Ferraria hot springs [26,27].
Menezes et al. [29] performed a broadband magnetotelluric reconnaissance survey across Sete Cidades Caldera and detected a high conductive layer with depths ranging from approximately 600 m deep to 2500 m, indicating the existence of a hydrothermal reservoir, just above the magma chamber inferred by Beier et al. [23].
Based on the study by Menezes et al. [29] on local tectonics and on the hydrothermal surface features, we delineated two possible geothermal reservoirs associated to the Sete Cidades active volcano, separated by the Mosteiros Graben. Zone I corresponds to the Mosteiros Geothermal Reservoir (MGR), whereas Zone II corresponds to the Ferraria Geothermal Reservoir (FGR) (Figure 2). At depth, both MGR and FGR could be partially linked. The Mosteiros hot springs and Ferraria hot springs, marginally placed, are probably surface expressions of those reservoirs.
In Figure 3, we present a conceptual model for the Sete Cidades geothermal reservoirs. The heat source is related to the repeated magma injection over the area, inside caldera (record of 17 eruptions in the last 5000 years) and outside (last eruption on Sabrina, year 1811; see Figure 2). The water inflow could have two origins: meteoric water from island high lands and inside caldera; seawater from the Atlantic Ocean. The preferential water inflow could occur along the Mosteiros Graben, a fractured zone probably extended to the southeast, mostly under distension stress behavior. The 3 km top magma chamber will heat the cold inflow water, after which the water is driven by the density difference and ascends to the surface. The long-term alteration of rocks by volcanic gases (mostly CO2 and H2S) and high temperature will contribute to the rock alteration and leaching processes, thus increasing the porosity, permeability, and an impermeable cap. An exploitable natural geothermal reservoir comprises a significant rock volume size, with appropriate void index, containing extractable fluid at medium to high temperature, and a cap rock to hold the heat.
Reservoir area. The estimations of the reservoir areas (including the minimum and maximum) are shown Figure 2 and Table 2. The maximum areas were coarsely interpreted from the 10 ohm-m anomaly, whereas the minimum areas were close to the 5 ohm-m [29]. To complete the model, we also used the hot springs’ locations and tectonics.
Reservoir thickness. The maximum and minimum thickness of the reservoirs (Table 2) were estimated following Meneses et al. [29].
Reservoir fluid and rejection temperature. According to Carvalho et al. [27], we cannot apply a hot spring chemical geothermometer to calculate the reservoir temperature. Taking into consideration the similitudes of the Fogo volcano to the Sete Cidades volcano [23], we used the temperature range (220 °C to 250 °C) of the Ribeira Grande Geothermal Reservoir for the Sete Cidades reservoirs (Table 2), FGR and MGR [22,30]. Fluid density and fluid specific heat were kept constant (Table 2); the rejection (or base) temperature was linked to the minimum temperature for self-producing wells (120 °C).
Rock density and rock specific heat. Sete Cidades rocks show a wide range of lithology, such as fallout deposits, lava flows, and pyroclastic. Therefore, we considered a range of 2000 to 3000 kg/m3 (Table 2).
Recovery factor. Recovery factor (Table 2) depends on reservoir parameters, such as temperature, porosity, permeability, and the success of drilling targets in determining the best transmissivities, i.e., maximizing well productivity [31].
Conversion efficiency. Efficiency of the conversion of heat to electricity depends on several parameters, such as fluid enthalpy, quality, temperature, type of power plant, base temperature, and wellhead pressure. Assuming a cooling fixed-source temperature of 20 °C, and a minimum inlet temperature of 120 °C, we considered a conversion efficiency of 11.5% for the rejection temperature [6]. In order to compare power figures of the Climeon module with binary power plants, we used the temperature formula of Moon and Zarrouk [5] for the efficiency conversion based on inlet temperature. Thus, the efficiency values data input for calculations were 6.3%, 3.6%, and 8.2%, respectively, for the maximum, most likely, and minimum (see the values in brackets in Table 2).
Plant life and load factor. Module or power plant life could extend over decades, depending on several parameters, such as fluid chemistry, climate, maintenance, and power plant characteristics. Here, we considered 30 years for plant life. Load factors on geothermal power plants were high (Table 2).
Figure 4 shows, for both the Climeon module and traditional binary plants, the power potential of a plant in MWe (for a lifetime assumed at 30 years) plotted against a relative frequency histogram. The cumulative frequency distribution can be considered a probability density function.
Sanyal and Sarmiento [32] used the cumulative probability of estimated reserve to classify resources as:
(a)
Proven − P90 or 90% probability: the minimum value.
(b)
Proven + Probable − mode (most likely) or median (P50 or 50%).
(c)
Proven + Probable + Possible − P10 or 10% probability: the maximum value.
Table 3 provides the results of the Monte Carlo simulation for the Sete Cidades site. The estimated power potential for the Climeon module was almost twice that compared to the binary plant. The proven reserves of Sete Cidades could produce for 30 years with 38 Climeon modules of 150 kWe each, thus producing a total accumulated amount of 14.20 × 108 kWhr.

3.3. Longroiva Spa Site

The Longroiva Spa is located in the Longroiva village, Municipality of Meda, District of Guarda (mainland Portugal). The geological setting includes the Ancient Massif, which corresponds to the western part of the morphostructural unit of the Iberian Peninsula, called the Hercynian basement, with evident episodes of extensive magmatic intrusions [33]. The region is part of a transition zone among plateaus, which are staggered at various altitudes, and steep slopes. That transition zone is materialized by a major tectonic accident, the Vilariça Fault (Bragança–Vilariça–Manteigas), which divides the region into two large blocks.
The Vilariça intraplate fault, originated by Iberia–Eurasia plate collision, which has been active since the late Cenozoic, plays as an NNE–SSW strike-slip deformation structure [34,35,36,37,38]. This fault zone is considered the most active fault in the Portuguese mainland territory [39,40,41], being a vertical fault, deep (up to about 20 km) and long (about 600 km), and continuing to the south of Manteigas towards Ponte de Sor [42,43]. The Vilariça Fault accumulates about 5.5 km of horizontal displacement and gave rise to a set of parallel fractures in a wide band of 0.5 to 1 km and subsiding structures, such as the Longroiva Graben (Figure 5). The fracture system shows asymmetric morphology on both sides of Vilariça Fault. The eastern bloc side exhibits a fault scarp of about 150 to 200 m height; the actual surface corresponds to a plateau tilted towards the northwest and to the river Douro, located north of Longroiva Spa. On the western side, tectonic forces have elevated the land to an altitude of 650 to 750 m where Meda town is located.
Along the Vilariça Fault and associated fracture systems, several hot springs occur. According to Ferreira Gomes [46], the Longroiva sulfurous hot spring, approximately 30.8 °C [47], emerges along the Longroiva Spa Fault, a fault parallel to the Vilariça Fault. Based on geological, geophysical, and drilling data, Ferreira Gomes [46] proposed a conceptual hydrothermal model that considers the existence of a probable deep geothermal reservoir between the Longroiva Spa Fault and the Vilariça Fault (Figure 6), i.e., the Longroiva Graben. The recharge water, of meteoric origin, infiltrates at maximum altitudes of 800 m (Trancoso region, on Figure 5), percolates deep into the granitic craton, and gradually incorporates the heat of the Earth’s geothermal gradient along with the radiogenic heat content of granitic rocks.
With Longroiva Spa exploration and exploitation projects, several studies were undertaken through shallow drilling. Two wells drilled (TD1, 45 m depth, sealed; AC1, 211.7 m depth, under production) in the Longroiva hot spring area improved the knowledge of the local shallow hot fluid circuit, giving evidence of two different aquifers: (a) an unconfined aquifer, with fresh, low mineralized water, reservoir thickness of approximately 50 m, with local recharge; (b) a confined aquifer of sulfurous water, with deep flow and probably distant recharge.
Well AC1 exhibited artesianism (well head pressure of approximately 1.2 barg) and produces a stable water flow of 6.3 L/s at a temperature of 47.4 °C [12]. Well tests permitted the calculation of the aquifer’s parameters: permeability, 0.4 m/day; transmissivity, 5.6 m2/day; and storage coefficient, 2.4 × 10−3. Well water analysis [48] revealed the chemical stability of an alkaline sulfurous sodium-bicarbonate water type (pH circa 8.8), with a total mineralization of 460 mg/L.
Recent research by Coelho Ferreira [49] anticipated a deep well in the surroundings of Longroiva SPA (1500–2000 m depth), estimating flow rates in the order of 15 to 20 L/s with temperatures up to 80 °C.
Reservoir area. Based on the fault geometry, local geomorphology and geology, and hydrothermal surface features, we designed a maximum probable rectangular area (23.0 km by 1.6 km) for the Longroiva Geothermal Reservoir (Figure 5) of approximately 37 km2.
Reservoir thickness. Without exploration studies in the area, particularly geophysical, there are no comprehensive data regarding the deep reservoir thickness. We assumed a prudent average reservoir thickness of 400 m.
Reservoir fluid temperature. Based on the chemical water composition, Coelho Ferreira et al. [11] and Ferreira Gomes et al. [12], using silica and Na/k geothermometers, estimated reservoir temperatures in the range 113 °C to 120 °C. Taking into consideration geothermal well gradient data [11,12] and heat flow models, Coelho Ferreira et al. [17] estimated the depth of the Longroiva Geothermal Reservoir to be from 1134 m to 2000 m.
Density, porosity, and rock specific heat. The reservoir rock is probably made of granitic type. We used the range values of Robertson [50] and Jumikis [51] for rock density (2530 to 2620 kg/m3), rock porosity (0.01 to 0.04), and rock specific heat (1.0 kJ/kg °C).
Recovery factor. Statistically, there are no sound historical records of the heat recovery factor for natural hydrothermal reservoirs under granitic geological settings in Portugal. Thus, for the Longroiva site, we used a prudent scenario of 5% for the recovery factor (Table 4).
Conversion efficiency. As for the Sete Cidades site, in the Longroiva case we used different conversion efficiency values for the Climeon module and binary power plants. For the input temperature range of 70 °C to 120 °C, we used Climeon module conversion efficiencies of 9.6 (1.5), 7.7 (0), and 11.5 (3.0), respectively, for the maximum, most likely, and minimum; the values in brackets denote the conversion efficiency for traditional binary power plants (Table 4).
Module life and load factor. For the Longroiva site, we considered the same model inputs (plant life and load factor) as for Sete Cidades.
Figure 7 shows, for both the Climeon module and binary plant for the Longroiva Geothermal Reservoir, the potential of the plant in MWe plotted against the relative frequency histogram.
Table 5 shows the results of the Monte Carlo simulation for the Longroiva site. The estimated power potential for the Climeon module was five times higher compared to the binary plant. The proven reserves of the Longroiva Geothermal Reservoir could stand for 30 years with four Climeon modules of 150 kWe each, thus producing a total accumulated amount of 1.50 × 108 kWhr.

4. Discussion

Surface features and exploration studies at the Sete Cidades volcano gives the indication of an important heat resource, probably a hidden deep source natural geothermal reservoir. There is no doubt about the large magma heat flux in the area, evidenced by the presence of several islands (inside and outside the Sete Cidades caldera) and surtseyan eruptions close to the coastline (such as the Sabrina eruption), from at least 200,000 years ago.
Taking into consideration a similar geological setting, namely, eruption and magma source style, the Sete Cidades geothermal reservoir (or reservoirs) might show similarities with the Ribeira Grande Geothermal Reservoir, associated with the Fogo volcano [10]. Thus, the reservoir, with temperatures up to 250 °C (here considered as liquid), could be attained by drilling from 1000 to 2500 m deep. The reserve estimations of 5.66 MWe (Climeon module) may be larger taking into consideration that the reservoir size could be greater and by the fact that we are not considering renewable heat (from the volcano and from well fluid reinjection). Also, depending on the cooling source (sea water, fresh water or cooling tower) and the altitude (for traditional BPP and mostly for CM), the conversion efficiency could augment significantly (we assumed a cooling source of 20 °C). Moreover, recovery factors can be optimized by conducting sound and extensive exploration studies, aimed to discover good drilling targets for the production phase.
The estimated reserve differences between the Climeon module and traditional binary plants are mostly related to conversion efficiency differences—efficiency decrease with input temperature decrease—mostly for traditional binary plants. Depending on the reservoir and well characteristics, a minimum wellhead temperature of 120 °C cannot be sustained if it is self-flowing; in this case, downhole pumps must be implemented.
Evaluation of the reserves for geothermal resources on the Portuguese mainland was mostly based on natural hot springs. However, there may be large hidden natural resources, with reservoir temperatures from 100 °C to 120 °C, which can be attained by drilling on the order of 1.5 to 3.0 km. Except for oil and gas exploration in the sedimentary basins, there has been no complete exploration studies (such as geophysical and deep drilling) to investigate deep-seated geothermal reservoirs. Despite the uncertainties (reservoir thickness) and speculative (recovery factor) approach of some of the input parameters in the calculations, the estimated values can give an order of magnitude of the resources and provide guidance to some of the actual conversion energies systems. Clearly, due to the minimum temperature resource, for the Longroiva site, the Climeon module was by far the most effective machine for the heat recovery (at least five times better than traditional BPPs). Water for the cooling source can be obtained from several sources, such as a shallow fresh aquifer, rainfall, rivers, and brackish and wasted water. Available water for cooling devices is in fact an issue in regions where rainfall is scarce, which is the case for the Longroiva site, nor for Sete Cidades site. The need for cooling water for the Climeon module (and also for binary power plants) depends on several factors, such as cooling water temperature, differential temperature of geothermal source (input and output), and on the size of the Climeon power unit (i.e., number of modules). Cascade use of geothermal resources (swimming pools, greenhouses, and aquaculture) and integration with air conditioning devices (individual dwellings or district heating systems) could transform an issue into a benefit. The heat recovering from the cooling source by means of a heat pump makes possible to reuse the cooling water and therefore reducing significantly the need for external cooling water. Moreover, if necessary, part of the cooling energy can be obtained by air-cooling devices, despite the global energy efficiency reduction. In Portugal, industrial use of water from rivers and aquifers requires previous national/regional authorizations.
For both cases (i.e., Sete Cidades and Longroiva), the Climeon modular unit of 150 kW is crucial for project development, and it must be taken into consideration that the Climeon technology can be easily implemented and adapted to the project phase and resource size, reducing risk.
Every single geothermal project demands an adequate and stepwise development strategy, namely exploration studies, such as geophysical research. Determining the best drilling targets is a crucial issue in geothermal projects, i.e., the recovery factor. Only good well producers can transport heat from the reservoir to the surface, thus raising the recovery factor.
Several hot springs occur across mainland Portugal, such as São Pedro do Sul and Chaves [52], evidencing several exploitable geothermal reservoirs. However, all of them lack a comprehensive reservoir evaluation for desirable exploitation and management, including environmental issues.

5. Conclusions

Portuguese natural geothermal resources are far from having a precise assessment. Despite the parameter uncertainties, we made electric power resource estimations for two natural geothermal reservoirs: a volcanic source high-enthalpy geothermal reservoir in Sete Cidades, São Miguel, 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 made the assessment of the power potential of geothermal resources in Sete Cidades and Longroiva using a probabilistic methodology, the Monte Carlo simulation.
For a wide range of input resource temperatures, two conversion technologies can be applied: Climeon and traditional binary technologies. For both cases, the estimated power potential was optimized using Climeon technology. For the high-enthalpy reservoir in Sete Cidades, the estimated reserves using the Climeon module could attain 5.66 MWe, more than twice that of traditional binary technology. For the Longroiva case, the estimation of the reserves was 0.64 MWe, mostly due to the low temperature resource and conversion efficiency factor between Climeon and traditional binary technologies; the difference was greater, attaining ten times more expected electricity, in favor of Climeon technology.
Natural reservoir volume and temperature cannot be changed, only discovered [31]. In order to reduce project risk, a stepwise development phase, namely, exploration studies such as geophysical research, are crucial for success. Defining the best drilling targets will increase the recovery factor. Thus, reducing the parameter range distribution of permeability, porosity, and temperature will improve the reservoir model, possibly producing better reservoir exploitation and management.

Author Contributions

Conceptualization, A.T., L.G. and P.F.; methodology, A.T.; software, A.T. and J.C.; validation, A.T., J.C. and L.G.; formal analysis, A.T. and J.C.; investigation, A.T., P.F., L.G.; resources, A.T., L.G. and P.K.; data curation, A.T. and J.C.; A.T., L.G. and P.F.; writing—review and editing, A.T., P.F., L.G.; P.K.; visualization, A.T. and J.C.; supervision, A.T.

Funding

This research was funded by Portuguese Foundation for Science and Technology, project reference UID/MAT/04674/2019.

Acknowledgments

We acknowledge technical support given by Carla Leal on map and figure artwork.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. EGEC (European Geothermal Energy Council). EGEC Geothermal Market Report 2017. 2018. Available online: https://www.egec.org/media-publications/egec-geothermal-market-report-2017/ (accessed on 1 October 2018).
  2. Dickson, M.H.; Fanelli, M. (Eds.) Geothermal Energy: Utilization and Technology; UNESCO Renewable Energy Series: Paris, France, 2003; 205p. [Google Scholar]
  3. Gupta, H.K.; Roy, S. Geothermal Energy an Alternative Resource for the 21st Century; Elsevier: Boston, MA, USA, 2006. [Google Scholar]
  4. DiPippo, R. Geothermal Power Plants: Principles, Applications, Case Studies and Environmental Impact, 3rd ed.; Elsevier: Oxford, UK, 2012. [Google Scholar]
  5. Zarrouk, S.J.; Moon, H. Efficiency of geothermal power plants: A worldwide review. Geothermics 2014, 51, 142–153. [Google Scholar] [CrossRef]
  6. Climeon. Climeon Heat Power Systems. 2019. Available online: https://climeon.com/wp-content/uploads/2017/04/Climeon-Tech-Product-Sheet.pdf (accessed on 15 April 2019).
  7. Havsed, R. A Modular and Vacuum Based ORC for Low Temperature Geothermal Power; GRC Transactions: Reno, NV, USA, 2018; Volume 42, ISBN 978-1-5108-7585-2. [Google Scholar]
  8. Kaplan, U. Organic Rankine Cycle Configurations. In Proceedings of the European Geothermal Congress, Unterhaching, Germany, 30 May–1 June 2007. [Google Scholar]
  9. Franco, A.; Vieira, N.V.; Ponte, C.P. Geothermal Developments in Pico Alto, Terceira Island, Portugal. In GRC Transactions; GRC Geothermal Library: Davis, CA, USA, 2017; Volume 41. [Google Scholar]
  10. Trota, A. Crustal Deformation Studies in S. Miguel and Terceira Islands (Azores). Volcanic Unrest Evaluation in Fogo/Congro Area (S. Miguel). Ph.D. Thesis, University of Açores, Açores, Portugal, 2009. [Google Scholar]
  11. Coelho Ferreira, P.J.; Ferreira Gomes, L.M.; Oliveira, A.S.C.; Carvalho, P.E.M. Contribution to the Knowledge of the Geothermal Potential of the Municipality of Meda (Portugal). In Proceedings of the World Geothermal Congress, Melbourne, Australia, 19–24 April 2015. [Google Scholar]
  12. Ferreira Gomes, L.M.; Ferreira Guedes, J.; Gomes da Costa, T.C.; Coelho Ferreira, P.J.; Neves Trota, A.P. Geothermal potential of Portuguese granitic rock masses: Lessons learned from deep boreholes. Environ. Earth Sci. 2015, 73, 2963–2979. [Google Scholar] [CrossRef]
  13. DGT. Direção-Geral do Território. Carta Administrativa Oficial de Portugal (CAOP), Shapefile; DGT: Lisboa, Portugal, 2017. [Google Scholar]
  14. Franz, P.; Neville-Lamb, M.; Azwar, L.; Quinao, J. Calculation of Geothermal Stored Heat from a Numerical Model for Reserve Estimation. In Proceedings of the World Geothermal Congress, Melbourne, Australia, 19–25 April 2015. [Google Scholar]
  15. Sarmiento, Z.F.; Steingrimsson, B. Computer programme for resource assessment and risk evaluation using Monte Carlo simulation. In Short Course on Geothermal Project Management and Development in Uganda; UNU-GTP: San Salvador, El Salvador; LaGeo: San Salvador, El Salvador, 2008; pp. 1–11. [Google Scholar]
  16. Williams Colin, F. Evaluating the Volume Method in the Assessment of Identified Geothermal Resources; Geothermal Resources Council Transactions: Portland, OR, USA, 2014; Volume 38, ISBN 9781634394673. [Google Scholar]
  17. Global Country Boundaries (Arcgis by Esri). Global Country Boundaries from DIVA-GIS. Shapefile from [email protected]_ucsb. Available online: https://www.arcgis.com/ home/item.html?id=2ca75003ef9d477fb22db19832c9554f (accessed on 8 May 2019).
  18. Johnson, C.L.; Wijbrans, J.R.; Constable, C.G.; Gee, J.; Staudigel, H.; Tauxe, L.; Forjaz, V.; Salgueiro, M. 40Ar/39Ar ages and paleomagnetism of São Miguel lavas, Azores. Earth Planet. Sci. Lett. 1998, 160, 637–649. [Google Scholar] [CrossRef]
  19. Abdel-Monem, A.; Fernandez, L.A.; Boone, G.M. K-Ar ages from the eastern Azores Group (Santa Maria, São Miguel and the Formigas Islands). Lithos 1975, 8, 247–254. [Google Scholar] [CrossRef]
  20. Queiroz, G.; Gaspar, J.L. Stratigraphy of Sete Cidades Volcano (S. Miguel Island, Azores). In 1a Assembleia Luso-Espanhola de Geodesia e Geofísica, Sessão S09; Vulcanologia Física: Almeria, Espanha, 1998. [Google Scholar]
  21. Moore, R.B.; Rubin, M. Radiocarbon dates for lava flows and pyroclastic deposits on São Miguel, Azores. Radiocarbon 1991, 33, 151–164. [Google Scholar] [CrossRef]
  22. Queiroz, G. Vulcão das Sete Cidades (S. Miguel, Açores): História Eruptiva e Avaliação do Hazard. Tese de Doutoramento no ramo de Geologia, Especialidade de Vulcanologia, Departamento de Geociências. Ph.D. Thesis, Universidade dos Açores, Ponta Delgada, Portugal, 1997. [Google Scholar]
  23. Beier, C.; Haase, K.M.; Hansteen, T.H. Magma Evolution of the Sete Cidades volcano, São Miguel, Azores. J. Pet. 2006, 47, 1375–1411. [Google Scholar] [CrossRef]
  24. Insulana, A. Ilha Sabrina e a Erupção Submarina em S. Miguel de 1811. Insulana 1951, 7, 260–265. [Google Scholar]
  25. Machado, F. Acid Volcanoes of San Miguel, Azores. Bull. Volcanol. 1972, 36, 319–327. [Google Scholar] [CrossRef]
  26. Freire, P. Águas minerais da Ilha de S. Miguel (Açores): Caracterização Hidrogeológica e Implicações para a Monitorização Vulcanológica. Master’s Thesis, Universidade dos Açores, Ponta Delgada, Açores, Portugal, 2006. [Google Scholar]
  27. Carvalho, M.R.; Mateus, A.; Nunes, J.C.; Carvalho, J.M. Chemistry of the Ferraria thermal water, S. Miguel Island, Azores: Mixing and precipitation processes. Environ. Earth Sci. 2011, 64, 539–547. [Google Scholar] [CrossRef]
  28. Ferreira, T.; Gaspar, J.L.; Viveiros, F.; Marcos, M.; Faria, C.; Sousa, F. Monitoring of fumarole discharge and CO2 soil degassing in the Azores: Contribution to volcanic surveillance and public health risk assessment. Ann. Geophys. 2005, 48, 787–796. [Google Scholar] [CrossRef]
  29. Menezes, P.T.L.; Travassos, J.M.; Marçal, A.J.A.; Monteiro Santos, F.A. 3D magnetotelluric exploration of Sete Cidades Volcano, São Miguel Island, Azores. Interpretation 2017, 5, 219–230. [Google Scholar] [CrossRef]
  30. Rangel, G. Temperature Model and Tracer Test Analysis for the Ribeira Grande Geothermal System, São Miguel Island, Azores; Reports; UNU GPT: Reykjavik, Iceland, 2014; 28p. [Google Scholar]
  31. Trota, A.P.N.; Rodrigues, F.C.; Meneses, J.G.A. Insights for the Angra do Heroísmo hydrothermal reservoir conceptual model. Sustain. Water Resour. Manag. 2019, 5, 135–146. [Google Scholar] [CrossRef]
  32. Sanyal, S.K.; Sarmiento, Z. Booking geothermal energy reserves. Grc Trans. 2005, 29, 467–474. [Google Scholar]
  33. Ribeiro, A.; Antunes, M.T.; Ferreira, M.P.; Rocha, R.B.; Soares, A.F.; Zbyszewski, G.; Moitinho de Almeida, F.; Carvalho, D.; Monteiro, J.H. Introduction à la Géologie Générale du Portugal; Serviços Geológicos de Portugal: Lisboa, Portugal, 1979; 114p. [Google Scholar]
  34. Cabral, J. Neotectónica de Portugal continental. Mem. Inst. Geol. Min. 1995, 31, 265. [Google Scholar]
  35. Cunha, P.; Pereira, D.I. Cenozoic Evolution of the Longroiva—Vilariça Area (NE Portugal); Ciências da Terra (UNL): Lisboa, Portugal, 2000; pp. 91–100. [Google Scholar]
  36. Vegas, R.; Vicente, G.; Muñoz Martín, A.; Palomino, R. Los corredores de fallas de Régua-Verín y Vilariça: Zonas de transferencia de la deformación intraplaca en la península ibérica. Geotemas 2004, 6, 245–249. [Google Scholar]
  37. Heredia, N.; Rodríguez-Fernánde, L.R.; Vegas, R.; Vicente, G.; Cloetimgh, S.; Giner, J.; González-Casado, J.M. Cadenas cenozoicas del Noroeste peninsular. In Geología de España; Vera, J.A., Ed.; SGE-IGME: Madrid, Spain, 2004; pp. 619–621. [Google Scholar]
  38. Vicente, G.; Cloetingh, S.; Van Wees, J.D.; Cunha, P.P. Tectonic classification of Cenozoic Iberian foreland basins. Tectonophysics 2011, 502, 38–61. [Google Scholar] [CrossRef]
  39. Cabral, J.; Ribeiro, A. Carta Neotectónica de Portugal Continental, Escala 1:1.000.000; Departamento Geologia Faculdade Ciências Lisboa, Serviços Geológicos: Lisboa, Portugal, 1988. [Google Scholar]
  40. Cabral, J.; Ribeiro, A. Carta Neotectónica de Portugal Continental, Escala 1:1.000.000; Nota Explicativa; Serviços Geológicos: Lisboa, Portugal, 1989; p. 10. [Google Scholar]
  41. Rockwell, T.; Fonseca, J.; Madden, C.; Dawson, T.; Owen, L.A.; Vilanova, S.; Figueiredo, P. Paleoseismology of the Vilariça segment of the Manteigas-Bragança Fault in Northeastern Portugal. In Palaeoseismology: Historical and Prehistorical Records of Earthquake Ground Effects for Seismic Hazard Assessment; Reicherter, K., Michetti, A.M., Silva, P.G., Eds.; Geological Society: London, UK, 2009; pp. 237–258. [Google Scholar]
  42. Cunha, P.P. Estratigrafia e Sedimentologia dos Depósitos do Cretácico Superior e Terciário de Portugal Central, a Leste de Coimbra. Ph.D. Thesis, University of Coimbra, Coimbra, Portugal, 1992. [Google Scholar]
  43. Sequeira, A.J.D.; Cunha, P.P.; Sousa, M.B. A reactivação de falhas, no intenso contexto compressivo desde meados do Tortoniano, na região de Espinhal-Coja-Caramulo (Portugal Central). Comunicações Instituto Geológico Mineiro 1997, 83, 95–126. [Google Scholar]
  44. SGP. Carta Geológica de Portugal, Escala 1/500000; Serviços Geológicos de Portugal: Lisboa, Portugal, 1992. [Google Scholar]
  45. LNEG. Carta Geológica de Portugal à Escala 1:500000. 5a Edição da Carta Geológica de Portugal à Escala 1:500000 Publicada Pelos Serviços Geológicos de Portugal em 1992. Unidade de Geologia, Hidrogeologia e Geologia Costeira. Laboratório Nacional de Energia e Geologia, I.P. Lisboa, Portugal. 2019. Available online: http://geoportal.lneg.pt/arcgis/services/CGP500k/MapServer/WMSServer?request=GetCapabilities &service=WMS (accessed on 25 May 2019).
  46. Ferreira Gomes, L.M. Modelos Geohidráulicos de Águas Minerais e de Nascente—Casos de Estudo da Região Centro. In Águas Minerais Naturais e de Nascente da Região Centro; José, S.C., Ed.; Mare Liberum: Aveiro, Portugal, 2012; pp. 185–206. [Google Scholar]
  47. Silva, J.J.R.F.; Almeida, J.D. Relatório de Análise. In Água das Caldas de Longroiva (Nascente Sulfúrea); Relatório; Universidade da Beira Interior: Covilhã, Portugal, 1970; 10p. [Google Scholar]
  48. Coelho Ferreira, P.J.; Ferreira Gomes, L.M.; Carvalho, P.E.M.; Oliveira, A.S. Water quality in deep and confined aquifer systems of granite rocks—The case of sulphurous water from Longroiva, Portugal. In Proceedings of the International Conference on Civil Engineering (Towards a Better Environment)—CE13, Covilhã, Portugal, 26–29 May 2013. [Google Scholar]
  49. Coelho Ferreira, P.J. Modelação de Sistemas Geohidráulicos Profundos Associados a Fraturas Extensas da Região da Meda. Ph.D. Thesis, University da Beira Interior, Covilhã, Portugal, 2019. in press. [Google Scholar]
  50. Robertson, E.C. Thermal Properties of Rocks; United States Department of the Interior Geological Survey, United Open-File Report 88-441; U.S. Geological Survey: Reston, VA, USA, 1988; 106p. [CrossRef]
  51. Jumikis, A.R. Rock Mechanics, 2nd ed.; Trans Tech Publications: Houston, TX, USA, 1983; 613p. [Google Scholar]
  52. DGEG. Geotermia—Energia Renovável em Portugal. In Brochura da DGEG, Direção Geral de Energia e Geologia, 1st ed.; DGEG: Lisboa, Portugal, 2017; 54p. [Google Scholar]
Figure 1. Location of the two investigated sites. Sete Cidades, Azores, Portugal, active volcanic zone; Longroiva Spa, Portugal, granitic craton associated to a regional active fault. Adapted from Portuguese Directorate-General of the Territory (DGT) maps database http://www.dgterritorio.pt/. Reproduced with permission from [13]. Portuguese Directorate-General of the Territory, 2019.
Figure 1. Location of the two investigated sites. Sete Cidades, Azores, Portugal, active volcanic zone; Longroiva Spa, Portugal, granitic craton associated to a regional active fault. Adapted from Portuguese Directorate-General of the Territory (DGT) maps database http://www.dgterritorio.pt/. Reproduced with permission from [13]. Portuguese Directorate-General of the Territory, 2019.
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Figure 2. Sete Cidades volcano: geology, tectonics, and hydrothermal features. Zone I: Mosteiros Geothermal Reservoir; Zone II: Ferraria Geothermal Reservoir. Minimum and maximum areas are illustrated (see Table 2).
Figure 2. Sete Cidades volcano: geology, tectonics, and hydrothermal features. Zone I: Mosteiros Geothermal Reservoir; Zone II: Ferraria Geothermal Reservoir. Minimum and maximum areas are illustrated (see Table 2).
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Figure 3. This sketch outlines the hydrothermal reservoir model of Sete Cidades based mostly on the interpretation (see A and B in Figure 2’s illustration) of published geological, geochemical, and geophysical data. Reproduced with permission from [22,23,27,29]. Society of Exploration Geophysicists and American Association of Petroleum Geologists, 2017.
Figure 3. This sketch outlines the hydrothermal reservoir model of Sete Cidades based mostly on the interpretation (see A and B in Figure 2’s illustration) of published geological, geochemical, and geophysical data. Reproduced with permission from [22,23,27,29]. Society of Exploration Geophysicists and American Association of Petroleum Geologists, 2017.
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Figure 4. Histogram graph for the power capacity of the Sete Cidades case according to data from Table 2 and based on the Monte Carlo simulation. (A) Climeon module; (B) traditional binary power plants (x-axis in MWe).
Figure 4. Histogram graph for the power capacity of the Sete Cidades case according to data from Table 2 and based on the Monte Carlo simulation. (A) Climeon module; (B) traditional binary power plants (x-axis in MWe).
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Figure 5. Longroiva geothermal area: geology, tectonics, and hydrothermal features. Adapted from SGP and LNEG. Reproduced with permission from [44,45], Geological Services of Portugal. Geological Services of Portugal, 1992.
Figure 5. Longroiva geothermal area: geology, tectonics, and hydrothermal features. Adapted from SGP and LNEG. Reproduced with permission from [44,45], Geological Services of Portugal. Geological Services of Portugal, 1992.
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Figure 6. Conceptual model of the hydrothermal reservoir of the Longroiva Spa site based mostly on the interpretation of published geological and geochemical data (from Ferreira Gomes). Reproduced with permission from [48]. National Library Board Singapore, 2018.
Figure 6. Conceptual model of the hydrothermal reservoir of the Longroiva Spa site based mostly on the interpretation of published geological and geochemical data (from Ferreira Gomes). Reproduced with permission from [48]. National Library Board Singapore, 2018.
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Figure 7. The histogram shows the power capacity of the Longroiva Hydrothermal Reservoir according to the data in Table 1. (A) Climeon module; (B) binary power plants (x-axis in MWe).
Figure 7. The histogram shows the power capacity of the Longroiva Hydrothermal Reservoir according to the data in Table 1. (A) Climeon module; (B) binary power plants (x-axis in MWe).
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Table 1. Basic technical characteristics of small-size compact Climeon heat power converters [6,7].
Table 1. Basic technical characteristics of small-size compact Climeon heat power converters [6,7].
CharacteristicsOne Module 150 kWePower Block 1 MWe (7 Modules)
Module
Height (mm)22702270
Depth (mm)21052105
Width (mm)208514,700
Total weight (kg)900063,000
Electrical Cabinet
Height (mm)21002100
Depth (mm)600600
Width (mm)220013,600
Total weight (kg)12006100
Heating Circuit
Module flange connection ISODN125/PN10DN125/PN10
Flow rate liter/second10–5070–350
Inlet temperature maximum °C120120
Cooling Circuit
Module flange connection ISODN125/PN6DN125/PN6
Flow rate liter/second10–5070–350
Minimum cooling inlet temperature °C00
Maximum cooling inlet temperature °C3535
Electrical Specification
Maximum net output power kW1501050
Voltage selectable V400/690400/690
Frequency selectable Hz50/6050/60
Table 2. Input parameters for the Monte Carlo simulation for the Sete Cidades site (ad = adimensional). The values for binary power plant efficiency are in brackets. Reproduced with permission from [5]. Praise Worthy Prize, 2015.
Table 2. Input parameters for the Monte Carlo simulation for the Sete Cidades site (ad = adimensional). The values for binary power plant efficiency are in brackets. Reproduced with permission from [5]. Praise Worthy Prize, 2015.
ItemsUnitsMost LikelyMinMaxProbability Distribution
Area (two zones, I and II)km2532678triangular
Thicknessm10005001500triangular
Rock densitykg/m3250020003000triangular
Porosityad0.150.10.2triangular
Recovery factorad0.0350.010.06triangular
Rock specific heatkJ/kg °C1 constant
Temperature°C230220250triangular
Fluid densitykg/m3827.1 constant
Conversion efficiencyad11.5 (6.3)(3.6)(8.2)constant/(triangular)
Fluid specific heat (constant pressure)kJ/kg °C4.9 constant
Plant lifeyears30 constant
Load factorad0.95 constant
Rejection temperature°C120 constant
Table 3. Results of the Monte Carlo simulation for Sete Cidades, both the Climeon module and binary power plant.
Table 3. Results of the Monte Carlo simulation for Sete Cidades, both the Climeon module and binary power plant.
UnitProven Reserves (P90) MWeProven + Probable (P50) MWeProven + Probable + Possible (P10) MWe
Climeon module5.667.039.26
Binary power plant2.043.566.02
Table 4. Monte Carlo simulation for the Longroiva Spa site (ad = adimensional).
Table 4. Monte Carlo simulation for the Longroiva Spa site (ad = adimensional).
ItemsUnitsMost LikelyMinMaxProbability Distribution
Areakm2373060triangular
Thicknessm400250500triangular
Rock densitykg/m3260025302620triangular
Porosityad0.020.010.04triangular
Recovery factorad0.05 constant
Rock specific heatkJ/kg °C1 constant
Temperature°C110100120triangular
Fluid densitykg/m3951 constant
Conversion efficiencyad9.6 (1.5)7.7 (0)11.5 (3.0)triangular
Fluid specific heat (constant pressure)kJ/kg °C4.2 constant
Plant lifeyears30 constant
Load factorad0.95 constant
Rejection temperature°C70 constant
Table 5. Results of the Monte Carlo simulation for Longroiva for both the Climeon module and binary power plant.
Table 5. Results of the Monte Carlo simulation for Longroiva for both the Climeon module and binary power plant.
UnitProven Reserves (P90) MWeProven + Probable (P50) MWeProven + Probable + Possible (P10) MWe
Climeon module0.640.871.24
Binary power plant0.060.130.24

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Trota, A.; Ferreira, P.; Gomes, L.; Cabral, J.; Kallberg, P. 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). Energies 2019, 12, 2838. https://doi.org/10.3390/en12142838

AMA Style

Trota A, Ferreira P, Gomes L, Cabral J, Kallberg P. 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). Energies. 2019; 12(14):2838. https://doi.org/10.3390/en12142838

Chicago/Turabian Style

Trota, António, Pedro Ferreira, Luis Gomes, João Cabral, and Peter Kallberg. 2019. "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)" Energies 12, no. 14: 2838. https://doi.org/10.3390/en12142838

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