Potential of geothermal energy for electricity generation in Indonesia: A review

Nasruddin, Nasruddin; Alhamid, Muhammad Idrus; Daud, Yunus; Surachman, Arief; Sugiyono, Agus; Aditya, H.B.; Mahlia, T.M.I.

doi:10.1016/j.rser.2015.09.032

Cited by 200 publications

(70 citation statements)

References 48 publications

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“…Geothermal energy is defined as the energy stored in the form of heat beneath the surface of solid Earth [4]. Among the different types of geothermal energy: very low, low, high, and very high enthalpy, the present research is focused in low or very-low enthalpy types, also known as shallow types [5]. This energy is characterized by being partially renewable, having high availability, reducing GHG emissions [6], and producing less waste than other energy sources.…”

Section: Introductionmentioning

confidence: 99%

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

González¹,

Rodríguez‐Gonzálvez²

2019

Remote Sensing

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The transition towards a new sustainable energy model-replacing fossil fuels with renewable sources-presents a multidisciplinary challenge. One of the major decarbonization issues is the question of to optimize energy transport networks for renewable energy sources. Within the range of renewable energies, the location and evaluation of geothermal energy is associated with costly processes, such as drilling, which limit its use. Therefore, the present research is aimed at applying different geomatic techniques for the detection of geothermal resources. The workflow is based on free/open access geospatial data. More specifically, remote sensing information (Sentinel-2A and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)), geological information, distribution of gravimetric anomalies, and geographic information systems have been used to detect areas of shallow geothermal potential in the northwest of the province of Orense, Spain. Due to the variety of parameters involved, and the complexity of the classification, a random forest classifier was employed, since this algorithm works well with large sets of data and can be used with categorical and numerical data. The results obtained allowed identifying a susceptible area to be operated on with a geothermal potential of 80 W·m −1 or higher.2 of 20 drilling operations. For this reason, different researchers have tried to develop methodologies to reduce costs in the search for these areas, taking into great consideration the use of remote sensing as a means to prioritize zones of potential geothermal energy [8,9], due to the availability of free satellite imagery and its cost-effective ratio for the geothermal exploration of large areas. One approach that involves remote sensing is the search for areas of rocks altered by hydrological action using images from one or more sensors, since they are indicative of thermal fluids being discharged along faults [10]. Surface thermal properties are an indicator of geothermal resources, which can be measured by the use of images from thermal sensors [11,12]. Additionally, temperatures can also be obtained using multispectral imagery [13] acquiring land surface temperature (LST) values.Among the geomatic techniques, geographic information systems (GIS) offer a whole new dimensionality by combining the remote sensing data with other geographic information sources as in [14], in which gravimetric anomalies, thermal images, and the location of geological faults were employed. Among the available GIS techniques, the use of random forest classifiers stands out, since they allow the ability to extract information from categorical and numerical variables. As a result, they support the decision-taking process without significant computational requirements. These algorithms are popular among the scientific community due to its ease of use and being able to be applied in multiple fields as in the case of [15], in which they were used to obtain a model of the demand of electricity. Another transversal example is the app...

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Section: Introductionmentioning

confidence: 99%

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

González¹,

Rodríguez‐Gonzálvez²

2019

Remote Sensing

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“…A number of new solutions have been proposed to produce heat-generated plants at low temperature and pressure, and has been proven to be applied in various fields such as solar thermal power, biological waste heat, engine exhaust gases, domestic boilers and so forth [3][4][5][6][7][8][9][10][11]. Among the solutions offered, for now the Organic Rankine Cycle (ORC) system is the most widely studied.…”

Section: Introductionmentioning

confidence: 99%

Turbine Design for Low Heat Organic Rankine Cycle Power Generation using Renewable Energy Sources

et al. 2018

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Abstract. In recent years, due to its feasibility and reliability, the organic rankine cycle has become a widespread concern and is the subject of research. In the organic rankine cycle system, the radial turbine component is a highly influential component of the high low performance resulting. This paper discusses the design of radial turbines for organic rankine cycle systems. The design stage consists of preliminary design and detail design with parametric methods on the working fluid R22 to determine the geometry and initial estimation of the performance of the radial turbine. After that, a numerical study of the fluid flow region in the radial turbine with R22 as the working fluid was performed. The analysis was performed using computational fluid dynamics of Autodesk Computational Fluid Dynamics Motion software on two models of real gas, k-epsilon and shear stress transport. From the results of this analysis, there is pressure, velocity and temperature distribution along the radial turbine blades and estimated performance under various operating conditions. Comparison between parametric and computational fluid dynamics analysis results show different performance. The difference is due to the computational fluid dynamics analysis already involving the real gas shear stress transport model.

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“…Meanwhile, it is estimated that 40% of world geothermal energy reserves exist in Indonesia. Compared to the total potential that exists, geothermal energy utilization in Indonesia is still very low, at 1.4 GW or only 4.5% of the existing potential (Nasruddin et al, 2016a). The Organic Rankine Cycle (ORC) is a power plant system that uses 276 Exergy Analysis and Exergoeconomic Optimization of a Binary Cycle System using a Multi Objective Genetic Algorithm organic fluids.…”

Section: Introductionmentioning

confidence: 99%

Exergy Analysis and Exergoeconomic Optimization of a Binary Cycle System using a Multi Objective Genetic Algorithm

Nasruddin

Nasution

Aisyah

et al. 2018

IJTech

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The increasing demand for energy and the current environmental issues are motivating experts to develop appropriate technology to face both problems. The binary cycle system is a highly effective generating technology which can be applied in the utilization of small-scale geothermal energy by using a working fluid that has a lower boiling point than water. In this paper, a geothermal power plant binary cycle system model was tested by using waste brine at a temperature of 180 o C at well pad 4 of the Dieng geothermal power plant. In the optimization procedure, total exergy destruction and total annual cost are chosen as the objective functions. Optimization is made by using a multi objective genetic algorithm. Based on the simulation, it is known that the exergy efficiency and economic value of the optimal binary cycle of the geothermal power plant system has optimum conditions at an evaporation temperature of 163. These results indicate that, by setting the above operating conditions, the system can achieve optimum efficiency, as indicated by the minimum values of both exergy destruction and total annual cost.

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Potential of geothermal energy for electricity generation in Indonesia: A review

Cited by 200 publications

References 48 publications

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

Detection of Geothermal Potential Zones Using Remote Sensing Techniques

Turbine Design for Low Heat Organic Rankine Cycle Power Generation using Renewable Energy Sources

Exergy Analysis and Exergoeconomic Optimization of a Binary Cycle System using a Multi Objective Genetic Algorithm

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