The name DMS-TOUGE is an acronym that stands for Decision Making Support Tool for Optimal Usage of Geothermal Energy (shorter DMT – Decision Making Tool). The main objective of this tool is to enable investors to conduct comparative analyses of different energy technologies for geothermal energy utilization. Namely, the tool helps the user to choose the technology with the highest yield for a specific site and consequently provides the information about the possible integration of EGS into the electric and heat systems.
Figure 1: Flowchart of the DMS-TOUGE utilization for assessing the potential geothermal project
DMS-TOUGE is a MATLAB-based tool and standalone open-access application that could be used to estimate different important economic and performance indices for a defined geothermal scenario. The tool has been designed to be flexible, user-friendly, and robust computer tool with a various possible level of simulation detail. Namely, the DMS-TOUGE application is based on separate modules (sub-applications) that are joined via this mutual interface. The sub-applications are modelled to cover different groups of data and are defined as site geological features, geothermal fluid properties, end-user option, geothermal power plant, technology details and costs, financial parameters, incentives, and environmental impact. Moreover, by relying on built-in correlations and default values, a basic simulation can be performed with limited knowledge on the subsurface, surface plant, and financing conditions. For a more detailed level of simulation, the user can provide its own data for various input variables. A user manual is available to help a new user get familiar with the tool.
The tool also provides MCDM (Multiple-criteria decision-making) analysis and facilitates thereby the decision-making process. Among other outputs, which include performance indices such as lifetime electricity and/or heat production, the economic outputs are the system’s levelized cost of energy (sLCOE), net present value (NPV) and internal rate of return (IRR) that are usually used to evaluate the potential energy production-related projects. The available end-use configurations are electricity generation, direct-use heating power production, and combined heat and power production (CHP).
This tool enables assessment of EGS resources within the temperature range of 50-150°C. Moreover, as mentioned four different end-use options are available in DMS-TOUGE:
• Electricity generation – all produced geothermal fluid is used to generate electricity with ORC binary power plant, either with air-cooled or water-cooled condenser.
• Direct-use heat – all produced geothermal fluid is used to provide heating for a given application, e.g. district heating system, industrial processes, greenhouse, agriculture, tourism.
• Combined heat and power (CHP) – where both electricity and heat are produced. Two different configurations are available:
• Series configuration – the geothermal energy is first used to produce electricity and any remaining heat in the geothermal fluid after leaving the power plant is supplied to a direct-heat application.
• Parallel configuration – a power plant is operated in parallel with a direct-use heat application. Namely, part of geothermal brine flow is used for direct-use application and other part for electricity generation. Therefore, this configuration can also be labelled as ‘heat demand preferring production mode’.
A separate module within DMT – multiple-criteria decision-making (MCDM) matrix has a role to process raw data into a decision. MCDM subprocess is performed by using the weighted decision matrix (WDM) and the analytical hierarchy process (AHP). For proper MCDM function, it is necessary to define appropriate criteria that will allow comparison of different EGS options on specific site and comparison of different sites for application of specific EGS option. Relative importance for each criterion can be altered by decision-maker based on preferred aspects of planned investment. There are seventeen influencing factors (sub-criteria) defined in the MCDM analysis and grouped into five categories of criteria as shown in Figure 2.
Figure 2: Defined influencing factors (sub-criteria) grouped into five categories of criteria in the MCDM analysis
By defining a different set of input parameters, the user creates different scenarios of end-application of geothermal energy at the chosen site and geological setting. Furthermore, after gathering all the input parameters and conducting techno-economic analysis, the user is additionally provided with multi-criteria decision-making (MCDM) analysis.