Configuration Analysis of Mainsteam Stop Valve-Governor Valve in a Supercritical Steam Turbine Using Computational Fluid Dynamics to Minimize Throttle LossesJauhar Fahmi1*, S. Silviana1,2, Sulistyo1 *Email corresponding author: jauharfahmi@alumni.undip.ac.id1) Master Program of Energy, School of Postgraduate Studies, Diponegoro University, Jl. Imam Bardjo SH Kampus Pleburan Semarang 502412) Department of Chemical Engineering, Faculty of Engineering, Diponegoro University, Jl. Prof. Sudarto SH Kampus Tembalang Semarang 50275Article history: Received: 20 Juni 2025 | Revised: 7 November 2025 | Accepted: 28 November 2025Abstract. Quantification of losses and prediction of the technical feasibility of a proposed modified system through computational fluid dynamics (CFD) numerical analysis constitute the focus of this study. The system involves a configuration of four sets of Main Steam Stop Valves and Governor Valves (4MSVGV), which are known to operate at low valve openings (<30%) to serve normal load demand. Using CFD modeling, the proposed 2MSVGV configuration demonstrates the ability to serve all load ranges with a general requirement of GV lifting below 82mm. The principles of entropy generation and exergy destruction are employed to quantify throttle losses. 2MSVGV valves configuration, consistently exhibits lower exergy destruction than the 4MSVGV configuration. Further review of the 4MSVGV configuration reveals that the low-opening 4GV contributes in higher exergy destruction compared to the MSV that indicate higher throttle lossess. The total average improvement in exergy destruction rate with the modified 2MSVGV system is about 2.05MW. The validated CFD-based analysis method in this study facilitates predictive evaluation of system behavior, offering a practical means to investigate various operational issues without resorting to expensive and high-risk experimental trials. Keywords – CFD; Throttle Losses; Governor Valves; Entropy; Exergy.INTRODUCTIONImproving the efficiency of energy conversion systems to achieve optimal utilization of energy resources remains a persistent and increasingly significant challenge in response to the growing global energy demand. Although the prevalence of Coal-Fired Power Plants (CFPPs) is projected to decline or face operational limitations in the future, the steam-based energy conversion component, such as steam turbines, is expected to retain a significant role in harnessing various emerging renewable thermal energy sources, including nuclear, geothermal, and solar thermal power. This highlights the continuing strategic relevance of steam turbines in the transition toward more sustainable energy systems.For power plants that are already integrated into the national grid, enhancing the efficiency of large-capacity steam turbines through process optimization within the existing equipment configuration offers a better approach compared to extensive design modifications or component replacements. This method offers cost-effectiveness, operational continuity, and implementation feasibility, while efficiency improvements are primarily achieved through process modifications that minimize energy losses in the power conversion cycle.-19050915035Table 1. Relationship between load, main thermodynamic parameters, and GV openingLoad400 MW500 MW600 MW700 MW800 MW900 MW950 MWGVOpening (%)22.334.627.526.724.626.725.7Mass Flow (Kg/s)346407481569637735774Pressure (Mpa)11.2812.0915.1019.6919.6922.0623.0900Table 1. Relationship between load, main thermodynamic parameters, and GV openingLoad400 MW500 MW600 MW700 MW800 MW900 MW950 MWGVOpening (%)22.334.627.526.724.626.725.7Mass Flow (Kg/s)346407481569637735774Pressure (Mpa)11.2812.0915.1019.6919.6922.0623.09The present study investigates the potential of modifying the control process of the main steam stop valve (MSV) and governor valve (GV) with the aim of minimizing throttling losses. Adjustments in the regulation of steam flow are anticipated to improve the thermal efficiency of the system and thereby contribute to an increase in the generated electrical load. Consequently, the findings of this research are expected to provide a tangible contribution to strategies for improving energy efficiency in steam-based power plants, both within the framework of energy transition and the optimization of existing technologies.The turbine studied utilizes four MSVGV assemblies to direct steam to the high-pressure (HP) turbine. Operational records show that the governor valves (GV) operate at low opening during normal operation, as shown in Table 1 that outlines the steam admission configuration of the investigated turbine, noting the typical operating conditions of its governor valves.The study by Yoo Y, Suh K (2011), on paper with title: Engineering analysis of mass flow rate for turbine system control and design investigated the characteristics and modifications of turbine stop and governor valves through experimental and numerical analysis, demonstrating that a mass flow methodology simplified both programming and experimental procedures for characterizing turbine systems[1]. By that paper result, this study was emerged for typical system with supercritical steam. In operational practice, with a fixed setpoint temperature and sliding pressure arrangement in response to the load setpoint, the magnitude of the mass flow directly determines the amount of energy that can be converted into electricity by the turbine-generator system. In this study, the numerical analysis was validated using actual operational data. Furthermore, numerical analysis was subsequently conducted on a modified MSVGV configuration, and quantify the reduction in losses achieved by both configuration.METHODSThe main challenge in process modification in large system is lies in demonstrating the practical applicability of the proposed system and validating the approach of solution methods employed to ensure that the predicted process outcomes will closely align with actual results. The inherent complexity of valve geometries poses a significant challenge to analytical approaches, thereby making it difficult to acquire data on specific operational parameters at desired spatial locations. On the other hand, numerical solution approach, which allow detailed data extraction at various points thus enabling further in-depth analysis, depend on the accuracy of the input parameters and the solution method to provide more accurate results. Figure 1, depicting the layout of MSVGV configuration to service high pressure (HP) turbine.Figure 1. MSVGV and HP Turbine configurationThis study aims to reduce throttle losses of steam turbine MSVGV by modifying its configuration from 4 assembly to become 2 assembly with the analysis method as depicted in figure 2, with initial step is problem acknowledgment, followed by:Data collection for geometry development, supplemented by daily operational data, and reference books; Geometry modeling using Ansys Fluent software (fluent with fluent meshing) with GV lift (opening) basis for the original 4MSVGV configuration; The results of the numerical analysis process are compared with actual operational data as a model validation stage with standardized software variable input; Variable input is used for configuration analysis of the 2MSVGV assembly with Mass flow rate basis at a certain load to obtain the required valve stem height. Entropy generation and exergy destruction analysis for the 4MSVGV and 2MSVGV system configuration. The new GV lift position for 2MSVGV will provides a reference for the new GV control system input.RESULTS AND DISCUSSIONGoverning EquationContinuity and energy balance equationThe main task of the MSVGV is the control of mass flow quantity using defined parameters to achieve the setpoint dictated by the turbine-generator's speed-load controller. The fundamental equations governing this process are based on the continuity equation (1) and the energy balance equation (2).dM dt = i=1n streammi(1)ddtU+12M∙v2+M∙g∙h=i=1n streammi∙Hi+12∙vi2+g∙hi+Q+W(2)-5080836930Figure 2. Flow chart of analysis methods framework00Figure 2. Flow chart of analysis methods frameworkUnder steady-state, the change of system internal (U) and external (kinetik+potential) energy with time are zero. Given negligible rates of energy at the system outlet due to kinetic and potential energy, and most real-world throttling processes in control valves are assumed to be approximately adiabatic (Q˙​≈ 0) because they happen rapidly and both valves are insulated to prevent significant heat exchange with the surroundings [2], it follows that:0= m1 H1-m2 H2(3)The throttling effect in control valves refers to fluid flow through a reduced geometry under isenthalpic conditions, meaning no heat transfer occurs and no work is performed, also known as an isenthalpic process. The fluid passes through the restriction from side 1 to side 2, experiencing a pressure drop and an increase in volume; however, throughout this flow, the enthalpy remains constant, such that H1=H2 [3].Based on Equation (3), three primary parameters determine the amount of steam energy entering the turbine: steam enthalpy (defined by pressure and temperature) and mass flow rate. Within the distributed control system the responsibility for achieving these parameters is distributed between the turbine master control and the boiler master control (boiler load demand). The boiler master control is tasked with supplying a steam at the target flow, temperature and pressure to MSV inlet. The temperature setpoint is maintained constant at a defined value (565°C for all load targets) through combustion control, heat distribution management, and desuperheater spray control.Entropy generationGovernor valve modulation induces a throttling effect across the valve, as an unavoidable irreversible process. The associated throttling loss can be quantified by the differential pressure measured upstream and downstream of the control valve. A fundamental characteristic of such valves is the inverse relationship between the valve's effective flow area and the resultant pressure drop; a smaller opening area leads to a greater pressure drop and, consequently, increased energy dissipation. Equation (4), derived from the principle of entropy balance where Sgen represents the magnitude of entropy generation, explain this phenomenon [4].dS dt =i=1n streammi Si+allQT +Sgen (4)With steady state and adiabatic conditions (no heat transfer), thenSgen =m∙(S2T2,P2-S1T1,P1)(5)In the context of compressible fluids, variations in valve opening also affect flow velocity, pressure distribution, as well as expansion and throttling phenomena along the valve passage. Conversely, when the valve opening is smaller, the flow area narrows, leading to a reduction in mass flow rate and an increase in pressure losses due to intensified throttling effects. This condition not only decreases the efficiency of energy conversion within the system but may also induce significant local turbulence, particularly under non-partial load (low-load) operating conditions [5].Exergy Analysis-227330634365Table 2. Boundary condition of modelGeometriBoundary TypeValueUnitLoadn/a951720552639855MWInletPressure Inlet (MSV)23.1317.4213.8315.2221.63MPaOutletPressure Outlet (GV)21.2616.0712.4714.2518.92MPaReynold NumberInlet (MSV)195941010531316464277979341687719-Turbulennt IntensityInlet (DH = 0.262m)2.6152.8263.0042.9262.665m0Table 2. Boundary condition of modelGeometriBoundary TypeValueUnitLoadn/a951720552639855MWInletPressure Inlet (MSV)23.1317.4213.8315.2221.63MPaOutletPressure Outlet (GV)21.2616.0712.4714.2518.92MPaReynold NumberInlet (MSV)195941010531316464277979341687719-Turbulennt IntensityInlet (DH = 0.262m)2.6152.8263.0042.9262.665mThe application of exergy balance to a control volume of assembly of MSVGV operating at steady state is corespond to above chapter assumption (W = 0, Q = 0, Kinetick and potential energy are neglected). Exergy balance equation is given in equation (6) considering exergy flow entering (Ex,in), exiting, (Ex,out), and exergy destruction (Ex,dest), within the control volume due to irreversibility.Ex,in-Ex,out-Ex,dest=0(6)The specific exergy [6], the rate of physical exergy flow per unit mass of fluid at a point can be expressed as equation (7), where ho, so, To is the enthalpy, entropi and temperature (in K) of the fluid at dead state.:εx=h-ho-Tos-so+Vi22+ghi(7)As velocity and elevation can be neglected, so the physical exergy per unit mass equation becomes:εx=h-ho-Tos-so(8)The destruction of exergy power as a result of throttling of the steam passing through the MSVGV assembly is calculated by [7]:Edest= εx∙i=1nmi(9)And corespond to equation (2), where W=0, Q=0, thus, the rate of exergy destruction that directly measures the energy that is "lost" or no longer available to do useful work due to the irreversible throttling process, is:Ex.dest=m(εx,1-εx,2) = m[h1-h0-T0s1-s0-h2-h0+T0s2-s0](10)Ex.dest=m[h1-h2-T0s1-s2(11)Combine with equation (2) above:Ex.dest=m[-T0s1-s2](12)Numerical StudyNumerical approach model validation and code verification are important aspects of a CFD method. However, they are not the only ones that have to be considered in order to achieve high-quality CFD results. One is by following guidelines, “To offer roughly those 20% of the most important general rules of advice that cover roughly 80% of the problems, the technical content for the guidelines is limited to single-phase, compressible and incompressible, steady and unsteady, turbulent and laminar flow with and without heat transfer and relevant to many mechanical, aeronautical, automotive, power, environmental, medical and process engineering applications”[8]. Thus, if relative factors were defined between numerical analysis results and experimental results in the early stage of development, it should be possible to produce the characteristic curve and to predict the actual performance of turbine systems wholly by numerical method without additional experiments [9].Figure 3. MSVGV volume control as a steam fluid pathGeometri ModellingThe modeled geometry defines the steam flow path from the MSV inlet header to GV diffuser, upstream of the first turbine nozzle. Key components integrated into this geometry are inlet of Main Stop Valve (MSV), MSV internal section (with strainer), MSV throat, MSV diffuser, Governor Valve (GV) internal section, GV throat, and GV diffuser. 58547069850000Due to the system is considered no heat transfer, the complexities of modeling and calculation setup are reduced. This less-complex system makes the setup of viscosity model and solution method relatively straightforward and efficient from a computational effort standpoint. Figure 3. shows the layout geometry of one of the 4MSVGV assembly sets and the position of the data collection area and the position of the data collection area. Figure 4. Area of data extractionFigure 5. GV lift position as mass flow controllerTurbulence ModelTurbulent flows feature fluctuating velocity that mix momentum and energy, but their small scale and high frequency make direct simulation computationally impractical. The Reynolds-Averaged Navier-Stokes (RANS) equations model all turbulence scales, focusing on mean flow quantities, and can yield steady-state solutions for steady mean flows[10]. The RNG k–ε model takes on a larger of the turbulent viscosity values with a slight gradient than the standard model and, inversely, takes on a smaller amount with a steep gradient. Thus, the RNG k–ε model appears to be more suitable for conducting numerical analysis of bent pipes and complex contours [1]. The RNG k-ε turbulent model was selected for subsequent studies for reasons of computational effort efficiency and accuracy[11] of this work. Table 3 provides detailed settings applied to the analysis after obtaining settings validation. The advantage of using numerical analysis is that it can determine the location of data to be extracted from the model quickly and repeatedly, as shown in Figure 4. Table 3. Numerical analysis configuration setupModel PresetSelection- Energy EquationEnabled- SolverPressure based, absolute formulation, steady state- Near-Wall TreatmentStandard Wall Function (No Slip)- Gradient optionLeast Square Based- Heat transferIsothermal- Viscous Model- Fluidsk-ε (2 equation) RNGIdeal GasAn ideal gas was selected as the working fluid in the software model to maintain consistency between the numerical analysis and subsequent loss calculations, the difference in throttling efficiency between real and ideal gases is less than 1.037% provided that the initial pressure is below 30 MPa [12]. This choice is both efficient and appropriate for simulating flow behavior, offering a balance between accuracy and computational cost. At the other hand, according to Luo and Wang,. This is because the heat exergy generated by throttling contributes only marginally to the total exergy when compared to the exergy at the initial throttling pressure. Therefore, the use of an ideal gas is recommended for calculating throttling efficiency.Boundary conditionThe boundary conditions for this simulation were defined based on software best practices outlined in the user manual, and relevant preceding publications. The MSVGV system was modeled under the assumption of an isentropic throttling process, with no heat transfer. This simplification allowed for the calculation of total steam densities throughout the system using the initial total pressure and temperature, with these values subsequently held constant according to the ideal gas law. The Reynolds Number was determined using Equation (6), and the turbulence intensity for fully-developed flow can be estimated from the following formula derived from an empirical correlation for pipe flows (7) [13]. Table 3. Shows boundary condition setup.Re=inertial forceviscous force(6)I=0.16(ReDh)-1/8(7)left193040Figure 6. Pressure distribution with volume renderingFigure 7. Temperature ContourFigure 8. Velocity stream line (left side)Figure 9. velocity stream line (right side)00Figure 6. Pressure distribution with volume renderingFigure 7. Temperature ContourFigure 8. Velocity stream line (left side)Figure 9. velocity stream line (right side) Validation of the Model and Modification Modelling of 2MSVGV AssemblyBy implementing the framework shown in Figure 2, the steam mass flow (including key parameters such as pressure and temperature) in the validated model can be used to predict the mass flow through the MSVGV control volume. Gathering data from relevant experiments to be compared with the simulation results. Result comparison: Comparing the simulation outcomes with the experimental data to evaluate the accuracy and validity of the model [14]. Actual opening demand data (Table 4, Section C) is directly converted into the GV lift position (in millimeters), providing data in Table 4, Section B. In this context, the actual mass flow rate can be compared with the results of numerical analysis for the 4MSVGV modeling. Figure 5. Show GV lift as variable for controlling mass flow rate to achieve load demand. The results from modeling using CFD show a difference in mass flow rate of around 5%. This discrepancy may arise from several factors, one of which is that the mass flow rate values are derived from mass flow rate balance calculations, commencing from the boiler through to the high-pressure (HP) turbine outlet.-129540734695Table 4. Collection of operational data (C) and Modelling data 4MSVGV (B) vs modified 2MSVGV (A).LoadMass FlowMSV Inlet PressMSV inlet TempMSV Throat PressMSV Throat TempMSV Difsr. PresMSV Difsr.TempGV Throat PressGV ThroatTempGV Outlet PressGV Outlet TempGV Lift <82mmMWKg/sMPaKMPaKMPaKMPaKMPaKmmA. Modified: modelling of 2MSVGV assembly951740.222.72834.722.08834.922.21836.321.39833.221.26832.767.30855700.821.18833.120.58833.420.70834.818.92829.818.40826.145.78720566.817.08833.716.65834.116.75835.515.85831.616.07832.660.00639482.414.93837.614.54837.714.62838.914.15837.114.25837.178.67552455.213.13835.012.72835.212.80836.812.48835.212.49834.970.10B. Modelling of 4MSVGV assembly951713.623.01837.322.88837.222.91837.420.52831.821.26834.317.77855691.221.50835.721.36835.721.39835.918.03827.618.92833.615.73720536.017.35836.417.24836.317.26836.615.56829.216.09833.119.80639465.615.24840.215.15840.015.17840.313.87835.214.28837.821.10552459.213.73838.613.63838.513.65838.811.95831.712.47836.718.78C. Actual 4MSVGV951768.023.07837.8n.an.an.an.an.an.a21.26835.017.77855707.621.59836.3n.an.an.an.an.an.a18.92834.315.73720558.417.36837.4n.an.an.an.an.an.a16.07832.819.80639493.215.22840.8n.an.an.an.an.an.a14.28837.221.10552439.613.74838.5n.an.an.an.an.an.a12.48834.018.7800Table 4. Collection of operational data (C) and Modelling data 4MSVGV (B) vs modified 2MSVGV (A).LoadMass FlowMSV Inlet PressMSV inlet TempMSV Throat PressMSV Throat TempMSV Difsr. PresMSV Difsr.TempGV Throat PressGV ThroatTempGV Outlet PressGV Outlet TempGV Lift <82mmMWKg/sMPaKMPaKMPaKMPaKMPaKmmA. Modified: modelling of 2MSVGV assembly951740.222.72834.722.08834.922.21836.321.39833.221.26832.767.30855700.821.18833.120.58833.420.70834.818.92829.818.40826.145.78720566.817.08833.716.65834.116.75835.515.85831.616.07832.660.00639482.414.93837.614.54837.714.62838.914.15837.114.25837.178.67552455.213.13835.012.72835.212.80836.812.48835.212.49834.970.10B. Modelling of 4MSVGV assembly951713.623.01837.322.88837.222.91837.420.52831.821.26834.317.77855691.221.50835.721.36835.721.39835.918.03827.618.92833.615.73720536.017.35836.417.24836.317.26836.615.56829.216.09833.119.80639465.615.24840.215.15840.015.17840.313.87835.214.28837.821.10552459.213.73838.613.63838.513.65838.811.95831.712.47836.718.78C. Actual 4MSVGV951768.023.07837.8n.an.an.an.an.an.a21.26835.017.77855707.621.59836.3n.an.an.an.an.an.a18.92834.315.73720558.417.36837.4n.an.an.an.an.an.a16.07832.819.80639493.215.22840.8n.an.an.an.an.an.a14.28837.221.10552439.613.74838.5n.an.an.an.an.an.a12.48834.018.78The same method as a study conducted by Yoo Y, Suh K (2011) for trial-and-error method is needed to determine the mass flow rate, given the stem lift in the control valve [1]. The calculation is initiated with an assumed mass flow rate at predicted position, and by trial and error to refine GV lift position to achieve desired mass flow rate. Table 4 section A, Give the final result of mass flow that close to actual data at certain load in certain GV lift positions. Figures 6, 7, 8, 9. show the typical distribution of parameters that the fluid has (855MW case).7565984363606Table 5. Exergy Calculation dataLoadMass Flow RateEntropy Inlet MSVEntropy Diffuser MSVEntropy Outlet GVSpecific EM.s.destMSVSpecific EG.s.destGVSpecific ETotdest TotalEM.t.destMSVEG.t.destGVEdestTotalMWKg/skJ/kg/°C kJ/kg/°C kJ/kg/°C kJ/kgkJ/kgkJ/kgMW MW MW A. Modified: modelling of 2MSVGV 951740.26.2946.3156.3326.3825.01911.4024901.538558756855700.86.3366.3576.4046.38314.05120.4344516.5994314459720566.86.4786.4966.5125.4024.78910.1913016.626745691639482.46.5736.5896.5994.9652.8357.8002448.713983847552455.26.6406.6616.6696.0632.4568.5192665.410803745B. Modelling of 4MSVGV 951728.86.2936.2976.3401.09512.89013.985840.9990010741855691.26.3356.3396.4121.24421.77123.015880.51540516286720536.06.4776.4816.5131.1689.53510.703652.453245977639465.66.5696.5726.6000.9188.3709.288452.941284581552459.26.6256.6306.6751.20513.66314.868529.960066536C. Actual 4MSVGV951768.06.2946.340n.an.an.a13.607n.an.a10450855707.66.3346.415n.an.an.a23.872n.an.a16892720558.46.4806.512n.an.an.a9.716n.an.a5425639493.26.5726.598n.an.an.a7.827n.an.a3860552439.66.6256.667n.an.an.a12.469n.an.a548100Table 5. Exergy Calculation dataLoadMass Flow RateEntropy Inlet MSVEntropy Diffuser MSVEntropy Outlet GVSpecific EM.s.destMSVSpecific EG.s.destGVSpecific ETotdest TotalEM.t.destMSVEG.t.destGVEdestTotalMWKg/skJ/kg/°C kJ/kg/°C kJ/kg/°C kJ/kgkJ/kgkJ/kgMW MW MW A. Modified: modelling of 2MSVGV 951740.26.2946.3156.3326.3825.01911.4024901.538558756855700.86.3366.3576.4046.38314.05120.4344516.5994314459720566.86.4786.4966.5125.4024.78910.1913016.626745691639482.46.5736.5896.5994.9652.8357.8002448.713983847552455.26.6406.6616.6696.0632.4568.5192665.410803745B. Modelling of 4MSVGV 951728.86.2936.2976.3401.09512.89013.985840.9990010741855691.26.3356.3396.4121.24421.77123.015880.51540516286720536.06.4776.4816.5131.1689.53510.703652.453245977639465.66.5696.5726.6000.9188.3709.288452.941284581552459.26.6256.6306.6751.20513.66314.868529.960066536C. Actual 4MSVGV951768.06.2946.340n.an.an.a13.607n.an.a10450855707.66.3346.415n.an.an.a23.872n.an.a16892720558.46.4806.512n.an.an.a9.716n.an.a5425639493.26.5726.598n.an.an.a7.827n.an.a3860552439.66.6256.667n.an.an.a12.469n.an.a5481Analysis of the modified control system, utilizing only 2MSVGV, demonstrates its capability to effectively manage varying load levels (400~1000MW) under normal operation, with the a-criterion GV Lift travelling below 82mm. The increasing overall pressure ratio for 2MSVGV configuration suggests a reduction in throttle losses in the form of drop pressure as the valve opening increases, which can be further quantified through exergy analysis.Entropy Generated and Exergy analysisThe comparison of destruction exergy between control valves in its original configuration (4MSVGV) with modified control characteristic (2MSVGV) will be analyzed to identify the effect of flow restriction level on work potential loss. Using the parameter data obtained at the specified points, an exergy analysis and entropy generation assessment are conducted to determine the contribution of each system component to the occurring losses [15] and to evaluate whether the applied modifications can contribute to reducing those losses. In practical terms, by applying exergy analysis and sustainability indices, refinements in plant design, maintainability procedures, and operational approaches have the ability to improve the overall performance of the plant [16], lowering exergy destruction directly enhances the overall thermodynamic efficiency of the turbine system, meaning that more of the steam’s energy is converted into useful mechanical work rather than dissipated as irrecoverable losses. Figure 10. Profile exergy specific totalFigure 11. Exergy distribution each assemblyThe thermal design of equipment involves two seemingly opposing approaches: enhancing thermal contact to achieve efficient heat transfer or applying insulation to minimize undesirable heat leakage. However, regardless of the specific objective, the core principle of both approaches lies in reducing entropy generation within the thermodynamic system, thereby improving overall efficiency [17]. In practice, the MSVGV body is covered with specialized insulation, and the fluid mass flow passing through the valve is considerably high, such that the heat loss to the environment is relatively small compared to the energy contained in the fluid, rendering negligible heat transfer [18].Figure 10 illustrates that the overlapping 4MSVGV modeling demonstrates the model's ability to closely approximate actual conditions, thus validating its suitability for subsequent exergy analysis of individual components. The modification employing 2MSVGV consistently exhibits lower exergy destruction compared to the 4MSVGV configuration. The most substantial reduction is observed at a load of 855MW, where the modified configuration achieves an exergy destruction saving of 2.572MW.Through exergy destruction analysis applied separately to the MSV and GV, as depicted in Figure 11, the compositional contribution of each component to the total exergy destruction was determined. In the 4MSVGV configuration, with an opening of 21mm, the graph indicates significant throttling occurring at the GV valve, thus dominating the exergy destruction. In this configuration, the average exergy destruction in the MSVs ranges from 0.9 to 1.3MW due to low steam velocity rate at 4MSV, with the remainder of the total exergy destruction resulting from throttling effects at 4GV. Figure 11 also reveals that the average exergy destruction for the MSV valves in the 2MSVGV configuration is between 5.4 and 6.4MW, with the remaining exergy destruction occurring in the GVs. Overall, the average reduction in exergy destruction for the 2MSVGV configuration is 2.050MW.In practical implementation, the proposed 2MSVGV configuration introduces no major trade-offs in safety, operational complexity, or hardware modification, as it merely involves a shift in the valve response characteristic. The valve characteristic adjustment is similar to sequence valves control, allows seamless integration with the existing turbine control logic, preserving all safety interlocks and operational procedures [19]. The modification does not require physical changes to the valve assemblies, ensuring minimal implementation risk. Furthermore, industry practice with the 3-valve governor configuration (3MSVGV) used in routine valve response testing provides supporting evidence that the proposed approach is technically safe and operationally feasible.CONCLUSIONUtilizing the mass flow rate of steam required to pass through the MSVGV at a specific load setpoint as the basis for determining GV lift has proven effective in simplifying the technical feasibility analysis of the new 2MSVGV configuration. Numerical analysis results for the 2MSVGV configuration indicate its capability to serve all normal operational loads ranging from 400 to 1000MW, meeting the criterion of governor valve lifting <80mm. CFD analysis provides the flexibility to obtain steam property data at all points within the MSVGV control volume, allowing for the analysis of the contribution of each MSVGV component to the overall losses. Quantification of throttling losses irreversibilities within the MSVGV through entropy generation and exergy destruction analysis provides a good understanding of the magnitude of these losses. The results from numerical CFD analysis and exergy destruction calculations reveal that the 4MSVGV configuration experiences significant throttle losses in the GV side compared to the MSV side lossess, attributed to the relatively low GV lift opening. The 2MSVGV configuration demonstrates a better distribution of due to a larger GV lift. Across the calculated load range, the 2MSVGV configuration consistently achieves throttle losses reduction with an average in reduced exergy destruction of 2.05MW.The present results also indicate that the inlet pressure setpoint upstream of the valve, which is currently operated under a linear control scheme, has a noticeable influence on the fluctuation of exergy destruction across different load conditions. Future studies should therefore focus on investigating a non-linear inlet pressure control strategy, using the minimum achievable exergy destruction as a key optimization criterion. Such an approach could further enhance overall system performance by minimizing unavoidable irreversibilities and improving the thermodynamic efficiency of the steam admission process.REFERENCES[1]Y. H. Yoo and K. Y. 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Liu, “Study on Valve Management of DEH for Steam Turbine,” Energy Power Eng, vol. 05, no. 04, pp. 319–323, 2013, doi: 10.4236/epe.2013.54b063. Copyright © 2025 Author [s]. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these termsR.E.M. (Rekayasa Energi Manufaktur) Jurnal | Vol.10 No.2/2025ISSN online (2528-3723)http://doi.org/10.21070/rem.v10i2.1762Fahmi, J., Silviana, S. & Sulistyo, Configuration Analysis of Mainsteam Stop Valve-Governor Valve in a Supercritical Steam Turbine Using Computational Fluid Dynamics to Minimize Throttle Losses, R.E.M. 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