Evaluation of Energy Consumption for Mineral Processing of Tungsten Ore in Mongolia: Khovd Aimag and Erdene-Soum as Case Studies
1
Research Institute for Earth Resources, Kangwon National University, Chuncheon-si 24341, Republic of Korea
2
Department of Integrated Energy and Infra System, Kangwon National University, Chuncheon-si 24341, Republic of Korea
3
Department of Energy and Resources Engineering, Kangwon National University, Chuncheon-si 24341, Republic of Korea
*
Author to whom correspondence should be addressed.
Minerals 2025, 15(6), 660; https://doi.org/10.3390/min15060660
Submission received: 18 May 2025
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Revised: 17 June 2025
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Accepted: 18 June 2025
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Published: 19 June 2025
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
Abstract
:The tungsten deposits in Mongolia have the potential to be exploited as an alternative source to alleviate the risk due to the monopolization in the global production of such a critical metal. However, it is challenging to develop an efficient mineral processing method that can complement the supply based on the currently available energy resources in Mongolia. Therefore, the present study investigated the range of energy required for the beneficiation of tungsten ores, including theoretical assumptions and practical evaluation for two processes in Mongolia. The range of energy consumption was 0.12 to 2.21 kWh/t for crushing and 0.29 to 4.62 kWh/t for grinding regarding the range of Kick’s constant 0.2–0.6 kWh/t and Bond work index 7–17 kWh/t, respectively. The most dominant impact factor in the comminution was the product size. The evaluation of 18 different comminution–flotation circuits indicated a range of required energy from 362 kWh to 8298 kWh. The maximum values of energy consumption for mineral processing of Erdene-soum and Khovd Aimag tungsten ore were 6280 and 6355 kWh. An estimation regarding the energy demand (6355 kWh) and supply energy for the process of Khovd Aimag ore was conducted to propose a suitable system of renewable energy resources using the power pinch analysis method.
1. Introduction
Tungsten (W) is one of the most important metals used in a wide range of industrial applications because of its unique physical and chemical properties such as a high melting point, high density, high tensile strength, and high thermal and electrical conductivity [1,2,3,4]. Most of tungsten global production (54%–72%) is used for manufacturing hard metal (cemented carbides) [1], which is an essential component in cutting tools, mining, construction, and oil and gas drilling industries [1,2,3]. The rapid growth of the global population and economy has led to a dramatic increase in the demand for tungsten and its related minerals for applications in modern life, technological innovations, and industrial fields, driving the continuous exploitation of tungsten primary resources. The steady increase in tungsten production has caused the progressive exhaustion of its minerals in the last few decades due to the limitations of tungsten reserves [1]. Therefore, tungsten has been listed as a strategic and critical metal by many countries (the European Union and the United States) and organizations [1,2,3,4]. Moreover, ~56% of the main tungsten reserves are located in China, and global tungsten production is heavily dependent on China, accounting for about 82% of the world’s supply (Figure 1) [5,6]. This monopolization poses substantial risks to global supply chains, prompting the exploration of alternative sources outside China. Mongolia has emerged as a promising candidate with potential tungsten reserves and production, and it was the world’s fourth largest producer of tungsten in 2020 (Figure 1) [6].
The typical grade of tungsten in the original minerals is critically low (0.1%–1.5%); hence, it is necessary to produce the concentrate with a higher grade of 65%–75% for the requirements of international trading [1]. Scheelite (CaWO4) and wolframite ((Fe, Mn)WO4) are two main tungsten minerals with sufficient economic value for commercial exploration [7,8]. Generally, the concentration of scheelite and wolframite involves the comminution (crushing and grinding) and separation stages (flotation, gravity, or magnetic separation) [1]. These minerals can be liberated at fine particles based on their brittleness; hence, it requires a size reduction stage using crushing and milling tools. The size reduction of tungsten ores should be operated carefully with classifying tools to prevent the generation of fines [1,7]. The further separation for scheelite normally includes gravity concentration and froth flotation because of its amenability, while gravity or magnetic method is applied for wolframite due to its paramagnetic property [1,7]. It is important to design the comminution and separation stages with suitable modeling of equipment and circuits, such as chemicals (collectors or pH), operating parameters (pulp density, temperature, and feed rate), equipment (type and design), and circuits (number of stage and configuration) [9]. However, the investigation of the energy consumption of the concentration process is also necessary because it is the most energy-intensive process in mining, accounting for 44% of the total power [10]. The large amount of energy consumption required for tungsten ore concentration is a significant challenge for Mongolia due to the remoteness of mine locations and the instability of conventional energy resources. If the power supply is only dependent on fossil fuels, it can lead to high emissions of greenhouse gases, climate change, and related harmful impacts on the environment and human health. The integration of renewable energy sources into mining operations presents a viable solution to alleviate these environmental impacts and enhance energy security in remote and off-grid areas with available resources [11]. The adoption of renewable energy has become a potential transition in global mining, and there has been an increase in the installment of microgrid or hybrid systems at different scales for rural mining sites [11,12,13]. A hybrid power generation system providing an affordable energy supply for the concentration of tungsten ore presents a suitable option for mining operations in remote sites in Mongolia. However, the balance between the demand for energy consumption and the supply system should be investigated to determine the components and scales of renewable energy resources. The specific energy required for the concentration process can be calculated using the theoretical approach based on the operational variables (feed size, product size, and Bond index) and apparatus (crusher, mills, or separation tools) [14]. Energy consumption for several mineral processes has been estimated, for instance, 157.5 MW/t-Cu for copper ore, 18 kWh/t-ore for gold ore, and ~889 kWh/t-Fe for iron ore [15,16,17]. In our previous study, the maximum energy consumption per hour for the concentration of tungsten ore in Mongolia was estimated to be 2–3 MW with the assumption of a variation of 7–17 kWh/t in the Bond work index and the feed size of 100 to 200 mm [14]. Consequently, a hybrid system comprising two or three renewable energy resources can be affordable for the estimated range of energy consumption. Although these estimations can depict the energy consumption and the required energy systems, the practical concentration process of tungsten ore in Mongolia should be further evaluated.
Therefore, the present study not only hypothetically estimated a range of energy consumption for tungsten ore treatment based on ore characteristics, processing parameters, and equipment but also applied the evaluation for two concentration processes for tungsten ore in Mongolia as case studies. Firstly, theoretical models were used to predict the range of required energy for the comminution and separation processes of tungsten ore by Kick’s equation, Bond’s equation, and the multiple linear regression (MLR) model. The energy amount was evaluated for several comminution–separation circuits with different apparatuses to describe the variation in the energy consumption. The calculations were further applied for two concentration processes of two Mongolian tungsten ores, Khovd Aimag and Erdene-soum. Finally, the power pinch analysis sizing method was used to estimate the electric supply system that was affordable for the demand of energy consumption in these concentration processes.
2. Materials and Methods
2.1. Materials
The calculation of energy consumption was conducted for two cases of Erdene-soum and Khovd Aimag tungsten ore. Erdene-soum ore is from Tud Aimag, near the center of Mongolia, while Khovd Aimag ore is located in the western region of Mongolia. The major chemical compositions and final grade of WO3 after the concentration of these ores are listed in Table 1 [18,19].
2.2. Calculation of Energy Consumption
In this study, the energy consumption of the comminution for crushers (jaw and cone crusher) and mills (rod and ball mill) was evaluated using Kick’s equation and Bond’s equation (Equations (1) and (2)), respectively [20,21].
where W is the specific energy consumption (kWh/t), Kk is the Kick’s constant (kWh/t), and P and F are the product and feed size (mm).
where W is the specific energy consumption (kWh/t), Wi is the Bond work index (kWh/t), and P and F are 80% of the product and feed passing size (P80 and F80, μm).
W = Kk × ln(F/P),
W = 10 × Wi (1/√P − 1/√F),
The energy consumption of the flotation cell was calculated by transferring the power of the motor (kW) to the energy (kWh) [22]. The power P (kW) of the flotation cell was estimated by finding the torque of the impeller M (Nm) and the rotation speed of the stirrer n (rpm) using Equation (3), and power was converted to energy using Equation (4).
where η is the efficiency of the motor, and T is the running time (η is assumed to be 0.85 and T is assumed to be 1 h).
P = 2πMn/60,
kWh = (kW × T)/η,
The influence of the ore properties (Bond work index and Kick’s constant) and operating parameters (feed size and product size) on energy consumption was evaluated using an MLR model with a 33 factorial design, which describes more than one regression between independent variables (predictors) and one dependent variable (response) (Equation (5)) [23,24,25].
where Y is the dependent variable (energy consumption); x1, x2,…, xk are the independent variables (Bond work index, Kick’s constant, feed size, and product size); β0 is the intercept of the regression; β1, β2,…, βk are the regression coefficients; and ε is the error term.
Y = β0 + β1x1 + β2x2 + … + βkxk + ε,
2.3. The Power Pinch Analysis (PoPA) Method
Power pinch analysis (PoPA) is an effective method to evaluate the generated amount from hybrid power systems (HPSs) containing more than one renewable generator, which is necessary to evaluate the affordable feasibility of the supply with the demand of energy [26]. The capacity of the renewable generators was selected based on the range of each type: wind, 1.5–9.2 MW; solar, 0.2–10.6 MW; and biomass, 2–1000 MW (listed in Table 2) [12,27,28].
If the generated energy exceeds the required amount, it can be stored in the battery and calculated using Equation (6) [24]. However, the hourly self-discharge rate and the amount of discharge are significantly small. Therefore, the cumulative storage capacity can be estimated by multiplying the sum of unused energy by charging efficiency (0.9).
where Bt: battery capacity (MWh); Bt−1: battery capacity at previous time interval (MWh); Ct: charging quantity (MWh); Dt: discharging quantity (MWh); σ: hourly self-discharge rate (0.00004/h); t: time (h); T: time interval (h); ηc: charging efficiency (0.9); and ηd: discharging efficiency (0.9).
Bt = Bt−1(1 – σ × T) + (Ct × ηc) + Dt/ηd
3. Results and Discussion
3.1. Tungsten Ore in Mongolia
Tungsten deposits are generally classified into three types including hydrothermal, skarn, and stratiform, and the most important type of deposit is hydrothermal, accounting for 60% of global tungsten reverses [29]. Tungsten deposits mainly occur in hydrothermal forms in Mongolia including (i) tin–tungsten greisen, stockworks, and quartz veins; (ii) tungsten–molybdenum–beryllium greisen, stockworks, and quartz veins; (iii) cassiterite–sulfide–silicate veins and stockworks; and (iv) cassiterite (tungsten) placer deposits [30]. Tin–tungsten deposits are mostly located in the west and central regions of Mongolia but in small amounts, while tungsten–molybdenum–beryllium deposits are found in northern and northeastern Mongolia (Figure 2) [31]. It can be seen that Mongolia has great potential for tungsten production with such a variety of mineral deposits; however, it requires more research and investment to complete a database of mineral deposits and occurrences in Mongolia as well as to provide solutions to increase the economic value of the original resources and the efficiency of the domestic mining process.
3.2. Estimation of the Range of Energy Consumption for the Concentration Processing of Tungsten Ore
3.2.1. Comminution Stage
The specific energy consumption (SEC) is a function of Kick’s constant, the Bond work index, the feed size, and the product size following Kick’s and Bond’s equations; hence, the regression between the SEC and the operating parameters was predicted using statistical analysis with Minitab 19.0 software [23,24,25]. A 33 factorial design of the parameter value was used to calculate the SEC based on Kick’s equation for crushing and Bond’s equation for grinding (Table 3), and the effect of each parameter was estimated based on the significance at the 95% confidence interval with Student’s t-distribution. The results showed that the range of energy consumption in the comminution stage was 0.12 to 2.21 kWh/t for crushing and 0.29 to 4.62 kWh/t for grinding. The small p-value of the model (<0.05) and the high value of R2 (87% for crushing and 88% for grinding) indicated that the regression model was adequate to explain the effect of the investigated parameters on energy consumption (Table 4). All the investigated parameters had significant influences on the required energy for the comminution (p-value < 0.05), and the feed size had the least distribution in the impact on the energy consumption. The contour plot of energy consumption versus the investigated parameters describes the comprehensive effects of the combination of these factors (Figure 3). In crushing, more energy was required for the processes with a product size of less than 10 mm and a Kick’s constant of more than 0.45 kWh/t (Figure 3a,b). For grinding, the most intensive energy consumption (>4.0 kWh/t) was observed when reducing the feed size of >30 mm to the product size of <1.5 mm with a Bond work of >14 kWh/t (Figure 3c,d). The crushers and mills can be used individually or combined depending on the properties of the ores and the desired product size.
3.2.2. Separation Stage
Generally, the separation of tungsten ore after the comminution stage can be operated using the flotation or shaking table depending on the product size, the nature of the ores, and the grade of tungsten. For example, the gravity method is commonly used for wolframite with larger mineralization, while flotation is more suitable for scheelite because of the finer particle size and low grade [1]. Gravity or flotation separation can be combined with magnetic separation to generate the final concentrate with a sufficient grade of tungsten. In the present study, the SEC of flotation, shaking table, and magnetic separation were estimated based on the power of the equipment’s motor (listed in Table 5) and converted to an energy consumption value by multiplying them by the corresponding capacity [32,33,34,35,36,37].
3.2.3. Range of Energy Consumption for the Comminution–Separation Circuit
The theoretical calculation of the energy consumption for the comminution and separation circuits of tungsten ore is summarized by each equipment with the corresponding operating parameters, power, and capacity, including the minimal and maximum values (Table 5). Based on the results, 18 different processes were proposed for tungsten ore concentration in the investigated range of the Kick’s constant, Bond work index, feed size, and product size. The possible combinations include (i) one crusher and one mill; (ii) two crushers and one mill; (iii) one crusher and two mills, and (iv) two crushers and two mills followed by flotation or shaking table, and finally magnetic separation (Table 6). Although the concentration process can vary due to the complex properties of tungsten ore, the circumstances, and the affordable equipment of the mines in Mongolia, the results provide a variety of options for feasible processes with the prediction of the required amount of energy consumption. This is an advantage for further design of an efficient concentration process and customization of suitable equipment to match the information provided by mineralogical analysis in Mongolia. The amount of energy consumption per hour from the simplest to the fullest process (Processes 8 and 17) ranged from 362 kWh to 8298 kWh. However, the common observation for all of these processes is that the most intensive energy consumption accounts for the comminution stage. For example, crushing and grinding required 50% and 94% for Processes 8 and 17, respectively (Figure 4). As a result, appropriate mill, crusher, and sizing techniques should be chosen to avoid overgrinding with a reasonable amount of energy.
3.3. Estimation of Energy Consumption for Tungsten Ore Concentration in Mongolia: Erdene-Soum and Khovd Aimag as Case Studies
3.3.1. Estimation of Energy Consumption for the Concentration Process of Erdene-Soum and Khovd Aimag Tungsten Ore
The values obtained for the mineral processing of Erdene-soum and Khovd Aimag tungsten ore are listed in Table 7, including the comminution–separation circuit and information regarding the equipment [18,19]. The practical process for tungsten ore concentration requires multiple stages of crushing, grinding, and separation; however, the grade of tungsten increased significantly from 3.96% to 67% and from 2.55% to 62% for Erdene-soum and Khovd Aimag ore, respectively [18,19]. Jig separation was employed to increase the efficiency and decrease the cost of the treatment, and magnetic separation was required due to the ferberite and cassiterite contents after gravity separation for Erden-soum ore [18]. In the case of Khovd Aimag ore, although the tungsten mainly exits in the form of hubnerite (MnWO4) and scheelite (CaWO4), it has a larger range of specific gravities 6–7 than that of gangue minerals 2.6–3 [19]. Therefore, a shaking table was used for separation with variations in the inclination angle, the flow rate of feed water, and the particle size of the sample [19]. Consequently, the total energy consumption of the concentration process for the practical conditions was relatively high, ranging from 794 to 6355 kWh (Table 7). However, the obtained values for the two actual processes of tungsten ore were precisely in the range of the theoretical estimation, i.e., 362 to 8298 kWh, and similarly, energy-intensive consumption was required for the crushing and grinding, 46%–94% (Figure 5). The maximum value of energy consumption 6355 kWh (~6.4 MW) was further employed to predict and design a sufficient electric supply system.
3.3.2. Designing the Energy Supply System
The maximum energy consumption for the concentration of tungsten ore is relatively high; therefore, a hybrid system of two or more renewable energy generators is preferred to offer higher reliability, higher efficiency, and better power quality. The four periods of working hours were assumed based on the operating time of the HPS including wind, biomass, and solar (Table 8). The amount of energy generated in Periods 1, 2, and 3 was entirely affordable for the demand energy for concentration processing. Although the demand for energy in the last period (38.4 MWh) was much higher than the possible supply of 22.8 MWh, the remaining energy from previous periods (17.4 MWh) can compensate for the deficit between the demand and the supply in Period 4. The unused energy from the final period can be kept in the batteries to be used for the next period of working time or supply for nearby areas. The sizing method PoPA indicates that the proposed HPS consisting of three renewable resources is necessary and effective for the energy consumption of the practical processing of tungsten ore in Mongolia.
4. Conclusions
The range of energy consumption for the concentration of tungsten ores in Mongolia was theoretically predicted using Kick’s and Bond’s equations for crushing and grinding. The effect of the properties of the minerals and the operating parameters on the value of required energy was demonstrated using the MLR model. Kick’ constant, the Bond work index, and product size had significant impacts on the comminution stage, while the feed size showed less effect on the energy consumption. The ranges of energy consumption required for crushing and grinding were 0.12 to 2.21 kWh/t and 0.29 to 4.62 kWh/t, respectively. The combination of comminution and separation formed 18 different circuits with the range of required energy from 362 kWh to 8298 kWh. The most intensive energy consumption accounted for the comminution stage, ranging from 46 to 94% for the simplest to the fullest process. The calculation conducted on the actual processing of Erdene-soum and Khovd Aimag tungsten ore showed the minimum and maximum values of energy consumption of 794 to 6280 kWh and 826 to 6355 kWh, respectively. The sizing method PoPA indicated that the proposed HPS consisting of three renewable resources (wind, biomass, and solar) was affordable to supply the highest demand energy of 6355 kWh for the four periods of working time. The present study provides a variety of options for the combination of size reduction and separation equipment, which can be later customized based on the mineralogical properties of tungsten ore and the available resources in Mongolia mining sites toward an efficient concentration process for tungsten ores.
Author Contributions
Conceptualization, J.L.; methodology, J.L. and H.B.T.; software, T.S., J.S. and S.K.; validation, T.S., J.S. and S.K.; formal analysis, T.S., J.S. and S.K.; data curation, H.B.T. and S.K.; writing—original draft preparation, H.B.T.; writing—review and editing, J.L.; visualization, H.B.T.; supervision, J.L.; project administration, J.L. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea (No. 20218530050040).
Data Availability Statement
Data are contained within the article.
Acknowledgments
The authors would like to thank Tsogchuluun Davaadorj from the Mineral Processing and Metallurgy Research Center, Korea Institute of Geoscience and Mineral Resources (KIGAM) for providing information on Erdene-soum and Khovd Aimag tungsten ore processing.
Conflicts of Interest
The authors declare no conflicts of interest.
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Figure 1.
Global tungsten ore production and reserves in 2020. Adapted from [6].
Figure 1.
Global tungsten ore production and reserves in 2020. Adapted from [6].
Figure 2.
Distribution of major tungsten ores in Mongolia. Adapted from Gerel et al., 2021 [31].
Figure 2.
Distribution of major tungsten ores in Mongolia. Adapted from Gerel et al., 2021 [31].
Figure 3.
Contour plot of energy consumption versus significant factors: (a,b) crushing (K, F1, and P1 are Kick’s constant, feed size, and product size); (c,d) grinding (W, F2, and P2 are Bond work index, feed size, and product size).
Figure 3.
Contour plot of energy consumption versus significant factors: (a,b) crushing (K, F1, and P1 are Kick’s constant, feed size, and product size); (c,d) grinding (W, F2, and P2 are Bond work index, feed size, and product size).
Figure 4.
Distribution of each device in energy consumption for Process 8 and Process 17.
Figure 5.
Distribution of each equipment in energy consumption for practical prosses of Erdene-soum and Khovd Aimag tungsten ore.
Figure 5.
Distribution of each equipment in energy consumption for practical prosses of Erdene-soum and Khovd Aimag tungsten ore.
Table 1.
Major chemical compositions and final grade of WO3 in Erdene-soum and Khovd Aimag ores.
| Name | Mineral Type | Major Chemical Composition (%) | Final Tungsten Grade (%) |
|---|---|---|---|
| Erden-soum (Tuv Aimag, central region) | Ferberite (FeWO4) | WO3: 3.96% SiO2: 86.15% Al2O3: 5.52% Fe2O3: 2.59% Sn: 0.7% | WO3 67% |
| Khovd Aimag (western region) | Hubnerite (MnWO4) Scheelite (CaWO4) | WO3: 2.55% SiO2: 64.12% Al2O3: 12.57% Fe2O3: 5.5% CaO: 3.68% MnO: 0.71% | WO3 62% |
Table 2.
Assumption of capacity and energy generation for renewable generators.
| Renewable Source | Operating Time | Time Interval (h) | Capacity (MW) | Energy Generation (MWh) | ||
|---|---|---|---|---|---|---|
| AC | DC | From | To | |||
| Wind | 0 | 12 | 12 | 3 | 18 | |
| Biomass | 0 | 24 | 24 | 4 | 48 | |
| Solar | 8 | 18 | 10 | 3 | 15 | |
Table 3.
Summary of factors and their values for calculation of energy consumption.
| Parameter | Unit | Value |
|---|---|---|
| Kick’s constant | kWh/t | Kk: 0.2, 0.4 and 0.6 |
| Bond work index | kWh/t | Wi: 7, 12 and 17 |
| Feed size | mm | Crushing (F1): 100, 150, 200 Grinding (F2): 5, 25, 50 |
| Product size | mm | Crushing (P1): 5, 25, 50 Grinding (P2): 1, 2, 3 |
Table 4.
Summary of the regression model statistics between energy consumption and the investigated parameters (Kick’s constant Kk or Bond work index Wi, feed size, and product size).
Table 4.
Summary of the regression model statistics between energy consumption and the investigated parameters (Kick’s constant Kk or Bond work index Wi, feed size, and product size).
| Source | Crushing | Grinding | ||
|---|---|---|---|---|
| AdjSS | p-Value | AdjSS | p-Value | |
| Kk/Wi | 3.049 | 0.000 | 11.18 | 0.000 |
| Feed size | 0.345 | 0.012 | 5.762 | 0.000 |
| Product size | 3.691 | 0.000 | 11.58 | 0.000 |
| Regression | 7.086 | 0.000 | 28.52 | 0.000 |
| Regression equation | W = 0.12 + 2.1Kk + 0.003F1 − 0.02P1 | W = 0.94 + 0.16Wi + 0.03F2 − 0.8P2 | ||
| Model summary | R2 = 87% | R2 = 88% | ||
Table 5.
Prediction of energy consumption for each device in the concentration process.
| Process Stage | Equipment | Kk or Wi * (kwh/t) | Feed Size (mm) | Product Size (mm) | Power (kW) | Capacity (t) | Energy Consumption Per Hour (ECPH, kWh) |
|---|---|---|---|---|---|---|---|
| Comminution | Jaw crusher (C1) | 0.2–0.6 | 200–100 | 50–25 | 200 | 480–1160 | Min: 114 Max: 1845 |
| Cone crusher (C2) | 0.2–0.6 | 50–25 | 10–5 | 220 | 58–336 | Min: 27 Max: 436 | |
| Rod mill (M1) | 7–17 | 25–6 | 3–1 | 1600 | 200–580 | Min: 112 Max: 1800 | |
| Ball mill (M2) | 7–17 | <20 | 3–1 | 800 | 800 | Min: 230 Max: 3692 | |
| Separation | Flotation (F) | - | - | - | 55 | 90 | 435 |
| Shaking table (S) | - | - | - | 1.1 | 80 | 103 | |
| Magnetic (M) | - | - | - | 20 | 880 | 120 |
* Kk and Wi are the Kick’s constant and Bond work index, respectively.
Table 6.
Energy consumption per hour for different combinations of comminution and separation circuits.
Table 6.
Energy consumption per hour for different combinations of comminution and separation circuits.
| Process No. | Comminution | Separation | Min ECPH (kWh) | Max ECPH (kWh) | |||||
|---|---|---|---|---|---|---|---|---|---|
| C1 | C2 | M1 | M2 | F | S | M | |||
| 1 | O | O | O | O | 781 | 4170 | |||
| 2 | O | O | O | O | 449 | 3838 | |||
| 3 | O | O | O | O | 899 | 6062 | |||
| 4 | O | O | O | O | 567 | 5730 | |||
| 5 | O | O | O | O | O | 1011 | 7862 | ||
| 6 | O | O | O | O | O | 679 | 7530 | ||
| 7 | O | O | O | O | 694 | 2791 | |||
| 8 | O | O | O | O | 362 | 2459 | |||
| 9 | O | O | O | O | 812 | 4683 | |||
| 10 | O | O | O | O | 480 | 4351 | |||
| 11 | O | O | O | O | O | 924 | 6483 | ||
| 12 | O | O | O | O | O | 592 | 6151 | ||
| 13 | O | O | O | O | O | 808 | 4606 | ||
| 14 | O | O | O | O | O | 476 | 4274 | ||
| 15 | O | O | O | O | O | 926 | 6498 | ||
| 16 | O | O | O | O | O | 594 | 6166 | ||
| 17 | O | O | O | O | O | O | 1038 | 8298 | |
| 18 | O | O | O | O | O | O | 706 | 7966 | |
Table 7.
Estimation of energy consumption per hour for practical processing of Erden-soum and Khovd Aimag tungsten ore.
Table 7.
Estimation of energy consumption per hour for practical processing of Erden-soum and Khovd Aimag tungsten ore.
| Tungsten Ore Deposit | Mineral Processing | Energy Consumption per Hour (ECPH, kWh) |
|---|---|---|
| Erden-soum (Tuv Aimag, central region of Mongolia) | 2 Crushing (jaw and cone crusher) 2 Grinding (rod mill) 3 Shaking table 1 Magnetic separation | Min: 794 Max: 6280 |
| Khovd Aimag (western region) | 2 Crushing (jaw and cone crusher) 1 Grinding (ball mill) 4 Shaking table | Min: 826 Max: 6355 |
Table 8.
Value of energy demand and energy generation from renewable resources (HPS: wind, biomass, and solar) in each period of working time.
Table 8.
Value of energy demand and energy generation from renewable resources (HPS: wind, biomass, and solar) in each period of working time.
| Time | Time Interval (h) | Capacity (MW) | Energy Generation (MWh) | Cumulative Storage | Energy Demand (MWh) | |||
|---|---|---|---|---|---|---|---|---|
| AC | DC | AC | DC | AC to DC 1 | DC | DC | ||
| 0 | ||||||||
| 8 | 8 (Period 1) | 7 | 0 | 56 | 0 | 53.2 | 2.0 | 51.2 |
| 12 | 4 (Period 2) | 7 | 3 | 28 | 12 | 38.6 | 13.0 | 25.6 |
| 18 | 6 (Period 3) | 4 | 3 | 24 | 18 | 40.8 | 2.4 | 38.4 |
| 24 | 6 (Period 4) | 4 | 0 | 24 | 0 | 22.8 | 38.4 | |
1 AC convert to DC = amount of AC × rectifier efficiency (0.95).
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MDPI and ACS Style
Trinh, H.B.; Kim, S.; Son, T.; Song, J.; Lee, J. Evaluation of Energy Consumption for Mineral Processing of Tungsten Ore in Mongolia: Khovd Aimag and Erdene-Soum as Case Studies. Minerals 2025, 15, 660. https://doi.org/10.3390/min15060660
AMA Style
Trinh HB, Kim S, Son T, Song J, Lee J. Evaluation of Energy Consumption for Mineral Processing of Tungsten Ore in Mongolia: Khovd Aimag and Erdene-Soum as Case Studies. Minerals. 2025; 15(6):660. https://doi.org/10.3390/min15060660
Chicago/Turabian StyleTrinh, Ha Bich, Seunghyun Kim, Taehun Son, Junkun Song, and Jaeryeong Lee. 2025. "Evaluation of Energy Consumption for Mineral Processing of Tungsten Ore in Mongolia: Khovd Aimag and Erdene-Soum as Case Studies" Minerals 15, no. 6: 660. https://doi.org/10.3390/min15060660
APA StyleTrinh, H. B., Kim, S., Son, T., Song, J., & Lee, J. (2025). Evaluation of Energy Consumption for Mineral Processing of Tungsten Ore in Mongolia: Khovd Aimag and Erdene-Soum as Case Studies. Minerals, 15(6), 660. https://doi.org/10.3390/min15060660
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