Mathematical Study Simulating Hydroelectric Power as a Renewable Green Energy Alternative

Mathematical Study Simulating Hydroelectric Power as a Renewable Green Energy Alternative

Tulus* Semin Muhammad Romi Syahputra Tulus Joseph Marpaung Jonathan Liviera Marpaung

Mathematics Department, Mathematics and Natural Sciences Faculty, Universitas Sumatera Utara, Medan 20155, Indonesia

Marine Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia

Statistics Department, Vocational Faculty, Universitas Sumatera Utara, Medan 20155, Indonesia

Corresponding Author Email: 
tulus@usu.ac.id
Page: 
1877-1884
|
DOI: 
https://doi.org/10.18280/mmep.110717
Received: 
6 February 2024
|
Revised: 
2 April 2024
|
Accepted: 
10 April 2024
|
Available online: 
31 July 2024
| Citation

© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

OPEN ACCESS

Abstract: 

The incorporation of renewable energy sources to fulfill the global energy demands has emerged as a crucial aspect in a complete investigation. Various options for generating renewable energy encompass multiple elements, including wind, steam, and water. The objective of the project is to investigate the modeling of Hydroelectric Power as a viable option for the advancement of sustainable green energy. The Hydroelectric power system was modeled using fluid dynamics computational program utilizing up-elements. The highest fluid flow rate of 153.67 liters per minute corresponds to a pumping power of 15,146 Newton meters per second, or a pump efficiency of 27,630%. On the other hand, the minimum flow rate of 95,230 liters per minute results in a pump power of 24,630 Newton meters per second, with an efficiency of 62,049%. Based on the experimental simulation results, it can be inferred that the water hose will function most effectively over a prolonged period with a low flow rate. This is because a minimal u(x, y) value will result in low pressure on the hose.

Keywords: 

hydroelectric power, fluid dynamics computation, finite elements, green energy, simulation

1. Introduction

In addition to the growing recognition of the detrimental effects of fossil fuel consumption on the environment, renewable energy is garnering worldwide recognition. Hydroelectric power, a form of renewable energy, harnesses the energy of water to produce electricity. Hydropower projects have experienced significant growth in recent decades, serving as a crucial component of a worldwide initiative to diminish greenhouse gas emissions and address the challenges of climate change. Hydroelectric power harnesses the potential energy of water and converts it into electrical energy using turbines and generators. Large dams are constructed to retain river water and create reservoirs that store potential energy. The kinetic energy of water is transformed into mechanical energy when it passes through the turbine, and subsequently transferred into electrical energy by the generator. Hydroelectric power offers a significant benefit since it relies on a renewable and eco-friendly energy source, without producing any direct emissions during its operation.

Hydroelectric power technology has advanced in recent years, incorporating novel ideas like ocean-current power plants and pump-turbine systems capable of storing surplus energy for future use. Despite the numerous benefits of hydroelectric power, such as its reliable supply and durable infrastructure, these projects frequently encounter environmental and societal obstacles. The alteration of river flow and its effects on river ecosystems are frequently a significant source of worry, and the involvement of local populations in the project development process is crucial for its effective execution. Hydroelectric power, as a sustainable energy option, holds significant promise in diminishing reliance on non-renewable resources and mitigating the worldwide emission of carbon dioxide. Nevertheless, it is crucial to consider sustainability and its associated consequences when designing and executing these initiatives. Through persistent exploration of the possibilities offered by renewable energies, such as hydroelectric power, the world can achieve sustainable objectives and establish a more pristine and ecologically conscious future.

In order to establish a research concentration on water taps within the realm of renewable energy, a comprehensive approach is necessary, considering the significant contribution this technology can make as a low-carbon, environmentally friendly, and sustainable energy source on a global scale. The design and optimization of water cranes to convert water kinetic energy to electrical energy with maximum efficiency, an in-depth understanding of the fluid dynamics and fluid mechanics that influence crane operation, and the adaptation of this technology to a variety of hydrological and environmental conditions are the primary concerns of this research. Additionally, it encompasses the investigation of novel materials and state-of-the-art technologies to facilitate the production of embroidery that is more resilient, productive, and ecologically sustainable. The advancement of predictive models and computer simulations that assess the performance of water faucets under diverse conditions, such as fluctuations in water flows and geographical factors, ought to be the focus of research. Additionally, socioeconomic factors such as the availability of technology in remote regions, the environmental and social consequences of water tap installation, and business models that facilitate the extensive integration of this technology into society should be taken into account. Additionally, a promising area of study is the integration of water pockets with other renewable energy systems, such as solar and wind, in order to produce hybrid systems that are more dependable and efficient. Through the resolution of these obstacles, scientific inquiry can facilitate the advancement and integration of water taps as a pivotal element in the worldwide shift towards more sustainable energy sources. Moreover, it can bolster endeavors to mitigate greenhouse gas emissions and significantly contribute to energy security and economic progress on a global scale. By integrating knowledge from economics, society, engineering, environmental sciences, and environmental sciences, a multidisciplinary approach will be essential for addressing the intricacies of these challenges and optimizing the capabilities of water beams in the context of renewable energy.

Multiple scholars have conducted studies to determine the energy output of various renewable energy models [1-3]. Viollet's [4] study investigated the mechanisms via which turbines harness fluid movements to generate a specific amount of electrical energy. Adanta [5] utilized fluid dynamics computing simulation to analyze an experimental flush with a low fluid flow rate. Hydroelectric power involves the utilization of several types of turbines to convert mechanical energy into various forms of electrical energy. The study conducted at the National Reference Center for Small Hydroelectric Plants of the Federal University of Itajuba tested a single turbine with a dike height of up to 4 m and a flow rate of 0.35 m3/s. The results indicated that a hydraulic efficiency of 70% was optimal for a flow rate of 1m3/s and a rotation speed of 534 rpm. The turbine generated an electrical power of 56 kilowatts in the study. The adjustment led to an increase in the turbine's efficiency to 79% ± 4.5% at a rotation speed of 696 rpm, resulting in the generation of 3.367 kW of power and a flow rate of 0.04 m3/s [6-9].

In this study, we will simulate the behavior of the kincir against the flow of turbulent fluid so that we can strengthen the analysis of the exhaustion rate of the system and in the long term we will do research towards optimization of models that provide optimal energy.

1.1 Navier-Stokes approach

The Navier-Stokes equation, a fundamental principle in the field of fluid dynamics, characterizes the motion of fluids by taking into account multiple parameters like pressure, viscosity, and external friction. Within the realm of turbulent fluid flows, which are distinguished by their chaotic nature and the presence of vortices at different scales, this equation unveils the imperceptible intricacy inherent in laminar flows. The Navier-Stokes equation is insufficient to correctly explain turbulence due to its random and multi-scale nature. This is because the equation requires a very high computational resolution to capture phenomena at all relevant scales. The general formula of Navier-Stokes approach is:

$\frac{\partial u}{\partial t}+(u . \nabla) u=-\frac{1}{\rho} \nabla p+v \nabla^2 u+f$     (1)

The mathematical modeling of fluid flow in hydroelectric power plants involves the conversion of mechanical energy into electrical energy. This process utilizes the significant potential and kinetic energy of the fluid on a turbine rotor. If $\vec{u}$ and $\vec{P}$ represent the vector components of speed and pressure and denote their respectively first derivatives with respect to time. The equation representing the conservation of mass and momentum is given by equation [9]:

$\nabla \cdot \bar{u}=0$,   (2)

$\rho\left(\frac{\partial \overline{\mathbf{u}}}{\partial t}\right)+\rho \overline{\mathbf{u}} \cdot \nabla \overline{\mathbf{u}}=-\nabla \bar{p}+\nabla \cdot(2 \mu S-R)+\rho \mathbf{f}$      (3)

where, $\rho$ represents the density of the fluid, $\mu$ represents the viscosity of the fluid, and $f$ indicates the type of friction on the surface. When analyzing fluid mechanics, we observe a significant centrifugal string direction with a value $S=$ $\frac{1}{2}(\nabla \bar{u}+\nabla T \bar{u})$. Additionally, the Reynolds pressure value is given by $R=\rho \bar{u}^{\prime} \times \bar{u}^{\prime}$, which leads to oscillations in fluid flow rate. The combination of the Share Stress Transport (SST) $k-\omega$ and $k-\varepsilon$ models. The SST $k-\omega$ model represents fluid flow close to the surface, while the $k-\varepsilon$ model represents flow further away from the surface. The turbulent kinetic energy on the rotor and its dissipation rate against the fluid's angular velocity $\omega$ are:

$\frac{\partial}{\partial t}(\rho k)+\nabla(\rho k \bar{u})=\nabla \cdot\left(\Gamma_k \nabla_k\right)+G_k-Y_k+S_k$    (4)

$\frac{\partial}{\partial t}(\rho \omega)+\nabla(\rho \omega \bar{u})=\nabla \cdot\left(\Gamma_\omega \nabla_\omega\right)+G_\omega-Y_\omega+S_\omega$    (5)

where, $G_k$ represents the turbulence resulting from the fluid potential, $\Gamma_{\omega, k}$ denotes the significant effective value of the diffusion coefficient, $Y_{\omega, k}$ represents a condition of divergence, and $D_\omega$ represents an orthogonal condition of divergence. Domain discrimination is employed in numerical simulations to accurately determine the beginning parameters that significantly influence the energy generated by variations in speed and pressure over time [10-12].

1.2 Hydraulic compressible model

Fluid flow procedures including potential differences can lead to significant compression experienced by fluids. Hydraulic systems do not experience compression when subjected to unsteady flow conditions. The fundamental equations of fluid continuity are as follows:

$g A^2 \frac{\partial H}{\partial l}+Q \frac{\partial Q}{\partial l}+A \frac{\partial Q}{\partial t}+\frac{f Q|Q|}{2 D}=0$   (6)

$Q \frac{\partial H}{\partial l}+A \frac{\partial H}{\partial t}+\frac{a^2}{g} \frac{\partial Q}{\partial l}=0$    (7)

The equation is simplified to incorporate the variable component for each initial condition, resulting in:

$\frac{g A H_r}{L Q_r} \frac{\partial h}{\partial x}+\frac{Q_r}{A L}\left(q+q_0\right) \frac{\partial q}{\partial x}+\frac{\partial q}{\partial t}+\frac{f Q_r}{2 D A}\left|q+q_0\right|\left(q+q_0\right)=0$  (8)

$\frac{Q_r}{A L}\left(q+q_0\right) \frac{\partial h}{\partial x}+\frac{\partial h}{\partial t}+\frac{a^2 Q_r}{g A L H_r} \frac{\partial q}{\partial x}=0$   (9)

The values of the components h, q, and x are as follows:

$h=\frac{H-H_0}{H_r}, q=\frac{Q-Q_0}{Q_r}, x=\frac{l}{L}$    (10)

In this case, the simulation of hydroelectric power plants involves the utilization of a nonlinear model to represent the flow.

2. Research Methodology

This study utilizes the principles of computational fluid dynamics in conjunction with structural analysis employing the finite element approach. The substantial energy produced is a consequence of the transformation of the fluid's potential energy into mechanical energy, which is then transferred to the turbine over time, leading to the conversion of mechanical energy into electrical energy.

Figure 1. Analysis of fluid flow geometry on the waterwheel

Exploring the conceptualization of water wheels within the scope of fluid dynamics opens up insight into how significant the influence of fluid flow speed and pressure is on the efficiency and performance of the water wheel itself; where the speed of the fluid flow, which fundamentally refers to how fast the fluid moves through the water wheel, plays an important role in determining the amount of energy that the wheel can convert from the kinetic energy of the flow into mechanical energy, because the higher the speed of the fluid flow, the more kinetic energy available for conversion, but it should be noted that this relationship is not without limits because at a certain point, too high a speed can cause excessive turbulence and can damage the wheel or reduce its efficiency through the cavitation phenomenon, where air bubbles formed due to local pressure drops can implosion with sufficient force to damage the surface of the wheel blades; on the other hand, fluid flow pressure, which refers to the force that the fluid exerts per unit area on the wheel, is intrinsically related to flow velocity but provides additional perspective on how gravity, fluid density, and other environmental factors such as the slope of the river or canal in which the water wheel is located are located, contributing to the energy potential that can be converted by the mill, thus, a balance between flow velocity and pressure must be achieved to optimize the mill's energy output without compromising its structural integrity or operational efficiency, so research and development in modern waterwheel design often explores advanced technologies such as adjustable propellers and control systems that can respond dynamically to changing flow conditions to maximize the utilization of the kinetic and potential energy of the fluid flow, while also considering environmental and sustainability aspects, as increasing the efficiency of waterwheels not only contributes to the production of better energy cleaner and more sustainable but can also help in more efficient management of water resources, showing how in-depth knowledge of the influence of fluid flow velocity and pressure is essential in designing optimal renewable energy solutions (Figure 1).

The horizontal velocity of the fluid flow denoted as $U_{\infty}$, Ux,y flows in the x and y directions down the horizontal line, reaching a depth Lwet on the fluid surface. The alteration of the waterwheel's momentum and the fluid's velocity results in an implicit rise in the fluid flow acceleration, reaching a waterwheel ratio of ω rad/s. The variation in Ux,y will persist in tandem with alterations in momentum and mass throughout the process [5, 13-15].

We propose that the water flow in the turbine will follow a radial route in accordance with the geometry of the waterwheel. This arrangement will enable the rotation of the turbine to generate energy, which can then be stored in the dynamo. Figure 2 depicts a water stream flowing on the hydroelectric power.

Figure 2. Boundary of the waterwheel

Within the framework of fluid flow on a waterwheel, this momentum holds significant importance as it dictates the magnitude of tension exerted by the fluid on the waterwheel beam. An increase in the momentum of a fluid has the potential to enhance the efficiency of energy conversion by facilitating the transfer of tension to the waterwheel.

When a fluid is in motion and comes into contact with the cuffs, the fluids exert force on the cuff bars, therefore transferring a portion of their momentum to the cuffs. The application of Newton's rule of action and reaction is evident in this scenario. The fluid exerts a unidirectional force on the waterwheel, while simultaneously impeding the flow of fluid and diminishing its momentum.

In order to do a more comprehensive analysis of the fluid dynamics of a waterwheel, one can employ the Bernoulli equation and Navier-Stokes equation as fundamental frameworks. The Bernoulli equation, which establishes a relationship between flow speed, pressure, and height, can provide valuable insights into the pressure distribution along waterwheel beams. The Navier-Stocks equation, which characterizes the motion of a viscous fluid, offers understanding of the alterations in fluid momentum around the pinching beams.

The alteration in momentum conservation and the mass of the water squeeze will produce a certain quantity of energy resulting from the movement. Let us consider the fluid flow simulation as an incompressible flow, namely a Newtonian viscous fluid, described by the general equation:

$\frac{\partial(\rho)}{\partial t}+\frac{\partial\left(\rho u_j\right)}{\partial x_j}=0$      (11)

Given a Reynolds number (Re) of 1.33×104, the fluid flow model in the waterwheel space is represented using the Reynolds Averaged Navier-Stokes (RANS) concept with the following formula:

$\frac{\partial \rho u_i}{\partial t}+\frac{\partial \rho u_i u_j}{\partial x_j}=-\frac{\partial p}{\partial x_i}+\frac{\partial}{\partial x_j}\left(\overline{\tau_{i j}}-\overline{\rho u_i^{\prime} u_j^{\prime}}\right)+\rho g_j$    (12)

The variables in the equation are listed as follows: p represents pressure, τij represents voltage viscosity, ρuiuj represents Reynolds voltage, and g represents gravitational acceleration [16-18]. The gravitational acceleration impacts the water waterwheel model as it causes the fluid flow to travel towards the Earth's surface and into open spaces, resulting in:

$-\overline{\rho u_i^{\prime} u_j^{\prime}}=\mu\left(\frac{\partial u_i}{\partial x_j}+\frac{\partial u_j}{\partial x_i}\right)-\frac{2}{3}\left(\rho k+\mu \frac{\partial u_i}{\partial x_i}\right) \delta_{i j}$     (13)

A waterwheel model was developed using COMSOL Multiphysics 5.6 to investigate the correlation between energy generation resulting from velocity changes and the impact of centrifugal type variations [4, 19, 20].

The materials used in the model are iron and solid plates with constant viscoelastic characteristics τy (yield stress) [14, 21].

3. Result and Discussions

3.1 Experimental simulation

The simulation is done by looking at the characteristics of the change in speed against the great energy generated by the rotation of the waterwheel. Figure 3 shows the representation of the critical point on the fluid flow scattered.

Figure 3. Mesh model 2D waterwheel

Figure 4. Fluid pressure on the viscous unit

Figure 4 illustrates the dispersion of energy during each rotation of the pinch, leading to the eventual depletion of the system over an extended duration. The turbulent fluid flow of the waterwheel will disperse around the outer surface of the waterwheel, exhibiting a color shift at each stage of the process. The result of the rotation of the waterwheel results in a huge change in pressure on each kitchen bucket. The relationship of the change in speed with the pressure has a direct impact on the movement of fluid mass from the inlet and the outlet.

In the exploration of turbulent water flow as a driving medium in a water wheel simulation aimed at alternative power generation, the intrinsic relationship between the speed and pressure of the water flow becomes a critical factor that influences the efficiency and effectiveness of the wheel in converting kinetic energy of the flow into electrical energy, where the speed of the water flow is increases theoretically have the potential to increase the resulting energy output due to the direct relationship between the fluid's kinetic energy and the square of its velocity, however, in practice, increases in water flow velocity are often accompanied by increases in turbulence characteristics, which not only make it difficult to predict and manage in wheel design but can also Inducing significant local pressure drops at certain points along the blades, this phenomenon, known as cavitation, has the potential to damage the blades and reduce overall operational efficiency as implosion of the resulting air bubbles can cause material erosion. and loss of momentum in the fluid flow, in addition, excessive turbulence can result in uneven pressure distribution on the surface of the blade, causing fluctuations in the rotational speed of the wheel which ultimately affects the consistency of the electrical output produced, to overcome this challenge, wheel simulation Water in the context of alternative power generation requires a careful and innovative design approach, involving the use of optimized propeller profiles to reduce the negative impacts of turbulence and advanced flow management techniques, such as flow guidance and diffusers that can stabilize the flow before it contacts the propellers. propellers, in addition, state monitoring and intelligent control technology can be applied to dynamically adjust the position or orientation of the propellers based on real-time flow conditions, maximizing energy extraction from turbulent water flows while minimizing the risk of cavitation and erosion, expertise in fluid dynamics and Turbulent flow mechanics, therefore, became of great importance in the development of waterwheels as alternative power plants, where a deep understanding of the relationship between speed and pressure in turbulent water flows allows engineers and designers to optimize the design and operation of waterwheels, thereby achieving a balance between energy effectiveness and operational sustainability in the face of natural challenges and variability in flow conditions, creating power generation solutions that are not only efficient and reliable but also environmentally friendly, underscoring the importance of technological innovation and adaptation in addressing future energy challenges.

The effect of the change of speed also results in the flow rate having a change of value over time, the $\frac{\partial u_x}{d t}$ shows the change in Figure 5.

Figure 5. Relationship of speed change to pressure on the waterwheel

Understanding the efficacy and performance of the system requires a firm grasp on the interconnections among generated energy, pressure, speed, and torque when simulating a water hose as an alternative power plant. The velocity of the turbulent water flow is a crucial factor in determining the quantity of kinetic energy that can be transformed into mechanical energy by the water hose. Nevertheless, it is worth noting that augmentations in flow velocity frequently coincide with heightened pressure, hence potentially impacting the efficacy of the water pin. The flow pressure is a fundamental quantity that governs the fluid's pressure distribution per unit area on the beam's surface. Turbulent flow can lead to an uneven pressure distribution, particularly around the beams, which might cause torque changes on the beak. The torque, which is influenced by the orientation of the bead, serves as an indicator of the rotational force exerted on the shaft. The torque generated by the water hose exhibits a strong correlation with both the velocity of the flow and the pressure exerted on it. Understanding the response of the water pinch to a specific flow condition in the simulation relies on the change in torque generated by the pinch as a result of variations in speed and flow pressure. The generation of electricity is facilitated by the conversion of mechanical energy into electrical energy, which is achieved by the torque generated by the water hose. The magnitude of torsion directly correlates with the amount of energy that may be harnessed from the water stream and subsequently transformed into electrical energy. Hence, while simulating water hoses, it is crucial to simulate the correlation between flow speed and pressure, as well as the resulting torque, in order to accurately estimate the potential electric energy that can be generated by such a hose. Engineers can enhance the design of water taps by comprehending this relationship in depth, resulting in improved operating efficiency and increased energy output. The utilization of simulation data that considers these variables enables the optimization of design parameters for the water tap, including tap shape and size, in order to achieve optimal performance across diverse turbulent water flow scenarios. Hence, the examination of the correlation among velocity, pressure, torque, and energy produced in the turbulent water flow within water tap simulations holds significant importance in the advancement of effective and sustainable alternative power facilities. These facilities aim to not only maximize the utilization of natural resources but also mitigate adverse environmental consequences.

Figure 6. The level of fluid flow against the change in speed

Figure 6 illustrates the correlation between the mass transfer rate and the power of flow when rotating the water pinch. The rate of change of pulse power to flux power in liters/minutes will decrease with time under steady state settings, as a result of variations in the impulse style of the pinch head on a certain iteration. The change in fluid flow speed, represented by the value ux,y, will exert pressure on each handle arm at the critical point of speed change. This alteration in speed will therefore lead to a modification in the centrifugal force acting on the handle rotation, facilitating the movement of fluid mass and momentum. Due to water level drop, mechanical obstacles, or blockages, the pinch may lose water velocity and amount. Reduced mass flow reduces water squeeze power. Power (P) is the product of mass flow (m) and energy per unit of mass (E), which are affected by flow velocity and gravity. The graph shows the water Pinch's ability to convert water's kinetic energy into mechanical energy decreasing with time. Falling flow power and mass transfer flow show this drop.

Figure 7. Changes in pressure against fluid flow speed

Table 1. Comparison of changes in pressure values, torsions, and fluid flow rate on the waterwheel

$\mathbf{p}_{\text {tot}_{in}}$  (bar)

Static Pressure Increase (N/m2)

Total Pressure Increase (N/m2)

Torque (N*m)

Shaft Power Consumption (Nm/s)

Power Given to Fluid (Nm/s)

Pump Efficiency (1)

Head (m)

Flowrate (l/min)

-0,0500

-3,329.1

5,913.7

0.52347

54,818

15,146

0.27630

0.60411

153.67

-0,0750

663.38

8,449.5

0.50346

52,722

20,124

0.38170

0.86316

142.90

-0,1000

4,531.3

10,874

0.47598

49,844

23,595

0.47338

1.1108

130.20

-0,1250

8,337.1

13,228

0.43678

45,739

25,402

0.55536

1.3513

115.22

-0,1500

12,207

15,518

0.37906

39,695

24,630

0.62049

1.5853

95,230

The efficiency of pressure changes in the work of the waterwheel in the flow of fluid will result in a change in the torsion value of the fluid pump process. A visual response to the flow dynamics that influence the performance and efficacy of the water tap is indicated by the color changes that occur in a turbulent water stream. The color patterns observed on the tap surface are influenced by the turbulence of the water stream, which is indicative of the fluctuating pressure distribution and variations in flow velocity surrounding the tap taps. By observing color variations in a water pin simulation, one can gain valuable insights into the interaction between pressure, flow speed, pinch shape, and overall performance. The alterations in color noticed on the water pin can serve as indicators of regions with elevated or diminished pressure, as well as the variations in flow velocity along the pinch's surface. Figure 7 illustrates that a more intense hue signifies a substantial alteration in pressure or velocity, whereas a steady hue is depicted in blue in regions with a more uniform pressure and velocity. The utilization of visual analysis to examine the alteration in hue can serve as a significant tool in comprehending the dynamics of fluid flow and assessing the efficacy of the suggested water pin configuration. Furthermore, alterations in color can serve as markers for identifying any operational issues, such as regions susceptible to cavitation or erosion, which can impact the effectiveness and structural soundness of the device. Hence, the alterations in color observed on water cranes during turbulent flow simulations serve a dual purpose: enhancing the visual comprehension of flow circumstances and serving as a vital diagnostic instrument for the advancement and upkeep of water cranes as a viable alternative power generation facility. Researchers can utilize these visual data to pinpoint regions that necessitate design modifications or operational enhancements in order to achieve optimal performance and sustain water tap efficiency throughout diverse flow circumstances.

A crucial factor influencing the flow velocity and flow pressure, flowrate denotes the quantity of water volumes traversing the vault within a given time period. As the flow rate increases, a corresponding volume of water traverses a vault, leading to a concomitant escalation in flow velocity and pressure (Table 1). Nevertheless, variations in the flowrate can cause fluctuations in the overall flow characteristics within the context of turbulent flow. This may have an impact on the pressure distribution surrounding the pinch, which is critical for optimizing the pinch's efficacy. Fluctuations in the flow rate may result in alterations to the flow patterns, subsequently impacting the distribution of pressure on the chinch-bone pressing surface. The torque generated by the pinch may experience an increase or decrease due to this pressure imbalance, thereby influencing the efficacy of the mechanical energy-to-electric energy conversion. Additionally, the velocity of the turbulent water flow significantly influences this correlation. The rate of water flow influences the quantity of kinetic energy that can be transformed into mechanical energy through the compression. An increase in flow velocity results in a corresponding extraction of kinetic energies by the Kinch, thereby ultimately fostering a surge in the generation of electrical energy. Nonetheless, variations in flow velocity may also induce heightened turbulence, thereby influencing the pressure distribution and overall effectiveness of the compression. Hence, it is critical to incorporate modeling the interplay between flowrate, pressure, and velocity in turbulent water flows into water pin simulations in order to comprehend the intricacies of flow dynamics and forecast pinch performance across diverse conditions. By meticulously analyzing simulation data, engineers are able to optimize the performance of the water pin design and operational parameters in order to generate electricity from turbulent water flows. Therefore, a comprehensive comprehension of this correlation is critical in the advancement of alternative power generation technologies that are more dependable, sustainable, and efficient. Such technologies can aid in diminishing reliance on traditional energy sources and ameliorating adverse environmental effects. The maximum fluid flow rate of 153.67 liters per minute is achieved with a pump power of 15.146 Newton meters per second and a pump efficiency of 27.63%. On the other hand, the minimum flow rate of 95.23 liters per minute requires a pump capacity of 24.630 Newton meters per second, with an efficiency of 62.05%. Based on the data from this experimental simulation, it can be inferred that the pump will operate most effectively over an extended period of time with a low flow rate. This is because the u(x,y) configuration will exert minimal pressure on the waterwheel 's bucket. Prolonged periods of effort will lead to significant changes in mass and momentum while requiring minimal energy use.

4. Conclusions

According to the research findings, it can be inferred that the waterwheel is designed to operate at a low speed but with an efficient flow rate. The simulation shows that the highest fluid flow rate of 153.67 liters per minute corresponds to a pumping power of 15,146 Newton meters per second, or a pump efficiency of 27.63%. On the other hand, the minimum flow rate of 95.23 liters per minute results in a pump power of 24,630 Newton meters per second, with an efficiency of 62.05%. This allows the waterwheel pump to work for extended periods of time, resulting in a significant amount of energy generated at the minimum fluid flow rate. The duration required for a machine to generate renewable energy is typically lengthy. The author assumes that in order to optimize the machine's long-term performance, it is necessary to regulate the flow speed of the fluid used to move the waterwheel. This is because waterwheel is sensitive to the pressure and momentum generated by the fluid's speed. To conduct additional research, we recommend employing simulation and empirical investigation to assess the system's exhaustion levels. Additionally, we propose developing a novel model of lightweight material geometry that can offer more efficient energy utilization.

Funding

The research was funded by the Research Institute of the University of North Sumatra (Grant No.: 424/UN5.1.R/RK/PPM/2019).

  References

[1] Singh, J., Singh, S., Singh, J.P. (2021). Investigation on wall thickness reduction of hydropower pipeline underwent to erosion-corrosion process. Engineering Failure Analysis, 127: 105504. https://doi.org/10.1016/j.engfailanal.2021.105504

[2] Zielinski, M., Myszkowski, A., Pelic, M., Staniek, R. (2022). Low-speed radial piston pump as an effective alternative power transmission for small hydropower plants. Renewable Energy, 182: 1012-1027. https://doi.org/10.1016/j.renene.2021.11.014

[3] Li, Z., Zhang, L. (2012). Research on numerical method of flow-induced vibration on spiral casing structure of large-scale hydropower station. Procedia Engineering, 31: 688-695. https://doi.org/10.1016/j.proeng.2012.01.1087

[4] Viollet, P.L. (2017). From the water wheel to turbines and hydroelectricity. Technological evolution and revolutions. Comptes Rendus. Mécanique, 345(8): 570-580. https://doi.org/10.1016/j.crme.2017.05.016

[5] Adanta, D., Sari, D.P., Syofii, I., Sahim, K., Martides, E., Radiansah, Y., Subagio, D.G., Utomo, Y.S., Rosyid, O.A., Fudholi, A. (2024). Pico scale undershot waterwheel for ultra-low-head: Analytical, experimental and CFD method. Renewable Energy Focus, 48: 100532. https://doi.org/10.1016/j.ref.2023.100532

[6] Kodirov, D., Tursunov, O. (2019). Calculation of water wheel design parameters for micro hydroelectric power station. E3S Web Conference, 97. https://doi.org/10.1051/e3sconf/20199705042

[7] Fu, X., Gou, T. (2023). Modeling of comprehensive power load of fishery energy internet considering fishery meteorology. Information Processing in Agriculture, 10(4): 581-591. https://doi.org/10.1016/j.inpa.2023.02.008

[8] Rahman, M.M., Syahputra, M.R., Marpaung, T.J., Marpaung, J.L. (2023). Computational assessment of wave stability against submerged permeable breakwaters: A hybrid finite element method approach. Mathematical Modelling of Engineering Problems, 10(6): 1977-1986. https://doi.org/10.18280/mmep.100607

[9] Adanta, D. (2020). The effect of channel slope angle on breastshot waterwheel turbine performance by numerical method. Energy Reports, 6: 606-610. https://doi.org/10.1016/j.egyr.2019.11.126

[10] Bilgili, M., Bilirgen, H., Ozbek, A., Ekinci, F., Demirdelen, T. (2018). The role of hydropower installations for sustainable energy development in Turkey and the world. Renewable Energy, 126: 755-764. https://doi.org/10.1016/j.renene.2018.03.089

[11] Owebor, K., Diemuodeke, E. O., Briggs, T.A., Imran, M. (2021). Power Situation and renewable energy potentials in Nigeria–A case for integrated multi-generation technology. Renewable Energy, 177: 773-796. https://doi.org/10.1016/j.renene.2021.06.017

[12] Marpaung, T.J. (2019). Computational analysis of water wheel for hydro-electric power. In Journal of Physics: Conference Series, 1376(1): 012017. https://doi.org/10.1088/1742-6596/1376/1/012017

[13] Azad, A.S., Rahaman, M.S.A., Watada, J., Vasant, P., Vintaned, J.A.G. (2020). Optimization of the hydropower energy generation using Meta-Heuristic approaches: A review. Energy Reports, 6: 2230-2248. https://doi.org/10.1016/j.egyr.2020.08.009

[14] Marpaung, T.J., Marpaung, J.L. (2023). Computational analysis for dam stability against water flow pressure. In Journal of Physics: Conference Series, 2421(1): 012013. https://doi.org/10.1088/1742-6596/2421/1/012013

[15] Cho, H., Kim, I., Park, J., Kim, D. (2022). A waterwheel hybrid generator with disk triboelectric nanogenerator and electromagnetic generator as a power source for an electrocoagulation system. Nano Energy, 95: 107048. https://doi.org/10.1016/j.nanoen.2022.107048

[16] Xu, H.M., Wang, D.Y., Liu, J.J. (2017). Process control optimization for hydroelectric power based on neural network algorithm. Advances in Modelling and Analysis C, 72(2): 155-166. https://doi.org/10.18280/ama_c.720204

[17] Maués, J.A. (2019). Floating solar PV-hydroelectric power plants in Brazil: Energy storage solution with great application potential. International Journal of Energy Production and Management, 4(1): 40-52. https://doi.org/10.2495/EQ-V4-N1-40-52

[18] Mahler, R.L. (2023). Public views on the importance and expansion of renewable electricity production over the last 35 years in Idaho, USA. International Journal of Energy Production and Management, 8(3): 133-139. https://doi.org/10.18280/ijepm.080301

[19] Sari, M.A., Badruzzaman, M., Cherchi, C., Swindle, M., Ajami, N., Jacangelo, J.G. (2018). Recent innovations and trends in in-conduit hydropower technologies and their applications in water distribution systems. Journal of Environmental Management, 228: 416-428. https://doi.org/10.1016/j.jenvman.2018.08.078

[20] López, Á.G., Benito, F., Sabuco, J., Delgado-Bonal, A. (2023). The thermodynamic efficiency of the Lorenz system. Chaos, Solitons & Fractals, 172: 113521. https://doi.org/10.1016/j.chaos.2023.113521

[21] Marpaung, J.L., Marpaung, T.J. (2020). Computational analysis of heat transfer in three types of motorcycle exhaust materials. In Journal of Physics: Conference Series, 1542(1): 012034. https://doi.org/10.1088/1742-6596/1542/1/012034