Development and Evaluation of a Solar Yacht: Enhancing Aerodynamics, Harnessing Solar Energy, and Assessing Costs and Environment Impact

Marine vessels, especially the older generation ships contribute to the pollution of seawater as proposed by Carreño & Lloret (2021). With the growing concern for the environment and the call for the use of renewable energy sources in the process of being answered, the construction of ships that will be powered by solar energy is gradually moving forward. The naval engineering is undergoing a significant transformation as it seeks to line up with global sustainability goals. The change from fossil fuel-powered vessels to renewable energy sources, such as solar power is a crucial step. Solar-powered yachts offer not only environmental benefits but also economic advantages, including reduced fuel costs and lower maintenance requirements. Also, these yachts can operate silently, enhancing the onboard experience for passengers by reducing noise pollution. This research aims to examine the concept design, system integration, and performance simulation of a small-capacity solar-powered yacht. The first goal is to offer a practical application to the current yachts that continue to use fossil fuels to reduce carbon emissions and operating costs. Based on the analysis, there are several reasons why the use of solar-powered yachts is necessary now. The yachts emit large amounts of greenhouse gases and other pollutants into the environment, which contributes to global warming and marine pollution. However, in solar-powered yachts, the use of renewable energy derived from the source of the sun means little or no emission during use. This research will focus on three main objectives: Designing and suggesting an original and ecological idea for a solar yacht, developing some of the main systems and elements of the ship, and performing the computational fluid dynamics to improve the design. Through incorporating the following hi-tech products in the fabrication and design of the frame, solar power collection, and energy storage the project aims at creating a power yacht that is slightly environmentally unfriendly.

OBJECTIVES:

 These are the following objectives of the project:

? To create a compact, environmentally friendly, solar-powered boat with a high capacity.

? To create the systems and parts that the boat needs. This covers propulsion systems, battery storage, and solar panels.

? To optimize the yacht's design by doing computer simulations and studies to evaluate the vessel's performance under various scenarios.

LITERATURE REVIEW

Yacht hull design must be optimized in improving fuel efficiency with minimal drag (Taylor et al., 2021). The findings of Taylor's research underscore the role that hull form and CFD can play in improving yacht design, incorporating their effect on efficiency at the highest level due to improved hydrodynamic performance. Miller and Smith (2019) go even further considering the potential influence of CFD on yacht design, demonstrating how computational fluid dynamics might be applied to hull geometries also performance improvements. One of the most interesting things about Solar is that it involves integrating solar panels into a yacht and doing so in an area, sustainable energy solutions onboard a boat having recently become big business. In Johnson (2020) the performance analysis of marine solar panels in efficiency and installation area is addressed. Williams & Garcia (2018) showed us that MATLAB and Simulink can be used for simulating the performance of solar panels under different conditions, emphasizing a precise modeling is essential to predict energy output. CFD analysis is a big part of determining the efficiency and effectiveness of yacht design changes, especially regarding understanding flow around fluid/jets passing through more complex geometries. CFD simulations have a vital role in marine engineering applications, as described by Brown et al. (2022) explicitly focusing on residuals and associated velocity vectors with pressure contours in the first place. The accuracy and validation of CFD simulations are elaborated to detail performance assessments by (Clark 2019). Without proper thermal management in place, solar panel will not be efficient and its life span won't last long. Nguyen (2021) explores the influence of ETFE, EVA or CFRP materials in combination on thermal performance of photovoltaic modules. Lee (2020) describes using ANSYS simulations to study temperature distributions and heat dissipation, as well cooling strategies affecting solar panel efficiency. This means that adding solar panels to the mix when it comes to designing yachts and boats can at some point be a viable option but will need full feasibility studies with regards budget planning as well as making sure they are damn easy and user friendly. According to Luís, 2023, enhancing the super yacht Silent 120's hydrodynamic performance was the main goal of this thesis. As the vessel's design and its parts were predetermined, the hull could only have appendix-style modifications such as lift-generating foils, trim adjustment flaps, and vortex-generating protuberances, among other things. Lift-generating foils had been by far the most widely used option in the naval industry. Not only did they greatly enhance the vessel's ability to maintain her seaworthiness, but they also allowed for the largest reduction in resistance of any alternative available. Because of their straightforward complexity, they were also easily implemented in a variety of scenarios. This study attempts to improve the vessel's hydrodynamic performance while keeping an eye on innovation. The company's potential clientele can be expanded by improving performance metrics through the reduction of overall drag. The concept of using a hydrofoil to accomplish this purpose was born; not only was it an easy implementation, but the advantages could not be overlooked. A prior simulation validation was required to report the data as accurately as feasible. We utilized a study from the National Advisory Committee of Aeronautics (NACA) for this purpose. In order to more effectively apply this study to our situation, we only examined the angles of attack that fell within our spectrum. This was done in direct accordance with experimental testing to maximize accuracy. After the optimal placement was determined, the 3D simulations could begin. One with the rear foil and the other with the hull alone. The same philosophy that we previously utilized for the 2D simulations with the vessel was applied here as well, however this time the dynamic meshing capability could function as planned. According to Adam, 2020, the surroundings of a solar plant, the collection of dust is an undesired circumstance. Traditional methods of dust removal resulted in increased power loss, particularly in arid regions. Furthermore, the majority of cleaning methods are created with the idea that dust particle adhesion forces can be defeated by applying a harmonic excitation force. The solar panel can sustain damage as a result of this stress. The most often used solar system component for directly converting sun energy to electrical energy is solar panels. The desert was one of the best places to install solar panels because it could produce intense solar radiation even in the presence of dust accumulation. Dust storms, which frequently occurred in these areas, were also important factors that affected the panels' performance. The binding force is dependent on the size of the dust particle, and because different forces occur on different particles as they vibrate, dusting out will eventually cause damage to solar panels. Dust particles differ from place to place throughout the world in terms of size, composition, and form. Moreover, the features and rates of deposition fluctuate significantly throughout locations.

The figure shows the total deformation of the six mode shapes at normal frequency. The red section shows the high frequency level and the blue section shows the minimum frequency level. Here, the minimum frequency is 4Hz and the maximum frequency value is 24.71 Hz. According to Sattar et al. 2022, due to the maximum power's negative temperature coefficient, the unconvertible fraction of incident radiation raises the temperature of the solar panels and reduces their efficiency. Cooling systems are used to reduce the temperature of photovoltaic (PV) panels to address this issue. Instead of perfecting the method to generate a net increase in the generation of electric power, the improvements are concentrated on reducing the efficiency or removing heat from the solar panel. Thus, the analytical model for the cell temperature and absorber design is proposed in this paper. MATLAB was used to analytically analyze the temperature behavior of the solar cells and the heat exchange between the fluid and the PV module's rear surface to build the cooling systems for the hybrid solar panels. The majority of the world's energy demands are met by fossil fuels. One of the most often used solutions to this issue is the use of solar panels to convert solar energy into electrical power. On the other hand, when their surface temperature rises, that is, by 0.45% for every degree over 25 °C, their efficiency falls. The majority of solar panels are intended to operate normally between 25 and 65 °C. In order to regulate the temperature of the solar panels and capture valuable thermal energy, hybrid solar panels have been created, which make use of a cooling system. As the temperature rises, solar panels' efficiency falls. Thus, the objective is to reduce the impact of temperature rises brought on by both ambient temperature and absorbed solar radiation (based on the climatic conditions of Islamabad, Pakistan). The details of the PV module that was examined for analysis. A combination of modeling and mathematics was used to build a cooling mechanism for PV panels.

METHODOLOGY:

The methodology begins with the design phase, focusing on creating a compact, efficient, and sustainable solar-powered yacht by engineering its hull, solar array configuration, and energy storage system, all while aiming to reduce CO? emissions and operational costs. The hull design prioritizes hydrodynamic efficiency to minimize water resistance, using ANSYS CFD simulations to analyze water interaction under varying conditions and optimize the form for reduced drag through features like a fine bow and balanced stern. Recyclable materials such as aluminum alloys and advanced composites are selected for their lightweight and eco-friendly properties, while structural integrity is verified using finite element analysis (FEA) in ANSYS to simulate loads like wave impact. The solar array configuration emphasizes maximum surface area utilization, exploring innovative panel placements—such as collapsible or integrated designs—to track the sun efficiently, and relies on high-efficiency monocrystalline silicon panels aligned to minimize aerodynamic drag. The energy storage system centers on lithium-ion batteries, chosen for their energy density and efficiency, with a design that balances capacity to prevent excess weight or insufficient power. Safety measures ensure integration withstands maritime conditions, including thermal protection and waterproofing. An energy management system (EMS) coordinates power flow between solar panels, batteries, and propulsion systems, regulating charge/discharge cycles and monitoring performance. In the development phase, components selected for durability and high efficiency—solar panels, lithium-ion batteries, PDUs, controllers, electric motors, and monitoring equipment—are integrated mechanically, electrically, and via software. Mechanical integration ensures optimal structural support and weight distribution; electrical integration includes safe, grounded, and insulated wiring; and software integration implements control algorithms and real-time monitoring using microcontrollers and PLCs. The final stage involves rigorous testing and validation: subsystem functional checks, integrated system simulations, and sea trials to assess propulsion, energy use, maneuverability, and environmental performance in real maritime conditions. These efforts ensure the yacht meets its performance criteria while remaining environmentally sustainable, demonstrating the feasibility of an innovative, solar-powered marine vessel.

Virtual Performance Characterization

An interactive process was used for the Yacht design. Three CAD models of the Yacht were designed and a CFD analysis was done for cruise velocity of 10km/hr to find drag on a boat and Power required, Next solar panel was based on power required by the boat and area available for installation.

Design of A Yacht (Design 1)

A Yacht was designed using a Iterative process. Initially a design was chosen with the following characteristics: • Hull Type: Power Catamaran • Length: 11m/36.1ft • Beam: 5.1m/18.6ft • Draft: 0.8m/2.6ft • Displacement: 9.5T (unloaded) • Material of boat: Fiber glass Polyester 4.1.1. CAD Model:

4.1.2 CFD Analysis of Design 1:

The analysis began with domain creation, establishing a primary computational domain for air and water, and a secondary domain focused on the yacht’s wetted surface, allowing for mesh refinement in critical areas. Mesh generation included body sizing with a Body of Influence (BOI) to ensure a finer mesh near the yacht, and a face sizing of 200 mm on the yacht’s surface. The setup used a steady-state analysis with water and air as materials, gravity set at 9.81 m/s², and a Volume of Fluid (VOF) model for multiphase flow. An open wave channel simulated realistic sea conditions. The k-omega SST turbulence model captured hydrodynamic effects, with boundary conditions including a 10 km/h inlet velocity, a free surface level at -0.8 m, and a bottom level at -15 m to allow depth interaction. Mesh motion was enabled, and the yacht’s reference area was input for accurate drag calculations. A coupled, second-order solver was used with drag monitoring, hybrid initialization, and wave conditions set to "wavy." A maximum of 500 iterations per timestep was set to ensure convergence.

4. Solution & CFD Results:

The solution phase began with residual monitoring, which tracked convergence quality during simulation by measuring changes in continuity, momentum, and energy equations—smoothly decreasing residuals indicated proper mesh and boundary setup. Drag coefficient, essential for assessing aerodynamic efficiency, initially fluctuated but stabilized around iteration 50, marking steady-state flow; its final value helped estimate propulsion power.

Post-processing included velocity vectors to analyze flow direction and turbulence around the hull, iso-surfaces to visualize velocity variations and wake behavior, and volume fraction plots showing water-air interaction across the hull. Pressure contours revealed high and low-pressure zones on the surface, aiding design improvements, while velocity contours provided insights into fluid flow dynamics and drag areas.

RESULTS & DESIGN LIMITATIONS:

CFD analysis of the first design yielded a drag force of 9494.1 N, requiring 29.37 kW of propulsion power at a cruise speed of 2.78 m/s. However, with only 20.7 m² of usable roof space for solar panels, and assuming 1000 W/m² irradiance and 22% efficiency, the available power output was just 4.554 kW—insufficient to meet propulsion needs.  This revealed a critical limitation: the excessive drag made it impossible to operate the yacht using available solar power alone. The design’s inefficiency, due to high hydrodynamic resistance, necessitated a redesign focused on reducing drag and optimizing energy use to align with the solar power generation capabilities of the limited panel area.

4.2. Design of YACHT (Design 2):  For the second design, we refined the hull of model one retaining its dimension. The aim was to enhance the aerodynamic performance by improving the hull shape to minimize drag, thus lowering the power requirements. The changes were made to align the yacht’s aerodynamic efficiency with the solar panel system’s Available power within the constraints of the available area for the solar panels.

4.2.1. Cad Model:

4.2.2. CFD Analysis of Yacht Design 2: A setup similar to first design was followed in the CFD Analysis of the Second design. In the CFD analysis of the second yacht design, residuals exhibited expected oscillations during early iterations, gradually stabilizing to acceptable values, indicating convergence and the reliability of the simulation. The drag force initially spiked as anticipated during early computation but settled at 2703.2 N, confirming proper simulation of hydrodynamic behavior. In the post-processing phase, various visualizations were employed to analyze the yacht's performance. Velocity vectors illustrated the initial turbulent flow around the hull, which stabilized over time, revealing areas of efficient flow and potential drag. Volume fraction plots mapped the interaction between air and water around the hull, giving insight into how the yacht behaves at the fluid interface. Pressure contours showed high and low-pressure zones along the yacht's surface, identifying regions contributing to drag or lift, essential for refining hydrodynamic efficiency. Velocity contours detailed flow speed variations around the hull, exposing areas of fast-moving water and potential vortex formation that influence performance. The results of this analysis showed that the drag force of 2703.2 N at a cruise velocity of 2.78 m/s requires 7.514 kW of propulsion power. To meet this, a solar panel area of 34.15 m² would be needed, but the yacht's roof offers only 17.9 m² of usable space. At a standard irradiance of 1000 W/m² and 22% efficiency, the resulting available power output is 3.95 kW, highlighting a shortfall and revealing that the solar input alone cannot currently meet the yacht’s energy demand without further drag reduction or increased solar collection capacity. Below are all respective figures.

LIMITATIONS:

The limitations of Design 2, as revealed by the repeated CFD analysis process, show that despite achieving a reduced drag force of 2703.2 N and a corresponding propulsion power requirement of 7.514 kW, the yacht remains inefficient due to spatial constraints, as the maximum available roof area for solar panel installation increased only slightly to 17.9 m², which, even under ideal conditions of 1000 W/m² solar irradiance and 22% panel efficiency, yields a maximum power output of just 3.95 kW, thereby still falling significantly short of the yacht’s energy demands, and necessitating further design changes—particularly to increase the effective solar panel surface area—in order to meet the required power levels for sustainable operation.

4.3. Design of YACHT (Final Design):

In the final design, significant modifications were implemented to enhance both solar panel capacity and overall performance, including increasing the yacht's length to 13 meters and beam to 6.56 meters, which expanded the available roof area for solar panel installation to 40 m², while maintaining other dimensions and ultimately adopting a power catamaran hull type with a finalized specification of 16 meters in length, 6.56 meters beam, 0.8 meters draft, 9.7-ton displacement (unloaded), and construction using fiberglass polyester, thereby optimizing solar collection potential and aerodynamic efficiency to better address the power demands identified in previous design iterations.

4.3.1CFD Analysis of Final Design

The CFD analysis of the final yacht design began with domain creation, where a primary computational domain was established to encompass both air and water regions. A secondary domain was introduced specifically at the yacht’s interface with water, enabling localized mesh refinement for improved accuracy.

During mesh generation, body sizing was implemented using a Body of Influence (BOI) to achieve finer resolution near critical flow areas, and a face sizing of 200 mm was applied to the yacht’s surface. The BOI was specifically applied within the secondary domain to enhance mesh density around the hull. For the simulation setup, a transient analysis type was selected to capture dynamic interactions between the yacht and surrounding fluids. The multiphase environment included water and air, divided across the domain with gravity activated at 9.81 m/s². The Volume of Fluid (VOF) model was employed to simulate air-water interaction, with an open wave channel to replicate realistic sea conditions. Turbulence was modeled using the k-omega SST model. Boundary conditions included an inlet velocity of 2.78 m/s (10 km/h), a free surface level at -0.8 m, and a bottom domain level at -15 m to ensure depth for flow development. Mesh motion was enabled to simulate dynamic responses, and the ship's reference area was defined to support accurate drag force computation. A coupled solver with second-order accuracy was chosen to enhance convergence, with a drag monitor set up for real-time force tracking. Hybrid initialization was performed, and the “wavy” wave condition was activated to mimic natural ocean dynamics. Time step size was set to 0.01 seconds, with up to 100 iterations per step and 50 total time steps to capture transient behavior.

The solution phase revealed how velocity distributions influenced hydrodynamic performance, helping assess flow pattern changes due to design modifications. Residuals initially fluctuated but eventually stabilized, indicating solution convergence and reliability. The drag force settled at 4158 N after an initial rise, reflecting stable aerodynamic resistance. In post-processing, volume fraction contours illustrated air-water phase interaction and hull contact efficiency. Velocity vectors revealed flow direction and magnitude, highlighting zones of acceleration or stagnation around the hull, critical for refining hydrodynamic and aerodynamic design. Volume fraction visuals provided phase distribution clarity, aiding in evaluating interface behavior and simulation accuracy. Pressure contours showed variation from high pressure at the bow and sides to low pressure near the stern, essential for understanding forces on the hull. Velocity contours mapped water motion around the hull and wake regions, identifying high-speed zones at leading edges and lower-speed zones in the wake, guiding further optimization for resistance reduction.

RESULTS:

The CFD analysis of the final yacht design determined a drag force of 4158.8 N at a cruising velocity of 10 km/h (2.78 m/s). The corresponding power requirement to overcome this drag was calculated using the formula Power = Drag × Velocity, resulting in a required power of 11.56 kW. To meet this power demand, a solar panel system was designed. Although the yacht's roof provides 40 m² of space, the solar panel can extend beyond this area to a total of 55 m². Using a solar irradiance of 1000 W/m² and a panel efficiency of 22%, the expected power output from the solar array is 12.1 kW, calculated using the formula Power Output = Area × Irradiance × Efficiency. This confirms that the solar panel system can supply enough energy to maintain cruising speed while also leaving additional power available for other onboard needs.

5. Final Design of the YACHT:

The available power generated by the solar panel system exceeds the yacht’s cruising requirements at a velocity of 10 km/h, providing sufficient surplus energy for other onboard systems and ensuring efficient operation while overcoming hydrodynamic drag. The integration of the solar panel system plays a vital role in enhancing the energy efficiency and sustainability of the final design. To accommodate the upgraded energy system, the yacht’s dimensions were increased to 13 meters in length and 6.56 meters in width, allowing for a larger solar panel installation of approximately 40 m² on the deck. The system was designed to meet a cruising energy requirement of 11.56 kW, while the total solar panel output reaches 12.1 kW, comfortably exceeding operational demands and supporting moderately heavy onboard usage. Beyond meeting performance needs, the incorporation of solar technology significantly reduces reliance on fossil fuels, aligning the design with eco-sustainable practices by promoting renewable energy use. The final CAD model reflects these improvements and the integration of the solar panel system into the yacht's structure.

5.1 Matlab Simulation:

The MATLAB/Simulink model offers a comprehensive simulation of a photovoltaic (PV) system's performance, allowing for a deep understanding of how various parameters such as irradiance and temperature influence power output without delving into complex design details like meshing or material layer specifics. The PV system in the simulation has a rated power of 12,100 W, with key specifications including a maximum power voltage (Vmp) of 26.4 V, maximum power current (Imp) of 458.33 A, open-circuit voltage (Voc) of 32.9 V, and short-circuit current (Isc) of 367.78 A. The system is modeled with 54 cells in series and 61 in parallel, with an internal resistance of 3.48 ohms. These parameters are essential for simulating the behavior of the PV system under different environmental conditions, particularly irradiance and temperature, and for deriving the output voltage and current.

The simulation includes graphical representations of key performance characteristics such as current and power as a function of voltage at different irradiance levels. Specifically, the I-V and P-V curves are plotted for irradiance levels of 1000, 500, and 100 W/m², providing insights into how these parameters change with varying levels of sunlight. In these graphs, as voltage increases, both current and power rise, reflecting the increased energy production capacity of the system. However, after reaching a peak, power begins to decrease sharply, which is a crucial behavior to understand as it determines the efficiency of the solar module under different irradiance conditions. The graphs visually demonstrate the maximum power point (MPP) where energy output is optimized, after which power declines due to the nonlinear behavior of PV cells. These observations are important for understanding the system’s performance in real-world conditions where sunlight is not constant and can fluctuate throughout the day.

Additionally, the simulation explores the effect of temperature on the PV system's performance under constant irradiance of 1000 W/m². As temperature increases, the output voltage of the panel decreases, while the current slightly increases, which results in a net decrease in power output. This behavior emphasizes the need for optimizing PV systems to maintain high efficiency even under varying environmental conditions, such as temperature fluctuations that can occur throughout the day. These temperature-dependent changes in power output are illustrated in graphs showing the current and power as a function of voltage at different temperatures, allowing for a better understanding of how temperature impacts the performance of the solar panel. The thermal analysis in the simulation also provides insights into how different layers in the solar panel behave under varying conditions. However, it is important to note that while material layers like ETFE, EVA, and monocrystalline silicon cells are described in the physical design process, such as those used in SolidWorks or ANSYS models, the MATLAB simulation focuses solely on the electrical behavior of the PV system. The performance data and thermal characteristics derived from this simulation are used to enhance the efficiency of the system and ensure that the solar panel operates optimally despite environmental challenges like temperature changes and varying sunlight. By presenting these graphs and results from the MATLAB/Simulink simulation, one can effectively demonstrate the behavior of a photovoltaic system in real-world conditions without needing to present complex design details such as material layers or meshing processes typically involved in CAD or thermal modeling. These graphs, including those showing current and power as a function of voltage at different irradiances and temperatures, form the core of the analysis, providing clear visual evidence of the system’s performance under various operating conditions. The results are not only useful for understanding the dynamic relationship between environmental factors and energy production but also crucial for making informed decisions when designing and optimizing photovoltaic systems for real-world applications.

5.3 Thermal Analysis: Meshing, Setup, Results

The meshing process in the simulation involves discretizing the CAD model into small elements, with an edge sizing of 0.3 meters to balance computational efficiency and simulation accuracy. This edge sizing defines the size of the elements along the edges of the model, crucial for fine-tuning the mesh quality. A hexahedral mesh was used, which divides the model into six-faced elements, offering a structured approach that is often preferred for simulation due to its regularity and efficiency. The mesh quality was verified through various metrics to ensure the most accurate representation for simulation purposes. In the setup phase, boundary conditions, loads, and simulation parameters were defined to represent the solar panel's real operational environment. This setup ensures that the simulation accurately predicts thermal behavior under different environmental scenarios. In Ansys Mechanical, boundary conditions were specified, which included heat flux, radiation settings, convection, and ambient temperature. Heat flux is essential for modeling how sunlight is absorbed by the solar panel, while radiation settings consider the radiative heat transfer, particularly the emission of heat from the panel’s surface. Convection conditions model the heat transfer between the panel and the surrounding air, factoring in wind and ambient temperatures, which play a role in the panel's cooling process. The ambient temperature serves as the base for all heat transfer calculations, varying depending on the weather conditions simulated.