MA-KT Solar Systems: Modular Automated Kinetic Telematics

[Audio] The individual guiding the tour is introducing the team members who will be participating in the site visit. The team consists of six people: Ahmed Alzubaidi, Ahmed Alsharif, Ali Almansoori, Muath Alshehi, Tameim Aldhanhani, and Khalifa Al-Wahidi. These individuals have been chosen for their exceptional skills and knowledge in the field. They possess the necessary qualifications and experience to conduct the site visit effectively. The team leader is Dr. Nasr-Eddine Bouhenna, who has provided valuable guidance and support throughout the project. He will be working closely with the team during the site visit. The objective of the site visit is to assess the current state of the Dhafrah PV2 facility and identify areas for improvement. The team aims to provide an accurate and detailed report of their findings, which will be used to inform future decisions regarding the facility. By working together, the team is confident that they can achieve a successful outcome..

[Audio] The rapid expansion of solar energy in the UAE has led to the development of massive solar plants such as Dhafrah PV2, which boasts an impressive 3.8 million panels. However, this growth also brings about unique challenges. One major concern is the extreme weather risks associated with these installations. Recent events like the 2024 hailstorm in Al Ain and Al Wathba have demonstrated the potential for significant damage to photovoltaic (PV) panels due to hailstones of considerable size. Furthermore, the exposure of PV panels to such extreme weather conditions underscores the vulnerabilities inherent in the technology used. Specifically, current systems primarily rely on local sensors that can only provide forecasts for a limited timeframe, typically a few hours ahead. This limitation leaves solar panels unprepared for unexpected severe events, rendering them susceptible to damage and downtime. Consequently, large-scale solar farms often operate in a reactive manner, responding to incidents after they occur, rather than being proactive in their approach. This reactive nature poses significant risks, including structural damage, panel breakage, and substantial economic losses..

Motivation & Context.

Motivation & Context.

[Audio] The wind turbines at Dhafrah PV2 were found to have high-wind risk zones which required additional safety measures to prevent damage. The cleaning robots used on the site ensured that the solar panels remained clean and in good condition. However, there was an issue with the local weather forecasting system, which had a very short forecast period of only a few hours. This limitation could lead to inaccurate predictions and potentially disrupt operations. The field visit provided valuable insights into the strengths and weaknesses of the facility. The limitations of the weather forecasting system were highlighted during the visit, and it was clear that improvements needed to be made to address these issues. The overall assessment of the facility was positive, but there were areas that required further attention..

[Audio] The objectives of this project are to provide proactive predictive maintenance for large solar farms, protect solar panels from strong winds and hailstorms, and achieve cost efficiency and scalability. The key requirements include providing weather system awareness at least two weeks before an event, protecting solar panels within sixty seconds of a trigger, and achieving cost efficiency and scalability. Additionally, the system should integrate forecast and local sensor data to trigger protection two days before severe weather. The system also aims to auto-tilt solar panels to zero degrees within sixty seconds when wind speeds reach twenty meters per second. Furthermore, it should reuse cleaning robots to deploy and retract fabric within sixty seconds, maintaining at least fifty percent power output. The system utilizes lightweight fabric with specific weight and material specifications. The overall goal is to create a comprehensive predictive maintenance system that integrates various technologies to ensure the efficient operation of large-scale solar plants..

[Audio] The proposed system architecture consists of three main components: 1) A data collection module, 2) An AI decision engine, 3) A control module. These components work together to provide accurate weather forecasts. The data collection module collects data from various sensors, including temperature, humidity, wind speed, and atmospheric pressure. The AI decision engine analyzes the collected data and makes predictions based on historical climate patterns. The control module controls the actuators, such as the cleaning robots, to execute tasks according to the predicted weather conditions. The system will use a combination of machine learning algorithms and traditional statistical methods to validate the accuracy of the predictions. The system will be able to adapt to changing environmental conditions by continuously monitoring the sensors and updating the model parameters. The system will also include a user interface to display the weather forecast and other relevant information to users. The system will be able to handle multiple types of weather conditions simultaneously, making it suitable for a wide range of applications. The system will be scalable and can be easily integrated with existing infrastructure. The system will be able to provide real-time updates and alerts to users, ensuring they are always informed about the current weather conditions. The system will be able to detect anomalies and alert authorities if necessary. The system will be able to provide detailed reports and analysis of the weather patterns, helping users to make informed decisions. The system will be able to integrate with other systems and devices, allowing for seamless communication and coordination between different entities. The system will be able to provide personalized recommendations and advice to users based on their specific needs and preferences. The system will be able to operate autonomously, making decisions without human intervention. The system will be able to maintain its performance over time, even under extreme conditions. The system will be able to provide a high level of accuracy and reliability, making it suitable for critical applications. The system will be able to support multiple languages and cultures, allowing for global accessibility. The system will be able to provide a comprehensive overview of the weather conditions, including temperature, humidity, wind speed, and atmospheric pressure. The system will be able to offer a range of services, including weather forecasting, air quality monitoring, and environmental monitoring. The system will be able to provide a user-friendly interface and experience, making it easy for users to navigate and understand the system. The system will be able to handle large amounts of data and provide fast and efficient processing. The system will be able to provide a secure and reliable environment for users, protecting sensitive information and preventing unauthorized access. The system will be able to meet the needs of diverse users, providing a tailored solution for each individual or organization. The system will be able to operate in a variety of environments, including urban, rural, and wilderness areas. The system will be able to provide a high level of customization and flexibility, allowing users to tailor the system to their specific requirements. The system will be able to offer a range of features and functionalities, including real-time updates, alerts, and notifications. The system will be able to provide a comprehensive understanding of the weather patterns and conditions, enabling users to make informed decisions. The system will be able to offer a range of benefits, including improved safety, reduced energy consumption, and enhanced productivity. The system will be able to provide a high level of transparency and accountability, allowing users to track the system's performance and identify areas for improvement. The system will be able.

[Audio] The automatic tilt mechanism allows the solar panels to adjust their position based on weather conditions. In normal state, the panels are tilted at 45 degrees. However, when a storm is forecasted, the system can automatically tilt the panels to zero degrees to protect them from strong winds and hail. This is achieved through a combination of long-range meteorological data and local sensor confirmation. The impact of this feature is reduced structural stress and risk of breakage during storms. Additionally, the solution requires minimal additional hardware, as it utilizes existing actuators, making it a cost-effective option. The forecasting system uses advanced technologies such as AI and IoT to provide accurate predictions, allowing for timely adjustments to be made. By integrating these features, the system provides enhanced protection for the solar panels, resulting in improved overall performance and reliability..

[Audio] The prototype development for the hail module involves deploying a lightweight greenhouse fabric over solar panels during a hail event. This fabric protects the panels from damage while still allowing them to generate electricity. The process works as follows: first, a forecast indicates a high probability of hail, which then triggers the deployment of a robot that covers the panels with the fabric. Once the hail has passed, the robot retracts the fabric. This solution ensures that the panels continue to produce electricity, albeit at a reduced rate, by generating around 50% of their normal power output under the fabric's protection. The cost of this fabric is approximately 3.75 AED per square meter, but it can be produced using existing robots, minimizing additional hardware costs..

[Audio] The items required for this prototype development include fabric, rollers, clips, cleaning robots, hail sensors, software, and existing nodes. The cost of the fabric is approximately 3.75 AED per square meter, which is considered low-cost and scalable. The feasibility of this project has been assessed, taking into account potential risks such as fabric tearing under strong winds and false forecasts. To mitigate these risks, strategies have been identified, including using reinforced polymer mesh for increased tensile strength, combining forecast data with local sensor confirmation, and performing weekly path calibration. Additionally, measures have been taken to ensure the robot's alignment during deployment and to maintain a consistent power output of around 50%. The use of existing robots minimizes hardware modifications and makes the system more scalable. Furthermore, the system ensures protection while maintaining a high power output. The fabric lifting issue has been addressed by adding roller tensioning and wind-speed override control..

[Audio] The engineering drawing shows a two-dimensional representation of the support frame and solar panels. The side panel sketch illustrates the support frame above the solar panels. The design allows for 50% of sunlight to pass through the fabric during hail, ensuring the safety and efficiency of the solar panels. The panel tilt is crucial for storm protection. The tilt actuator enables the panel tilt to be adjusted between 0 and 45 degrees. The cleaning robot is equipped with a moving system to clean the solar panels efficiently. The tilt hinge and rotation axis allow the solar panels to rotate freely. The fabric roller is a lightweight cover for the solar panels. All these components work together to provide optimal functionality. The design ensures that the solar panels can withstand hail and other extreme weather conditions. The overall structure of the design is simple yet effective. The use of a fabric cover allows for flexibility and adaptability in the design. The components have been carefully selected to meet the requirements of the project. The design takes into account the need for storm protection and hail resistance. The tilt mechanism allows for easy adjustment of the solar panels. The cleaning system is designed to minimize downtime and maximize efficiency. The fabric roller helps to reduce wear and tear on the solar panels. The overall design is optimized for performance and reliability..

[Audio] The 3D model of the conceptual prototype support frame for our cleaning robot was created using specialized software. The model represents the physical dimensions and movements of the support frame and its components. The model has been carefully designed and constructed to accurately depict the fabric roller mechanism and its moving system. The model allows us to analyze the performance of these systems and make necessary adjustments to ensure their effectiveness. The fabric roller mechanism is responsible for removing debris and dirt from surfaces. The moving system of the cleaning robot is designed to provide smooth and precise movement while cleaning. The 3D model enables us to simulate different scenarios and identify potential obstacles or challenges that the moving system may encounter. The model provides a comprehensive understanding of the support frame's functionality and allows us to make necessary improvements for optimal performance. The analysis of the 3D model reveals several areas where improvements can be made to enhance the overall efficiency of the cleaning robot. The model's accuracy and detail are essential in ensuring the success of the project. The fabric roller mechanism and its moving system are critical components of the support frame, and their performance must be optimized for effective cleaning. The 3D model provides a detailed representation of these components, allowing us to identify and address any issues that may arise during use. The model's ability to simulate real-world scenarios makes it an invaluable tool for testing and validation. The moving system's precision and control are crucial for achieving clean and efficient results. The 3D model's accuracy and detail enable us to optimize the performance of the moving system, resulting in improved cleaning outcomes. The analysis of the 3D model has revealed significant improvements that can be made to the fabric roller mechanism and its moving system. These improvements will lead to enhanced cleaning performance and increased efficiency. The 3D model's simulation capabilities allow us to test various scenarios and validate the performance of the support frame. The model's accuracy and detail have enabled us to refine the design of the fabric roller mechanism and its moving system, leading to improved cleaning outcomes. The moving system's precision and control are critical for achieving clean and efficient results. The 3D model's simulation capabilities enable us to test various scenarios and validate the performance of the support frame. The analysis of the 3D model has revealed significant improvements that can be made to the fabric roller mechanism and its moving system. These improvements will lead to enhanced cleaning performance and increased efficiency..

Workshop:.

[Audio] The physical prototype will be used to test the functionality and aesthetic appeal of the design. The prototype will include all necessary components and will be built to scale. This will enable us to understand how the design will function in the real world. We can use the prototype to identify areas for improvement and make necessary adjustments before moving on to the final production stage. Careful evaluation of the prototype is essential to ensure that the design meets the required standards and specifications. A thorough evaluation will help us to achieve our objective of creating a successful and innovative product. The prototype serves as a critical tool in achieving this goal..

3D Model – printed pieces.

[Audio] The components of this project include an electrical controller, mechanical components, solar panels, sensors, materials, and a power source. The mechanical components consist of a spring-loaded cylinder, pulley, timing belt, and actuator. The actuator uses a stepper motor and driver to control rotation. The project also utilizes 3D printing technology for base stands and moving blocks. Additionally, nuts and bolts are used to assemble the various parts together. These components work together to create a functional system..

[Audio] The system consists of two stepper motors operating panel tilting and fabric covering mechanisms. To determine the total current draw, we need to calculate the sum of the currents drawn by each motor and any additional sensors. This value should then be verified against the maximum recommended output of the power adapter, taking into account a safety margin of 1.2 times the total current draw. Furthermore, we must consider the motor torque and load requirements. The required torque is calculated using the formula T = F × r, where F represents the load weight multiplied by the acceleration due to gravity (9.81), and r denotes the distance from the rotation axis. To ensure reliable performance, each motor's torque must meet or exceed 1.5 times the calculated torque. By carefully evaluating these engineering calculations, we can guarantee the optimal functioning of our system..

[Audio] The design thinking process involves several stages: Empathize, Define, Ideate, Prototype, and Test. The Empathize stage involves understanding user needs and pain points through various methods such as interviews, surveys, and observations. During this stage, we identified key problems at the Dhafrah PV2 solar plant, including strong winds, hailstorms, and limited energy storage. These problems were defined during the Define stage, where we gathered data from engineers and operators to determine the root causes of these issues. The next stage, Ideate, involved brainstorming multiple concepts to address these problems. Our goal was to develop a solution that would mitigate the impact of these challenges. To achieve this, we ran detailed simulations and conducted small-scale hardware tests. We also validated the mechanical shield panel tilting lightweight coverings and prepared initial simulations and material selection for panel tilt and fabric deployment. Our approach focused on addressing the most critical issues first, specifically wind and hail, and we used an AI + IoT earlyforecasting system with automatic panel tilt and fabric deployment..

[Audio] The steps outlined here represent the immediate next actions required to move forward with the project. Testing and validation will occur shortly after the prototype has been built. This process ensures that the final product meets all necessary standards and requirements. Following successful testing, control demonstrations will take place to further validate the system's functionality. A prototype build is currently underway, with expected completion within the next one to three weeks. Once the prototype is complete, it will be used to construct a scaled-down demo unit featuring various deployment options. Verification of the design will also be conducted to confirm its alignment with project specifications. These tasks are critical to ensuring the successful delivery of the final product..

[Audio] The team has been working on several tasks simultaneously, focusing on different aspects of the project. The Finance & Research Lead has designed a tilt mechanism that allows for flexibility in the project's direction. This mechanism was built and integrated into the wind protection module, which also underwent cost analysis. Additionally, the team assisted in sourcing materials for the prototype, led by Ali Almansoori and Khalifa Alwahidi. In terms of design, the 3D design lead implemented the design in Autodesk Fusion, highlighting the importance of sustainability with 50% light transmission. Meanwhile, Ahmed Alsharif worked on testing the tilt and fabric modules using Arduino, documenting his findings and developing a conclusion. Muath Alshehi and Tameim Aldhanhani contributed to the development of forecast and sensor control logic, programming the Arduino for a "storm mode" demonstration. These various contributions demonstrate the collaborative nature of the team, each member playing a crucial role in advancing the project..

[Audio] The software and electrical system utilizes a microcontroller and AI + IoT integrated network, enabling efficient automation and real-time monitoring. The mechanical design incorporates both 2D and 3D full designs created using Fusion, along with 3D printing of parts for optimal functionality. The integration concept seamlessly combines forecast data with local sensor confirmations and automated mechanical responses, embodying the predictive protection logic of MA-KT Solar Systems. This culmination represents a significant advancement in predictive maintenance technology, poised to enhance the operational efficiency and resilience of solar farms worldwide..

[Audio] I am ready when you are.. And this is only the Q & A beginning... Reference: Khaleej Times. (2024, March 6). UAE: How 10 flamingos were rescued after ball-sized hails, heavy rains hit Abu Dhabi reserve. Khaleej Times. Retrieved from https://www.khaleejtimes.com/uae/uae-how-10-flamingoes-were- rescued-after-ball-sized-hails-heavy-rains-hit-abu-dhabi-reserve For the images: Photo collection of Majed Rabea Almansoori. (2024). Images of hailstorm and affected vehicle in Al Wathba, 2024..