User:Subigya Khanal

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I am Subigya Khanal, an Electrical Engineering graduate from the Institute of Engineering, Tribhuvan University, Nepal. I am currently working as a STEM instructor, where I teach school-level students robotics and electronics.

My work involves hands-on teaching with sensors, microcontrollers, and basic automation systems. This experience has strengthened my ability to explain technical concepts in simple ways and build practical engineering solutions.

I am passionate about applying engineering knowledge to solve real-world problems, especially in sustainable energy and open-source technologies.

• Renewable Energy Systems (Solar, Hybrid Systems)
• Smart Grids and Power System Stability
• Electric Vehicle Infrastructure
• Open-source hardware for education and sustainability

For my undergraduate final year project, I developed an Artificial Neural Network (ANN) based Unified Power Flow Controller (UPFC) to improve power flow control and voltage profile management in transmission systems.

• Designed and trained an ANN model to replace conventional controllers in a UPFC system
• Improved voltage stability and active/reactive power flow across transmission lines
• Implemented and simulated the full system in MATLAB/Simulink
• Demonstrated that the ANN-based controller outperformed conventional PI controllers in response time and accuracy
• This work connects directly to machine learning applications in energy systems, including solar PV planning and EV charging optimization

• Teaching school-level students robotics, electronics, and basic programming
• Working hands-on with sensors (ultrasonic, IR, etc.) and microcontrollers (Arduino, ESP32)
• Guiding students in building real-world mini projects and automation systems
• Developing practical understanding of hardware systems and troubleshooting
• Simplifying complex engineering concepts into easy-to-understand ideas

This experience has strengthened my ability to connect theory with practical implementation, which I believe is essential for developing real-world open-source engineering solutions.

I am strongly interested in the Free Appropriate Sustainability Technology research group because of its focus on developing open-source, low-cost, and practical technologies that solve real-world problems.

I am particularly inspired by the lab's work in solar photovoltaic systems, open source hardware, and the recent research on machine learning models for electric vehicle charging and national-level solar PV planning. My background in ANN-based power system optimization connects directly to these research directions.

Through my combination of theoretical knowledge in power systems and hands-on experience with embedded hardware, I am motivated to contribute to accessible and open-source energy solutions that can make a real difference, especially in developing regions like Nepal.

Through my teaching experience, I have developed a strong interest in open-source hardware and hands-on learning. I believe that engineering solutions should be accessible, replicable, and adaptable by others — which is exactly the philosophy behind Appropedia and the FAST Lab.

I am particularly interested in creating low-cost and open-source systems that can be used both for education and real-world applications in energy and sustainability.

• MATLAB / Simulink
• Arduino / ESP32
• Sensors and Embedded Systems
• Power Systems Analysis
• Artificial Neural Networks (ANN)
• Circuit Design and Prototyping
• Basic Python

I aim to pursue graduate research in sustainable energy systems, specifically in solar photovoltaics, open-source hardware, and intelligent control systems. I want to contribute to technologies that improve energy access in developing regions and support the global transition to clean energy.

• B.E. Electrical Engineering — Institute of Engineering, Tribhuvan University, Nepal

• Email: subigyakhanal345@gmail.com