Dr. Rabin Dhakal is a senior researcher at Electric Power Research Institute (EPRI). He works in the Solar Generation Program. His area of research focus on applications of modeling and data analytics of photovoltaic systems for performance, maintenance, and reliability analysis and optimization.
Prior to joining EPRI, he worked for four years in the renewable energy industry on micro-hydro, solar, and wind energy-based projects. In this role, he conducted a detailed feasibility study of implementation of renewable energy projects at different site locations in Nepal and South Africa. He is highly motivated with a real passion for implementing research findings through commercialization. This was demonstrated during his early career, which led to him becoming the technical leader of his research team, developing the use of ultra-low head micro-hydro power plants.
After working in renewable energy-based projects in Nepal and South Africa, He accepted a Ph.D. position at Texas Tech University, where he worked on prediction of wind and solar power for different time horizons using various classical time series and machine learning algorithms. He has developed a novel hybrid prediction model based on existing classical forecasting techniques and deep learning methods.
He has a BSc from Tribhuvan University, Nepal and MSc, and Ph.D. degrees in Mechanical Engineering from Texas Tech University. His education and research focus on fluid machines and renewable energy resource assessment.
Area of Expertise:
• Renewable Energy
• Resource Assessment
• Data Analytics
• Modelling and Optimization
Prior to joining EPRI, he worked for four years in the renewable energy industry on micro-hydro, solar, and wind energy-based projects. In this role, he conducted a detailed feasibility study of implementation of renewable energy projects at different site locations in Nepal and South Africa. He is highly motivated with a real passion for implementing research findings through commercialization. This was demonstrated during his early career, which led to him becoming the technical leader of his research team, developing the use of ultra-low head micro-hydro power plants.
After working in renewable energy-based projects in Nepal and South Africa, He accepted a Ph.D. position at Texas Tech University, where he worked on prediction of wind and solar power for different time horizons using various classical time series and machine learning algorithms. He has developed a novel hybrid prediction model based on existing classical forecasting techniques and deep learning methods.
He has a BSc from Tribhuvan University, Nepal and MSc, and Ph.D. degrees in Mechanical Engineering from Texas Tech University. His education and research focus on fluid machines and renewable energy resource assessment.
Area of Expertise:
• Renewable Energy
• Resource Assessment
• Data Analytics
• Modelling and Optimization
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