Ali Karimi
Ali Karimi
Ali Karimi

About

Hello, and thank you for visiting!

I am Ali Karimi, a Ph.D. student in industrial engineering at the University of Naples Federico II, Italy, and a proud member of the Apper Lab research group, where I work under the guidance of Professor Alfredo Gimelli. Currently, I am a guest researcher at the University of Stavanger in the Department of Energy and Petroleum Engineering, under the supervision of Professor Mohsen Assadi.



My current research focuses on the following areas:

  • Hybrid Energy Systems: I'm deeply involved in the development of an integrated energy system that combines a micro gas turbine, electrolyzer, battery energy storage, and photovoltaic panels. This intelligent system has the capability to make real-time decisions based on various conditions. It determines which energy source to use, when to operate at full power, and when to conserve energy. This approach aims to maximize efficiency and sustainability in energy generation and consumption..
  • Digital Twins: Throughout my academic journey, I've been focused on creating digital twins for a variety of equipment. My experience includes working with Organic Rankine Cycle (ORC) plants, Combined Heat and Power (CHP) units powered by internal combustion engines, and currently, micro gas turbines and electrolyzers. These digital twins serve as virtual replicas, enabling in-depth analysis, simulation, and optimization of equipment performance.
  • Optimization: Optimizing integrated energy systems is a continuous challenge, and it's essential to optimize both the operation and equipment size for efficiency and cost-effectiveness. In my recent work on Combined Cooling, Heating, and Power (CCHP) systems, I focused on optimizing the size of the battery and determining the optimal number of internal combustion engines (ICE) to run, all while considering fossil primary energy savings. This research contributes to the development of highly efficient energy systems.
  • Artificial Intelligence in the Energy Sector: Leveraging artificial intelligence (AI) is a game-changer in energy system simulations. I've been actively utilizing deep neural networks (DNN) to monitor and model the behavior of the T100 micro gas turbine (MGT) within integrated systems. AI-based simulations are significantly faster than physics-based models, making them ideal for predictive analytics and control strategies. My research aims to enable the operation of a micro gas turbine with 100 percent hydrogen (H2), pushing the boundaries of clean energy utilization.

These research areas drive my passion for creating innovative solutions that contribute to a more sustainable and efficient energy landscape.