Researchers from the University of Tehran have contributed three key chapters to Physics Informed Machine Learning for Integrated Energy Systems Management, published by Elsevier in the Netherlands.

Why it matters: 

The work showcases Iran’s role in advancing global research on energy storage, renewable integration, and system reliability — all essential for building sustainable energy infrastructure.

The book blends physical fundamentals with practical tools for designing, planning, and operating integrated energy systems — a field critical to the energy transition.

 

Zoom in:

  • Chapter 1 – By Maryam Parvin, Hamid Sarafha, and Prof. Hossein Yousefi, outlines the framework and core features of integrated energy systems, including components, storage systems, and modeling methods.
     
  • Chapter 2 – By Mohammad Hassan Ghodousi Nejad, Setareh Peyro, and Prof. Hossein Yousefi, highlights multi criteria decision making and advanced mathematical models for optimizing energy planning under uncertainty.
     
  • Chapter 3 – By Kianoosh Choubineh, Mohammad Hassan Ghodousi Nejad, Prof. Hossein Yousefi, and Prof. Moein Moeini, examines the role of energy storage in enhancing system flexibility and grid reliability.

 

The big picture:

The chapters draw from both academic expertise and applied analysis, offering policymakers and engineers practical paths to improve energy networks worldwide.

 

Go deeper:

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seyed mohammad kazemi - ahmad shirzadian