The PyPSA Handbook

Integrated Power System Analysis and Renewable Energy Modeling

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Éditeur :

Elsevier


Paru le : 2025-12-02



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Description
The PyPSA Handbook: Integrated Power System Analysis and Renewable Energy Modeling is a comprehensive guide to the landmark open-source platform for modeling modern energy systems. Starting from core concepts in energy system analysis, the book builds a clear theoretical foundation before progressing to advanced topics such as renewable integration, storage, grid expansion, system stability, and future developments. Designed for both newcomers and experienced users, it features layered examples, hands-on exercises, and real-world case studies. This book is an indispensable resource for students, researchers, and energy professionals. - Progresses from foundational principles to advanced modeling techniques - Includes real-world case studies, exercises, and ready-to-run PyPSA code - Presents open-source energy modelling in accessible, practical, and reproducible manner
Pages
285 pages
Collection
n.c
Parution
2025-12-02
Marque
Elsevier
EAN papier
9780443266317
EAN EPUB SANS DRM
9780443266324

Prix
185,67 €

Dr. Neeraj Dhanraj Bokde is a Lead Researcher at the Technology Innovation Institute (TII), Abu Dhabi, with over 12 years of interdisciplinary experience in renewable energy, data science, and AI. He has held academic positions at Aarhus University in Denmark and contributed to applied research at DEWA and VNIT Nagpur. Dr. Bokde develops open-source tools in R and Python for data analysis, forecasting, and optimization. His work supports the energy transition through transparent modeling, advanced analytics, and integrated planning strategies. He has published extensively in the fields of energy modeling, renewable integration, and data-driven decision support.Dr. Carlo Fanara is Executive Director of the Energy Modelling team at the Technology Innovation Institute (TII), Abu Dhabi. He has extensive experience spanning nuclear and plasma physics, materials science, and machine learning, and has held academic and industrial roles across Europe. He holds a Ph.D. in plasma physics and has led research in energy beams, diagnostics systems, and data-driven modeling. His current work focuses on advancing energy systems analysis through high-performance computing, algorithm design, and applied data science. He is member of the IEEE Nuclear and Plasma Physics division and ordinary member of the ACM.

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