The PyPSA Handbook: Integrated Power System Analysis and Renewable Energy Modeling’ is a unique guide to the landmark open-source program for modelling complex modern energy systems and their challenges. Beginning with fundamental concepts of the program and energy systems analysis, this book clearly outlines theoretical background and provides a firm foundation in PyPSA methodology. It moves steadily towards complex system modelling and analysis suitable even for the experienced user, including renewable integration, energy storage challenges, grid expansion planning, stability issues, and future developments. Including layered examples and exercises appropriate for both foundational and advanced practitioners, The PyPSA Handbook is an indispensable new resource for students, academics, and professionals working on energy systems.
Table of Contents
1. Introduction to Power Systems and PyPSA2. Getting Started with PyPSA
3. Modeling Components in PyPSA
4. Advanced Modeling Techniques
5. Decarbonization and Renewable Integration
6. Microgrids and Distributed Energy Resources (DERs)
7. Transmission Planning and Expansion
8. Reliability and Resilience
9. Integrating PyPSA with Other Tools
10. Future Trends and Challenges
Authors
Neeraj Dhanraj Bokde Assistant Professor, Centre for Quantitative Genetics and Genomics, Aarhus University (Denmark); Senior Researcher, Renewable and Sustainable Energy Research Centre, Technology Innovation Institute, United Arab Emirates.Neeraj Dhanraj Bokde is currently an Assistant Professor in the Centre for Quantitative Genetics and Genomics at Aarhus University (Denmark), and a Senior Researcher in the Renewable and Sustainable Energy Research Centre at the Technology Innovation Institute (United Arab Emirates).
Carlo Fanara Senior Physicist, Data Scientist, Lead of Energy Modeling, Directed Energy Research Centre, Technology Innovation Institute, United Arab Emirates. Carlo Fanara is a Senior Physicist, Data Scientist, and the Lead of Energy Modeling at the Directed Energy Research Centre of the Technology Innovation Institute, United Arab Emirates. He has a decade of research experience in machine learning, following two decades specializing in physics. He participated in the construction and operation of the interrogation machine, led data campaigns and data analysis both in situ and abroad, and took responsibility for the validation of the machine using machine learning algorithms for discrimination and identification of substances. He has held positions as senior data scientist and head of research at companies in Belgium and France working on data from genetic programming to time series.
