Comprehensive overview of blockchain applications in smart power systems. This chapter covers technical foundations, use cases, and implementation strategies for modern energy grids and distributed energy markets, exploring the potential of distributed ledger technology in revolutionizing energy systems.

Comprehensive technology stack for developing smart contracts in energy applications, enabling decentralized energy markets and blockchain-based transactions. This work provides a practical framework for implementing smart energy systems and peer-to-peer energy trading platforms.

Role of smart contracts in enabling the digital green transition, facilitating decentralized energy markets and sustainable energy systems. This work demonstrates how blockchain technology can support the transition to renewable energy and sustainable power systems.

Comprehensive review of simulation models addressing CO2 pollution reduction in transportation, focusing on electrification strategies and sustainable mobility solutions. This work provides insights for designing effective policies and technologies for sustainable transportation systems.

Advanced multi-agent system for peer-to-peer energy trading with postpaid payment mechanisms. This framework enables efficient energy exchange in smart grids through coordinated negotiations, facilitating decentralized energy markets and sustainable energy distribution.

Comparison between dynamic and static models for railway electrification systems, providing insights for infrastructure planning and operational optimization. This work bridges the gap between theoretical modeling and practical railway system design.

Novel negotiation framework for electric vehicle charging in congested distribution networks. This research addresses grid stability and efficient energy management through multi-agent systems, enabling smart coordination of electric vehicle charging in urban environments.

Advanced modeling approach for DC railway systems using nonlinear switched models for accurate voltage estimation and power flow analysis in complex railway networks. This methodology enables precise simulation of railway electrification infrastructure.

Development of a comprehensive computer platform for visualization and simulation of vehicular DC distribution systems. This work enables advanced analysis of electrical vehicle networks, supporting the design and optimization of electric vehicle power systems.

Analysis of hybrid energy storage systems for railway applications, addressing regenerative braking and energy management in railway electrification systems. This work contributes to improving energy efficiency and sustainability in modern railway transportation.

Comprehensive model and solver for high-speed railway traction systems at 2×25 kV AC. This research enables extensive network simulations and analysis of railway electrification infrastructure, supporting the design and optimization of modern high-speed railway systems.

Comparative analysis of energy storage strategies in DC railway systems, evaluating off-board and on-board solutions against reversible substation technologies. This research provides valuable insights for optimizing railway energy management systems.

Advanced simulation framework for DC railway systems incorporating power electronic converters and energy storage devices. This work enables detailed analysis of railway electrification systems with renewable energy integration, addressing the challenges of modern sustainable railway infrastructure.

This paper presents a novel algorithm for solving meshed DC railway networks with nonlinear load characteristics. The work addresses voltage constraints and power flow analysis in complex traction systems, providing an efficient solution for railway electrification infrastructure analysis and optimization.

Analysis of sensorless control techniques for active magnetic bearings, investigating the impact of saturation and leakage flux on control performance. This research contributes to the development of reliable magnetic bearing systems for advanced applications.