In line with the global commitment to net-zero emissions, three key trends—digitalization, decentralization, and electrification—are rapidly driving the transformation of power and transportation systems. As the power system transitions from a passive, one-way infrastructure to a dynamic, bidirectional network, digitalization becomes crucial in enabling seamless data flow. Decentralization facilitates the integration of high levels of renewable energy sources (RESs) and flexible demand response mechanisms. Electrification, particularly through the widespread adoption of electric vehicles (EVs), offers a significant pathway for decarbonizing the transport sector. Furthermore, green hydrogen plays a pivotal role in the transition to net zero. The operation of hydrogen-based technologies within the power system can enhance energy efficiency and promote sustainability. Therefore, developing sustainable energy management models for the optimal scheduling of energy systems integrated with EVs and hydrogen-based technologies is of critical importance and forms the core focus of this thesis. Firstly, this thesis presents a model for charging scheduling and trajectory optimization for in-motion EVs, integrating EVs with parking lots while facilitating their participation in real-time electricity markets. Additionally, two scheduling models are introduced for power-and-hydrogen-based microgrids (P&HMGs). The first model addresses price-taker microgrids connected to the distribution grid, incorporating local energy markets for both power and hydrogen, as well as retail and balancing electricity markets. The second model considers price-maker microgrids and their participation in wholesale electricity markets (WEM). Moreover, this thesis presents a scheduling model for virtual energy hub (VEH) plants, enabling their participation in WEM. All proposed models are designed with a risk-averse approach to manage uncertainties and are decentralized to ensure data privacy, enhance scalability, and improve security. This research lays the groundwork for integrating emerging technologies with existing energy infrastructures and optimally coordinating their participation in various energy markets. Simulation results demonstrate the efficiency and practical applicability of the proposed models.
Date of Award | 23 Jan 2025 |
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Original language | English |
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Awarding Institution | |
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Supervisor | Abbas Mehrabidavoodabadi (Supervisor) & Mousa Marzband (Supervisor) |
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- Microgrid
- Electricity Market
- Uncertainty Management
- Power-to-Hydrogen
- Decentralized Energy Management
Sustainable Scheduling of Smart Energy Systems Integrated with Electric Vehicles
Mansour Saatloo, A. (Author). 23 Jan 2025
Student thesis: Doctoral Thesis