Planning of Sustainable Distribution Networks Utilizing Mobile Energy Storage Systems

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De-carbonization and smart-grid initiatives led to an evolution in distribution networks (DNs) from conventional towards sustainable grids with high penetration of renewable energy sources (RESs) and electric vehicles (EVs). Such innovations impose challenges to the planning and operation of DNs. Energy storage systems (ESSs) are one promising technology that can mitigate some of these challenges. The research proposed include the following projects: 1)Increasing the connectivity of RESs and fast-charging stations (FCSs) in DNs: With the growing penetration levels of RESs and EVs, the adequacy and security of DNs could be compromised because of the uncertainty associated with such components. Thus, deploying ESSs is essential for accommodating large capacities of RESs and FCSs. More specifically, these components have time-varying profiles, which differ from one month, or season, to the other. Therefore, the application of mobile ESSs (MESSs) deems more efficient and economical, in comparison to stationary ESSs, to accommodate the seasonality of RESs and FCSs. The research proposed in this area aims at developing a stochastic planning framework that employs MESSs for increasing the penetration levels of RESs and FCSs in DNs. 2) Providing a resilient response to natural disasters: MESSs can provide emergency response to power outages due to natural disasters (e.g., hurricanes, storms, etc.), thus increasing the resiliency and reliability of DNs. For this purpose, the proposed research includes two stages: pre-positioning and real-time allocation. These two stages ensure placing MESSs at the optimal locations to serve DNs during normal operation, and to reach and restore affected zones (microgrids) during contingencies. 3)Optimizing investments in microgrids: Next-generation DNs (i.e., dc or hybrid ac/dc microgrids with high penetration of RESs and EVs) necessitate the cost-effective allocation of ESSs to justify the use of such a costly technology. Microgrids boundaries define zones that are characterized by different types and power profiles of loads and RESs. Moving MESSs between neighboring zones is the key to meet their various needs and optimize investment costs of ESSs. Therefore, a new planning model for MESSs in microgrids is essential, which aims at optimizing costs and revenues of MESSs, while taking into consideration the probabilistic models of loads and RESs. The above projects will support the training of HQP and provide the new tools that are crucially needed to enhance DN reliability and support the integration of RESs and EVs. In Canada, the industrial beneficiaries of this program include local distribution companies (utilities). Students who participate in the projects will receive advanced training in the planning and operation of modern DNs, becoming highly qualified individuals ready to contribute to the Canadian economy through careers in academia, industry, and government.