Planning, Operation and Control of Battery Energy Storage Systems based on Repurposed Electric Vehicle Batteries
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Battery Energy Storage Systems (BESSs) play a pivotal role in facilitating the grid integration of renewable energy resources and mitigating the impact of high penetration of Electric Vehicles (EVs). The increasing number of EVs, however, would lead to stockpiling of used Electric Vehicle Batteries (EVBs) after their vehicular End-of-Life (EoL). Since high installation and capital costs of new BESS pose a barrier to their large-scale deployment, utilization of the used EVBs after repurposing can play a significant role in power systems by helping defer capacity addition in the long-term. This would also alleviate the adverse environmental impacts of manufacturing more batteries and delay the recycling process of used EVBs. There are significant benefits for the utilities, EV customers, and governments in utilizing the used EVBs, as they offer a cheaper option for energy storage applications. In this context, BESS has emerged as a promising and viable solution for utilities such as microgrids and Local Distribution Companies (LDCs) for balancing their supply and demand and implementing efficient control and operation. The thesis aims at developing models for planning, operation, and control of BESS and Repurposed Electric Vehicle Battery (REVB) in isolated microgrids and distribution systems. The thesis first presents a comprehensive and novel framework for planning and operation of BESS based on REVBs. A systematic procedure is proposed to model and simulate the degradation of EVBs during their first life in vehicles to capture the impact on their State of Health (SoH) and hence on the number of years to reach their EoL, which are used to estimate the expected cost of installing REVBs. A generic microgrid planning model is developed to determine the optimal energy and power ratings, and year of installation and replacement of new BESSs and REVBs considering the impact of calendar and cycling degradations. The proposed planning model introduces a novel set of mathematical relations for BESS degradation and optimal year of replacement, thereby avoiding premature replacements and additional costs. The EVB degradation model is arrived at by using a real EVs drive cycle database and the microgrid planning model is validated using the CIGRE isolated microgrid test system. The thesis then extends the earlier proposed microgrid planning model to include system adequacy requirement using a novel backward-forward propagation approach with an embedded energy sharing strategy for multiple REVB units. A novel concept of measuring the adequacy level of the microgrid in terms of REVB energy to power ratio (E/P) is presented. The novel, heuristic, adequacy check module starts from the terminal year of the planning horizon, and propagates to the initial year, to ensure that the microgrid's capacity adequacy requirements are met in all years. To accommodate multiple installations and replacements of REVBs over the planning horizon, an energy sharing strategy among various installed REVB units is proposed to enhance the battery useful life and delay their replacements so as to minimize the total cost. The proposed models are validated on the CIGRE isolated microgrid test system. The third part of the thesis introduces an interactive real-time Community Energy Management System (CEMS) for an REVB-based Community Energy Storage System (CESS) in a practical Low-Voltage (LV) distribution system. This is an extension (in terms of operation and control) to the first research problem, where economic viability of installing REVBs is assessed. A rule-based controller for the four-quadrant REVB-based CESS is embedded in the CEMS to reduce the loading of the distribution transformer and slow down battery degradation. The proposed controller structure can be modified based on the specific characteristics of the battery. A Hardware-in-the-Loop (HIL) simulation is carried out to validate the simulation results and illustrate the effectiveness of the proposed CEMS and its rule-based control algorithm, using actual signals from the Battery Management System (BMS) and the bidirectional charger setup.
Cite this version of the work
Talal Alharbi (2020). Planning, Operation and Control of Battery Energy Storage Systems based on Repurposed Electric Vehicle Batteries. UWSpace. http://hdl.handle.net/10012/16368
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