INTEGRATING ELECTRIC ROADWAYS INTO THE ELECTRIC POWER SYSTEM: A MULTI-SCALE SPATIOTEMPORAL EVALUATION

Electric roadways (ERs) represent a new paradigm for electrified transportation that is

enabled by the emerging dynamic (in-motion) wireless power transfer technology. Large-scale

integration of DWPT systems into power grids can pose a problem due to its high-power

requirements, significant number of power electronic converters and spatial concentration.

Despite their potential magnitude, the operational impacts of DWPT on the power grid have

not been fully studied in the literature. This dissertation contributes to our understanding

of how ERs could be successfully integrated with the electric power system at a diverse range

of spatial and temporal levels.

On a macroscopic level, a framework for assessing the financial viability of ERs is proposed.

Annual ER load estimations from traffic flow models of electric vehicles are used to

generate energy forecasts and carry out a financial evaluation. These models are also used to

plan distribution system capacity expansion. On a mesoscopic level, a data-driven design of

ERs and their interconnection with the distribution grid is presented. A data-based stochastic

traffic flow model is developed and used for designing the interconnection of the DWPT

system with the distribution grid ensuring adequate power transmission to high penetration

levels of heavy-duty trucks. The model is also used for conducting a series of quasi-steady

state studies on the power distribution system. On a microscopic level, a methodology for

modeling ER systems for time-domain simulations is proposed. Dynamic component models

are developed for the DWPT system. Power electronics are modeled using average-value

representations and integrated with models of the distribution grid. The models are used for

time-domain system simulations, transient analysis, fault analysis and power quality studies.

Theoretical analysis as well as numerical case studies and simulations of the proposed

methodologies are presented.