  As climate change provides impetus for investing in smart cities, with
electrified public transit systems, we consider electric public transportation
buses in an urban area, which play a role in the power system operations in
addition to their typical function of serving public transit demand. Our model
considers a social planner, such that the transit authority and the operator of
the electricity system co-optimize the power system to minimize the total
operational cost of the grid, while satisfying additional transportation
constraints on buses. We provide deterministic and stochastic formulations to
co-optimize the system. Each stochastic formulation provides a different set of
recourse actions to manage the variable renewable energy uncertainty: ramping
up/down the conventional generators, or charging/discharging of the transit
fleet. We demonstrate the capabilities of the model and the benefit obtained
via a coordinated strategy. We compare the efficacies of these recourse actions
to provide additional managerial insights. We analyze the effect of different
pricing strategies on the co-optimization. We also conduct congestion analysis
in the power network, comparing our cooperative approach to a non-cooperative
strategy when we assume electrified fleet sizes grow with greater battery
capacities. Given the recent momentum towards building smarter cities and
electrifying transit systems, our results provide policy directions towards a
sustainable future. We test our models using modified MATPOWER case files and
verify our results with different sized power networks. This study is motivated
by a project with a large transit authority in California.
