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As climate change provides impetus for investing in smart cities, withelectrified public transit systems, we consider electric public transportationbuses in an urban area, which play a role in the power system operations inaddition to their typical function of serving public transit demand. Our modelconsiders a social planner, such that the transit authority and the operator ofthe electricity system co-optimize the power system to minimize the totaloperational cost of the grid, while satisfying additional transportationconstraints on buses. We provide deterministic and stochastic formulations toco-optimize the system. Each stochastic formulation provides a different set ofrecourse actions to manage the variable renewable energy uncertainty: rampingup/down the conventional generators, or charging/discharging of the transitfleet. We demonstrate the capabilities of the model and the benefit obtainedvia a coordinated strategy. We compare the efficacies of these recourse actionsto provide additional managerial insights. We analyze the effect of differentpricing strategies on the co-optimization. We also conduct congestion analysisin the power network, comparing our cooperative approach to a non-cooperativestrategy when we assume electrified fleet sizes grow with greater batterycapacities. Given the recent momentum towards building smarter cities andelectrifying transit systems, our results provide policy directions towards asustainable future. We test our models using modified MATPOWER case files andverify our results with different sized power networks. This study is motivatedby a project with a large transit authority in California.

Co-optimizing the Smart Grid and Electric Public Transit Bus System