IEET: KoLa

KoLa

Optimized Load Management and Flexibility Coordination for Electrified Urban Public Transport

Abstract

Transport companies in Germany are progressively converting their fleets to zero-emission drives as part of the decarbonization process. E-buses are currently charged mostly via a charging management system that distributes the available power to the various buses on the basis of internal, operational criteria (state of charge, disposition, time of use, etc.). The current states of the power grid and power acquisition have not been taken into account so far, although it is known that the expansion of the charging infrastructure can lead to local overload situations in the distribution grid.

Therefore, the KoLa project investigates the flexibility potentials of E-bus charging at the depot of Hamburger Hochbahn AG in Alsterdorf. New functions for the existing load management are to be developed so that the charging of the E-buses can also be optimized and shifted in time in the future on the basis of external control variables (criteria on the electricity grid side such as grid utilization and criteria on the electricity market side such as electricity market prices). By utilizing this flexibility potential, the electricity supply can be optimized on the basis of ecological (e.g., only green electricity) or economic (e.g., inexpensive electricity) criteria. In order to ensure congestion-free grid operation and minimize grid expansion despite flexible power usage, a coordination function (KOF) is being developed at the distribution grid level as part of the project. This KOF ensures that the shifting of the charging processes happens in accordance with the current grid state.

The focus of our contribution is the development of the KOF. This includes algorithms for load shifting based on the predicted grid conditions, as well as methods for forecasting unknown consumers. The research focuses, on the one hand, on the effects of schedule uncertainties and forecasting errors on preventive congestion prevention and, on the other hand, on evaluating non-discrimination and fairness in congestion management measures such as the KOF. In addition, the system is tested in a distributed simulation environment prior to deployment.