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Cooperative balancing between energy communities using traffic information and charging assignments

Integrating high penetration of fluctuating renewable energy sources causes many challenges for the future smart grids. The integration of intelligence from e.g. transportation provides opportunities for new services for local balancing. In this paper we introduce a method of cooperative balancing between adjacent grid segments for local power balancing which uses the mobility of electric vehicles with short-term charging needs in the load profile adaptation for grid segments through the exchange of EV charging demands between grid segments. Hereby travel tolerances like speed, direction, and charging needs are exploited. The method will be assessed through simulations in a two-grid-segment setup and a fleet of electric vehicles. Practically, the method serves a dynamic charging station assignment respecting immediate user preferences. Results show, that the method contributes to the prevention of critical load levels to impact the grid balancing by linking with the traffic flow as input (prediction) as well as controllable variable (via charging assignments).