Analysis of bidirectional EV charging infrastructures within industrial DC grids

Industrial electrification is increasing to reduce fossil fuel dependence, alongside a growing share of volatile renewables. A secure and reliable energy supply is crucial for industry, leading to a shift from centralised to decentralised grid structures. DC microgrids becoming increasingly popular in industry, since they enable energy recuperation from braking, reduce components and cables, and integrate storage and local generation to manage supply interruptions or peak loads. EVs add further synergies by serving as mobile storage units, helping to store and redistribute locally generated renewable energy. This paper analyses how EV integration in droop-controlled DC grids can contribute to a more stable, low-emission and peak-reduced load profile to the supply grid through load shifting and bridge interruptions. A droop-controlled DC grid model has been developed, incorporating an EV charging park based on probability functions. Scalable scenarios allow for diverse condition analysis using an energy management system (EMS) that utilises fuzzy logic and sequential MILP optimisation. It has been shown that a 7% improvement of coefficient represented grid-serving behaviour is possible by load shifting. It has also been demonstrated that an optimised EMS can reduce the demand-based CO 2 emissions by 41 kg for a representative day compared to a fuzzy logic EMS. At the same time peak load is decreased yielding a more constant residual load. These results highlight the potential of a controlled bidirectional charging infrastructure in DC grids and underscore the need to explicitly consider charging processes to ensure a residual load as constant as possible.