Techno-economic analysis of energy storage systems integrated with ultra-fast charging stations: A dutch case study

A fast and efficient charging infrastructure has become indispensable in the evolving energy landscape and thriving electric vehicle (EV) market. Irrespective of the charging stations’ internal alternating current (AC) or direct current (DC) bus configurations, the main concern is the exponential growth in charging demands, resulting in network congestion issues. In the context of exponential EV growth and the provision of charging facilities from low-voltage distribution networks, the distribution network may require frequent upgrades to meet the rising charging demands. To avoid network congestion problems and minimize operational expenses (OE) by integrating energy storage systems (ESS) into ultra-fast charging stations (UFCS). This paper presents a techno-economic analysis of a UFCS equipped with a battery ESS (BESS). To reduce reliance on the electric grid and minimize OE, a dual-objective optimization problem is formulated and solved via grid search and dual-simplex algorithms. Analytical energy and physical BESS models are employed to evaluate the optimization matrices. The intricacies of BESS ageing are examined to ensure an optimal BESS size with a more extensive lifespan than the corresponding payback period. The integrated BESS significantly reduced reliance on the grid to tackle network congestion while fulfilling charging demands. The dynamic pricing (DP) structure has proven more favourable, as the average per unit cost remains lower than the static tariff (ST). Results illustrate that integrating BESS reduces the OE and peak-to-average ratio (PAR) by 5-to-49% and 16-to-73%, respectively. Moreover, the combination of 70% BESS and 30% grid capacities outperforms the other configurations with a 73% reduction in PAR and a 49% reduction in OE before BESS reaches the end-of-life. • A realistic demand profile that resembles the FastNed network charging demand is introduced to replicate real-world charging scenarios. • Electric vehicle analytical and charging stations’ cumulative energy models have been developed. • The impact of the energy storage system on reducing grid reliance and operational expenses is analyzed to mitigate power system contingencies and optimize resource utilization. • The grid search algorithm optimizes the grid connection and energy storage sizes, and the linear programming algorithm schedules (dis)charging processes. • The temperature-dependent parameters of the energy storage system are considered in the estimation of cyclic ageing. • The impact of storage system size and ageing factors is investigated on lifespan.