ENERGY STORAGE SIMULATION
E-charging Infrastructure with Integrated Storage
Our energy storage simulation offers precise analyses and data-based foundations for decision-making. Based on real operating data, we simulate the behavior of energy storage systems and their integration into the energy market. With the help of our energy price forecasting tool FlexPowerHub , various strategies can be tested to maximize performance. At the same time, the simulation enables an accurate forecast of storage capacity utilization and thus supports optimal bidding on the market.
How Can a Battery Storage System be used Economically at an E-Charging Station?
A common problem with e-charging stations is the limited connected load, which limits the charging speed. Increasing the charging capacity often requires costly infrastructure measures such as the construction of transformers. A battery storage system solves this problem: it stores energy directly at the charging station and delivers up to 300 kW of charging power and 200 kWh of flexibility in one device.
In addition, unused storage capacity can be used profitably on the energy market. This creates additional income and increases the profitability of the investment by optimizing the use of the storage system. Our detailed feasibility study minimizes planning uncertainties by using cost-benefit analyses to reliably assess the profitability of storage integration based on historical values.
Data-based Energy Storage Simulation for Optimal Market Integration
Our simulation integrates operating data such as charging cycles, capacity utilization as well as historical and forecast energy prices. We use realistic models to analyze charging infrastructure and storage capacity utilization under various scenarios and take dynamic market developments into account. A clear visualization presents the results and recommendations for action in an interactive dashboard.
In future, the flexibility of battery storage systems can be recorded on the basis of these simulations and placed on various energy markets using individual marketing strategies. Our automation tool FlexPowerHub can then be used to optimize returns by offering existing flexibilities on the balancing energy market during the most profitable auction period. Forecasts for the next 2 to 8 hours are repeatedly employed and compared with the simulated use of the charging stations. A short-term reduction in available flexibility can be compensated for by an automatically adjusted (high) price set by FlexPowerHub.
In Which Ways Could cognify Support This Project?
How Our Customers Benefit
We simulate the use of battery storage and forecast charging usage based on historical data. Distributed across the charging stations and taking into account the charging curves, the storage system generates lucrative flexibilities. These are forecast for use on the balancing energy market and an overall yield calculation is created. Participation in the balancing energy market can be realized both in the form of cost-effective recharging management as well as high-yield and grid-supporting feeding into the power grid. Valuable by-product: The analysis of historical charging processes can provide important insights for the selection of locations for e-charging stations.