A major battery maker has called for more precise modelling to identify the optimum level of energy storage for projects.  

Michael Lippert (pictured), marketing and business development manager with France-based Saft’s TTG division, said such modelling can predict energy storage systems’ (ESS) fuel savings, lifetime performance and ROI.

Lippert said battery modelling techniques are continuing to evolve to better address the growth of microgrids and renewables. As part of this evolution, simulations are now key to the project development process and can deliver insights into renewable and storage applications ahead of deployment, helping to determine how much power and energy are required overall.

However, while modelling software can quickly carry out simulations to discover the optimum renewable power rating along with an appropriate level of storage, Lippert said precise modelling requires more detailed inputs and time to optimize the dispatch methodology.

High-level modelling, which is feasible even with minimal data input, is typically based on hourly data, he explained. But with this sort of modelling the granularity of ESS dispatch is correspondingly coarse.

For example, Lippert said, an initial model of a microgrid can be constructed with minimal inputs, such as the coordinates of an island village off the US Pacific coast having a peak load of 150 kW in January. Based on this information, high-level modelling can be used to construct a typical load profile, and location-specific solar or wind data can be downloaded.

But high-frequency data, with granularity of no more than ten-minute intervals, is more valuable. According to Lippert, such modelling provides insights into system operation including diesel synchronization and cool-down times, and can minimize diesel starts, maximize fuel savings and optimize battery life.

“Combining high-level and precise modelling leads to a more cohesive, informed insight into energy storage system requirements,” said Lippert – “in turn, enabling an accurate evaluation of a project’s viability, as well as the development of a detailed strategy to help ensure project success.”

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