The integration of high and ultra-high shares of variable renewable energies (VREs)âwind and solar powerâ rises some technical challenges that need to be solved to maintain the reliability and cost-effectiveness of power systems. For example, VREs are weather-dependent and therefore their power generation is uncertain and exhibit variable diurnal and seasonal patterns. These properties cause more frequent and/or steeper net demand fluctuations that require the enhancement of power system flexibility
[1,2]. Energy storage devices could play a pivotal role in the transition towards low-carbon and flexible power systems. For instance, these devices can provide a variety of services including energy arbitrage, transmission and distribution congestion relief and investment deferral, demand shifting and peak reduction, spinning and non-spinning reserves, and seasonal energy storage
. However, the assessment of the integration of VREs and energy storage technologies using model-based system analysis poses a challenge for the modeling of power system. For instance, the modeling of VREs and storage systems requires the accommodation of short-term dynamics âwind and solar generation patterns as well as evolution of storage levelsâ using a chronological hourly resolution in power planning models, which result in large computational needs
[4,5]. This study focuses on the techno-economic assessment of grid-energy storage technologies from energy storage owner (ESO) and system operator (SO) perspectives using price-taker and production cost models, respectively. Different modeling approaches are evaluated in terms of both accuracy and computational cost. Finally, niche markets for grid energy storage in United States are identified and impacts on electricity prices and power system operations are quantified.
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