Subsequently, a comprehensive optimization model is formulated for the large-scale deployment of various energy storage types, aiming to minimize the annual system-wide cost. Furthermore, to overcome computational complexity, the second-order cone relaxation method is implemented for efficient convexification of the non-convex planning problem.
Contemporary research has explored diverse energy storage applications across power systems, revealing location-dependent operational characteristics . An optimization framework for determining the optimal capacity and location of battery energy storage systems (BESS) in distribution networks is developed in .
For practical operation, the electrochemical energy storage units are assumed to adopt virtual synchronous generator (VSG) control, emulating synchronous inertia and damping to provide virtual inertia and primary frequency regulation, as illustrated in Fig. 1 (a).
To tackle the previously mentioned challenges and guarantee the reliable and stable operation of transmission networks, massive energy storage systems (ESSs) emerge as a strategic imperative, enabling dynamic mitigation of volatility-induced imbalances between generation and demand [, ].
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