Abstract
A wide scale deployment of energy storage systems in power networks for energy balancing applications will lead to network reliability improvements. After a fault occurs in a network, energy storage will be able to help restore supply in the network areas isolated from the primary substation or in those re-connected to adjacent feeders of limited transfer capacity by emergency-ties. The reliability improvements introduced by energy storage need to be evaluated and quantified for both restoration modes. The objective of this paper is to assess the energy storage contribution in these restoration modes and to seek analytical, less computationally intensive solutions for such evaluation. The proposed analytical technique uses a probabilistic model of energy storage to assess the charge and discharge processes over a fault duration and the related operational strategy. In this way, reliability indices are calculated by taking into account the energy storage actions during a fault as well as the time-evolution of renewable generation and demand. These features lead to more realistic modelling of energy storage in analytical techniques. The proposed analytical technique was firstly validated by using a case study where the results obtained by Monte Carlo Simulation were used as a reference. Then, the proposed technique was applied to a distribution network to assess the reliability improvement provided by energy storage and to demonstrate the effectiveness and accuracy of the proposed approach.
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