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Contribution of renewable energies in power systems is increasing due to continuous growth of wind and solar generators. Because of intermittency and uncertainty of these resources, conventional reliability evaluation methods are not applicable and different techniques have been developed to model these generators. However, most of these methods are time-consuming or may not be able to keep time dependency and correlations between renewable resources and load. Therefore, this paper intends to improve the existing methods and proposes a fast and simple approach. In this approach, wind power, PV generation and electricity demand are being modelled as time dependent clusters, which not only can capture their time dependent attributes, but also is able to keep the correlations between these data sets. To illustrate the effectiveness of this framework, the proposed methodology has been applied on two different case studies: IEEE RTS system and South Australia power network. The developed technique is validated by comparing results with sequential Monte Carlo technique.

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Source ID Mix" spoofing emerged as a new type of cyber-attack on Distribution Synchrophasors (DS) where adversaries have the capability to swap the source information of DS without changing the measurement values. Accurate detection of such a highly-deceptive attack is a challenging task especially when the spoofing attack happens on short fragments of DS recorded within a relatively small geographical scale. This letter proposes an effective approach to detect this cyber-attack by realizing the multifractal characteristics of DS measurements. First, the multifractal cross-correlation of DS measured at multiple intra-state locations is revealed. Then the derived correlation is integrated with weighted two-dimensional multifractal surface interpolation to reconstruct quasi highresolution signals. Finally, informative location-specific signatures are extracted from the high-resolution DS and they are integrated with advanced machine learning techniques for source authentication. Experiments using the real-life DS are performed to verify the proposed method.