Since the Ukraine blackout in 2015, coordinated cyber-physical attacks (CCPAs) have been emerging and are used to mask line outages in the smart grid. In this paper, we investigate the features of CCPAs and constitute the mathematic formulation with respect to topologies and electric parameters of a power grid before and after attacks. With the objective of maximizing the number of overloaded lines, a bilevel programming model is developed to describe the interaction between the adversary and the control center. The most damaging CCPA can be determined by transforming the developed bilevel model to a single mixed-integer linear programming problem using the Karush-Kuhn-Tucker conditions. Based on the features of the bilevel model, the countermeasure is expressed as a trilevel model with one leader and multiple followers. The implicit enumeration-based searching strategy is proposed to solve the trilevel model to identify the protected meters. Both the implementation of CCPAs and the effectiveness of the developed countermeasure are verified on the modified IEEE 14-bus system. INDEX TERMS Bilevel programming, coordinated cyber physical attacks (CCPAs), trilevel programming, smart grid. NOMENCLATURE Sets and Indices: O/d Bus set / bus index. G/g Generation set / generation index. L/l Transmission line set / transmission line index.

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As one of the most important mesoscopic properties of networks, the community structure plays an important role in cascading failures on isolated networks. However, the study for understanding the influences of the community structure on the cascading failures on interdependent scale-free networks remains missing. In this paper, we investigate cascading failures on interdependent modular scale-free networks under inner attacks and hub attacks from the global and local perspective. We mainly analyse the inter-community connections and coupling preferences, i.e. random coupling in communities (RCIC), assortative coupling in communities (ACIC) and assortative coupling with communities (ACWC). We find that increasing inter-community connections can enhance the robustness of interdependent modular scale-free networks for both inner attacks and hub attacks. Furthermore, we also find that the ACIC is more beneficial to resisting cascading failures compared with RCIC or ACWC. For ACIC, the cascading failures propagate mainly in a local community where the initial failure occurs. It is meaningful to control the cascading failures on interdependent modular scale-free networks by constructing ACIC.

Surveillance of SF6 decomposition products is significant for detection of partial discharge (PD) in gas insulation switchgear (GIS). As a basis in on-site detection and diagnosis, PD early-warning aims to quickly find the abnormalities using a simple and cheap device. In this paper, SO2 is chosen as a feature product and detected through ultraviolet spectroscopy. The derivative method is employed for baseline correction and spectral enhancement. The standard gases of the main decomposition products are qualitatively and quantitatively detected. Then decomposition experiments with different defects are designed to further verify the feasibility. As a stable decomposition product under PD, SO2 is proved to be applicable for PD early-warning in the field. By selecting the appropriate wavelength range, namely 290–310 nm, ultraviolet derivative spectroscopy is sensitive enough to the trace SO2 in the decomposed gas and the interference of other products can be avoided. Fast Fourier transform could be used for feature extraction in qualitative detection. Concentrations of SO2 and other by-products increase with increasing discharge time and could be affected by the discharge energy and PD type. Ultraviolet detection based on SO2 is effective for PD early-warning but the threshold should still be carefully selected in practice.

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