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Grid security is the lifeline of civilization. As one of the most important function in State Estimation (SE), Bad Data Detection (BDD) is vulnerable to false data injection attacks. Therefore, it is very important to develop patent and effective method to detect false data injection attacks. In this paper, we propose an improved cusum algorithm and synergy with the Unscented Kalman Filter (UKF) to detect false data injection attack. The proposed algorithm tested on IEEE-14 systems successfully, confirm the advantages of the approach.

The modern power system is the integration and development of the physical grid and the information system. However, state estimation in the modern power system faces the rising threat of false data injection attacks, which lead to malfunction of the relay protection, dispatcher's misjudgment or faulty operation. In this paper, we propose an improved detection method to detect false data injection attacks based on the Jensen-Shannon distance. This method tracks the dynamics of measurement variations and calculates the distance between two probability distributions derived from real-time measurement variations and historical measurement variations. When false data is injected into the modern power system, the real-time probability distributions will deviate from the historical ones, thus leading to a larger Jansen-Shannon distance. The proposed method is simulated on the IEEE14-bus system using real load data. Test results demonstrate that our method can accurately detect most of the attacks, and has good stability as well as practicability.

Smart grid is a space-time multidimensional heterogeneous system integrated with cyber system and power system. Because of event-driven discrete characteristic of communication system and continuous characteristic of power system, it is difficult to study power and communication hybrid system. In traditional researches, the model of either system was simplified and run in one single platform, while the accuracy and practicability of study results can't be guaranteed. Therefore, co-simulation methods have become a research hotspot which can be used to analyze complex dynamic performance of power and communication hybrid system. This paper summarizes existing co-simulation methods by classifying them into three types: unified simulation methods, non-real-time simulation methods and real-time simulation methods. Simulation tools, system architecture and data synchronization problems are also overviewed and analyzed in detail. In order to increase simulation precision and efficiency, a new time synchronization method based on state cache is proposed.

In this paper, a networked control problem is addressed for a class of singular systems with time-varying transmission period. The singular networked control system is transformed as an asynchronous dynamical system in the case of no networked-induced delay and no data packet dropout. Meanwhile, time-varying transmission period is regarded as a time-varying uncertain parameter. Further, the feedback stabilization of the asynchronous dynamical system is studied by Lyapunov methods and linear matrix inequality techniques. The design methods of a controller and the sufficient condition for stabilization of the system are presented. Finally, a numerical example illustrates the effectiveness of the proposed method.

Analytic Hierarchy Process (AHP) is a powerful tool to solve the tasks of multi-criterion decision system fields. But some complicated decision scenarios challenge the applications of AHP. For example, it may be either the complicated tasks are unable to be solved by AHP due to being unsatisfied with consistency condition or judgment matrix too intricate to solve, which causes AHP invalidation. To tackle such situation, an AHP knowledge system with the aid of Genetic Algorithms (GA) is proposed in which the priority order information is obtained through Rough Sets Theory (RST) method. With the development of economy globalization, enterprises and governments from home and abroad give more attention to improving the capability of self-innovation for enterprises. As a case study, the data of the self-innovation competence from investigation samples of Shanghai enterprises is fed into the proposed model and the analytical results indicate that the model is applicable.

The purpose of this study is to analyze the pelvic strain behavior after iliac tumor type I resection. Six adult cadaveric specimens were tested. The iliac subtotal resection models were established according to Ennecking's type I resection. The surficial strains of the defect pelvis and the intact pelvis were measured using 6 strain gauges attached to the key regions of pelvis including the site of lateral sacral mass, iliac arcuate line and the superior ramus of pubis. Axial loading from the proximal lumbar was applied by MTS load cell in the gradient of 0 N to 500 N in the double feet standing state. Much change of the strains was found of the pelvis after type I resection. Compared with the intact pelvis, the remarkable change of strain values was found on both side of the superior ramus of pubis, compressive strain altering to tensile strain. In addition, the average strain values on the normal sites of lateral sacral mass (-554.5plusmn251.2 muepsiv ) and iliac arcuate line(-1105.5plusmn352.7 muepsiv) under vertical load of 500 N were enlarged, which were 2.86 times and 3.77 time as much as the those in the corresponding sites of the intact pelvis. The differences of strain values on this two sites between the defect pelvis and the intact pelvis were statistically significant (p