A chaos-oriented prediction and suppression model to enhance the security for cyber physical power systems

Abstract

Smart grid has become a fully automated system with common use of electronic equipments to control, compute and communicate. This can be modeled as cyber physical power systems (CPPS) to analyze connections and interactions, and security is one of the key factors to find the inner unmanaged vulnerabilities. In some cases, voltage source inverters (VSI) with pulse width modulation (PWM) are sensitive to initial conditions, and this is a typical chaotic state. In this paper, we present a CPPS model with the improved chaos prediction and suppression methods to enhance the security with the abilities to avoid and eliminate chaos. The main process is “prediction–quantization–control”. First, an improved maximum velocity criterion method is used to predict the possibility of chaos in the parameter space of CPPS. Second, when a possibility of chaos is predicted, a sinusoidal wave frequency modulation is used to suppress chaos. To analyze the connections of the inner entities’ transmission, a security coefficient is introduced to obtain hazard perception and to express measurements quantitatively. Third, it has proposed a chaotic control algorithm based on a fuzzy model with closed-loop dynamic mechanism to solve the security coefficient effectively. The experiments prove the predicted result has a margin of error of plus or minus 10%, and the sinusoidal wave frequency modulation can avoid chaos on CPPS. Also, the results show that security coefficient increases by 13.89%, which means it is useful with sensitive parameters and other related disturbances. Overall, this CPPS model can eliminate potential chaos phenomena caused by inversion processes, and it can be used into smart grids to improve the security effectively.