Application of computing and communications intelligence effectively improves the quality of monitoring and control of smart grids However, the dependence on information technology also increases vulnerability to malicious attacks False data injection (FDI), that attack on the integrity of data, is emerging as a severe threat to the supervisory control and data acquisition system In this paper, we exploit deep learning techniques to recognize the behavior features of FDI attacks with the historical measurement data and employ the captured features to detect the FDI attacks in real-time By doing so, our proposed detection mechanism effectively relaxes the assumptions on the potential attack scenarios and achieves high accuracy Furthermore, we propose an optimization model to characterize the behavior of one type of FDI attack that compromises the limited number of state measurements of the power system for electricity theft We illustrate the performance of the proposed strategy through the simulation by using IEEE 118-bus test system We also evaluate the scalability of our proposed detection mechanism by using IEEE 300-bus test system

Real-Time Detection of False Data Injection Attacks in Smart Grid: A Deep Learning-Based Intelligent Mechanism

The paper investigates contribution of doubly fed induction generator (DFIG) to system frequency responses. Impact of different governor settings and system inertia are investigated. Three distinct cases are simulated in order to illustrate the influence of DFIG penetration on frequency regulation. Provision of inertial response by DFIG through artificial speed coupling is also presented. The effects of the inertial response on the machine behavior and its significance for frequency regulation are discussed. The influence of converter current limits and auxiliary loop parameters on the inertial response are illustrated and a novel control algorithm is developed for extracting maximum energy from the turbine in a stable manner. The results of the study are illustrated on the example of an isolated power system consisting of a diesel generator and a DFIG.

Dynamic Contribution of DFIG-Based Wind Plants to System Frequency Disturbances

This paper conducts an analysis of subsynchronous resonance (SSR) phenomena in doubly-fed induction generator (DFIG)-based wind farms interconnected with series compensated networks. A dynamic model is developed to analyze the induction generator effect (IGE) and torsional interaction (TI) in such systems. A test system derived from the IEEE first benchmark model is considered for the analysis. The effect of two factors namely: 1) series compensation level and 2) wind speed on the IGE and TI are studied. In addition, impact of the inner current converter controller parameters and turbine parameters on SSR is also addressed. Small signal (eigenvalue) analysis is conducted to assess the damping of network and torsional modes followed by dynamic (time domain) simulations. The major contribution of this paper is the analytical investigation on SSR phenomena presented in DFIG-based wind farms interconnected with series compensated networks. The paper clearly demonstrates that IGE instead of TI is the major reason for SSR in such systems.

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Modeling of DFIG-Based Wind Farms for SSR Analysis

Subsynchronous resonance (SSR) was observed in wind farms located in North China. These wind farms prevailingly consist of doubly-fed induction generators (DFIGs) and are connected to series-compensated transmission lines. The observed resonant frequency is about 6 $\sim$ 8 Hz, which is much lower than that of the reported SSR occurred in Texas. The frequency varies during the occurrence and this phenomenon is observed for the first time. The output power is usually within a certain range, when SSR occurs. Based on the practical system, an equivalent simulation system has been established, in which wind farms are modeled as many identical low rating DFIGs. Then, the SSR event is reproduced by simulations. Analysis results indicate that SSR happens even when the equivalent transmission system compensation level seen from wind farms is only 6.67%. Eigenvalue analysis shows that this phenomenon is an electrical resonance, and could be affected considerably by wind speed, number and control of DFIGs. The number of in-service DFIGs has a nonlinear impact on the damping of SSR. An equivalent electric circuit is deduced to intuitively explain why SSR happens and how the above factors affect it. Considering its features, this phenomenon is recognized as DFIG control participated induction generator effect.

Investigation of SSR in Practical DFIG-Based Wind Farms Connected to a Series-Compensated Power System

The paper presents a nonlinear approach, using a two-mass model and a wind speed estimator, for variable-speed wind turbine (WT) control. The use of a two-mass model is motivated by the need to deal with flexible modes induced by the low-speed shaft stiffness. The main objective of the proposed controllers is the wind power capture optimization while limiting transient loads on the drive-train components. This paper starts by an adaptation of some existing control strategies. However, their performance are weak, as the dynamics aspects of the wind and aeroturbine are not taken into consideration. In order to bring some improvements, nonlinear static and dynamic state feedback controllers, with a wind speed estimator, are then proposed. Concerning the wind speed estimator, the idea behind this is to exploit the WT dynamics by itself as a measurement device. All these methods have been first tested and validated using an aeroelastic WT simulator. A comparative study between the proposed controllers is performed. The results show better performance for the nonlinear dynamic controller with estimator in comparison with the adapted existing methods.

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Nonlinear Control of a Variable-Speed Wind Turbine Using a Two-Mass Model

Due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. the variable speed wind turbine using a doubly fed induction generator (DFIG) is becoming a popular concept and thus the modeling of the DFIG based wind turbine becomes an interesting research topic. Fundamental frequency models have been presented but these models are often complex with significant numerical overhead as the power converter block consisting of power control, rotor side and grid side converter control and DC link are often simulated in detail. This paper develops a simple DFIG wind turbine model in which the power converter is simulated as a controlled voltage source, regulating the rotor current to meet the command of real and reactive power production. This model has the form of traditional generator model and hence is easy to integrate into the power system simulation tool such as PSS/E. As an example, the interaction between the Arklow Bank Wind Farm and the Irish National Grid was simulated using the proposed model. The model performance and accuracy was also compared with the detailed model developed by DIgSILENT. Considering the simplification adopted for the model development, the limitation and applicability of the model were also discussed in this paper.

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Yazhou Lei

Papers

Modeling of the wind turbine with a doubly fed induction generator for grid integration studies