Modeling and performance evaluation of stealthy false data injection attacks on smart grid in the presence of corrupted measurements

The false data injection (FDI) attack cannot be detected by the traditional anomaly detection techniques used in the energy system state estimators. In this paper, we demonstrate how FDI attacks can be constructed blindly, i.e., without system knowledge, including topological connectivity and line reactance information. Our analysis reveals that existing FDI attacks become detectable (consequently unsuccessful) by the state estimator if the data contains grossly corrupted measurements such as device malfunction and communication errors. The proposed sparse optimization based stealthy attacks construction strategy overcomes this limitation by separating the gross errors from the measurement matrix. Extensive theoretical modeling and experimental evaluation show that the proposed technique performs more stealthily (has less relative error) and efficiently (fast enough to maintain time requirement) compared to other methods on IEEE benchmark test systems.Comment: Keywords: Smart grid, False data injection, Blind attack, Principal component analysis (PCA), Journal of Computer and System Sciences, Elsevier, 201

A Generalized Index for Static Voltage Stability of Unbalanced Polyphase Power Systems including Th\'evenin Equivalents and Polynomial Models

This paper proposes a Voltage Stability Index (VSI) suitable for unbalanced polyphase power systems. To this end, the grid is represented by a polyphase multiport network model (i.e., compound hybrid parameters), and the aggregate behavior of the devices in each node by Th\'evenin Equivalents (TEs) and Polynomial Models (PMs), respectively. The proposed VSI is a generalization of the known L-index, which is achieved through the use of compound electrical parameters, and the incorporation of TEs and PMs into its formal definition. Notably, the proposed VSI can handle unbalanced polyphase power systems, explicitly accounts for voltage-dependent behavior (represented by PMs), and is computationally inexpensive. These features are valuable for the operation of both transmission and distribution systems. Specifically, the ability to handle the unbalanced polyphase case is of particular value for distribution systems. In this context, it is proven that the compound hybrid parameters required for the calculation of the VSI do exist under practical conditions (i.e., for lossy grids). The proposed VSI is validated against state-of-the-art methods for voltage stability assessment using a benchmark system which is based on the IEEE 34-node feeder

Closed-Loop Control of a Piezo-Fluidic Amplifier

Fluidic valves based on the Coand\u{a} effect are increasingly being considered for use in aerodynamic flow control applications. A limiting factor is their variation in switching time, which often precludes their use. The purpose of this paper is to demonstrate the closed-loop control of a recently developed, novel piezo-fluidic valve that reduces response time uncertainty at the expense of operating bandwidth. Use is made of the fact that a fluidic jet responds to a piezo tone by deflecting away from its steady state position. A control signal used to vary this deflection is amplitude modulated onto the piezo tone. Using only a pressure measurement from one of the device output channels, an output-based LQG regulator was designed to follow a desired reference deflection, achieving control of a 90 m/s jet. Finally, the controller's performance in terms of disturbance rejection and response time predictability is demonstrated.Comment: 31 pages, 23 figures. Published in AIAA Journal, 4th May 202

Thrust stand evaluation of engine performance improvement algorithms in an F-15 airplane

An investigation is underway to determine the benefits of a new propulsion system optimization algorithm in an F-15 airplane. The performance seeking control (PSC) algorithm optimizes the quasi-steady-state performance of an F100 derivative turbofan engine for several modes of operation. The PSC algorithm uses an onboard software engine model that calculates thrust, stall margin, and other unmeasured variables for use in the optimization. As part of the PSC test program, the F-15 aircraft was operated on a horizontal thrust stand. Thrust was measured with highly accurate load cells. The measured thrust was compared to onboard model estimates and to results from posttest performance programs. Thrust changes using the various PSC modes were recorded. Those results were compared to benefits using the less complex highly integrated digital electronic control (HIDEC) algorithm. The PSC maximum thrust mode increased intermediate power thrust by 10 percent. The PSC engine model did very well at estimating measured thrust and closely followed the transients during optimization. Quantitative results from the evaluation of the algorithms and performance calculation models are included with emphasis on measured thrust results. The report presents a description of the PSC system and a discussion of factors affecting the accuracy of the thrust stand load measurements

Two-Stage Consensus-Based Distributed MPC for Interconnected Microgrids

In this paper, we propose a model predictive control based two-stage energy management system that aims at increasing the renewable infeed in interconnected microgrids (MGs). In particular, the proposed approach ensures that each MG in the network benefits from power exchange. In the first stage, the optimal islanded operational cost of each MG is obtained. In the second stage, the power exchange is determined such that the operational cost of each MG is below the optimal islanded cost from the first stage. In this stage, a distributed augmented Lagrangian method is used to solve the optimisation problem and determine the power flow of the network without requiring a central entity. This algorithm has faster convergence and same information exchange at each iteration as the dual decomposition algorithm. The properties of the algorithm are illustrated in a numerical case study

Low Power Depth Estimation of Rigid Objects for Time-of-Flight Imaging

Depth sensing is useful in a variety of applications that range from augmented reality to robotics. Time-of-flight (TOF) cameras are appealing because they obtain dense depth measurements with minimal latency. However, for many battery-powered devices, the illumination source of a TOF camera is power hungry and can limit the battery life of the device. To address this issue, we present an algorithm that lowers the power for depth sensing by reducing the usage of the TOF camera and estimating depth maps using concurrently collected images. Our technique also adaptively controls the TOF camera and enables it when an accurate depth map cannot be estimated. To ensure that the overall system power for depth sensing is reduced, we design our algorithm to run on a low power embedded platform, where it outputs 640x480 depth maps at 30 frames per second. We evaluate our approach on several RGB-D datasets, where it produces depth maps with an overall mean relative error of 0.96% and reduces the usage of the TOF camera by 85%. When used with commercial TOF cameras, we estimate that our algorithm can lower the total power for depth sensing by up to 73%