Massimo La Scala

Short-Term State Forecasting-Aided Method for Detection of Smart Grid General False Data Injection Attacks

Successful detection of false data injection attacks (FDIAs) is essential for ensuring secure power grids operation and control. First, this paper extends the approximate dc model to a more general linear model that can handle both supervisory control and data acquisition and phasor measurement unit measurements. Then, a general FDIA based on this model is derived and the error tolerance of such attacks is discussed. To detect such attacks, a method based on short-term state forecasting considering temporal correlation is proposed. Furthermore, a statistics-based measurement consistency test method is presented to check the consistency between the forecasted measurements and the received measurements. This measurement consistency test is further integrated with

Predictive Dispatch Across Time of Hybrid Isolated Power Systems

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Enhancement of interconnected power system stability using a control strategy involving static phase shifters

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A probabilistic approach to the voltage stability analysis of interconnected power systems

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PMU based Robust Dynamic State Estimation method for power systems

-norm-based measurement residual analysis to construct the proposed detection metric. The proposed detector addresses the shortcoming of previous detectors in terms of handling critical measurements. Besides, the removal problem of attacked measurements, which may cause the system to become unobservable, is addressed effectively by the proposed method through forecasted measurements. Numerical tests on IEEE 14-bus and 118-bus test systems verify the effectiveness and performance of the proposed method.

Coordination of active and reactive distributed resources in a smart grid

The paper proposes a methodology for the optimal dispatch of energy sources in hybrid and isolated energy systems. The proposed approach is based on the formulation and solution of a nonlinear discrete optimization problem aimed at optimizing input and output time trajectories for a set of combined generating and storage technologies. Loads and interruptible loads are among controlled variables, and are modeled according to their interruption costs. The approach is general enough to be applied to any hybrid system configuration and was developed having in mind the complex hybrid system architectures comprising several competing storage technologies (battery, pumping, and hydrogen). Test results are aimed at showing the feasibility of the proposed methodology, comparing optimal trajectories to suboptimal system behavior given by load-following strategies.

Transmission Grid Control Through TCSC Dynamic Series Compensation

Abstract The static phase shifting transformer is one of the potential options of the recently proposed FACTS (flexible AC transmission systems). Promising results have been obtained for enhancing the small-disturbance and the transient stability of interconnected power systems. In this paper, the important concept of involving in the same control strategy both generating units and static phase shifters has been considered. A systematic procedure for designing co-ordinated and decentralized controllers of these components is provided to assure a satisfactory dynamic performance of an interconnected power system under both small and large perturbations. The approach uses optimal control theory as a basis for the co-ordination of static phase shifter and governor controllers. A suboptimal decentralized control scheme is derived from the designed optimal controller by using a ‘minimum norm’ nearness criterion. The resulting feedback control signals for each generating unit and for each phase shifter is expressed in terms of measurable and local variables only. Test results show the effectiveness of the proposed control strategy and the usefulness of control actions on static phase shifters.

Advanced Monitoring and Control Approaches for Enhancing Power System Security

Abstract In planning a power system it is always necessary to assess whether a voltage collapse occurs during a prefixed system operating condition. However, present approaches to the analysis of voltage instability phenomena in interconnected power systems are deterministic and, consequently, they cannot take into account the unavoidable uncertainties associated with the bus load forecast. This is indeed an important limitation. In this case the application of probabilistic techniques is the most feasible alternative. On the basis of this observation, in this paper a probabilistic approach to the voltage stability analysis of interconnected power systems is presented; it treats loads as random uncorrelated variables with normal distributions. The method proves suitable for determining systematically, for each expected system operating condition, the statistics of all the node voltages which are critical from the voltage stability viewpoint. The capability and usefulness of the suggested approach are illustrated by carrying out simulation studies on a sample power system.

Multistage Phasor-aided Bad Data Detection and Identification

An accurate and dynamically robust state estimator is indispensable for the efficient and reliable operation of a power system. In this paper, a state estimation method based on Phasor Measurement Units (PMUs) is proposed for the real-time monitoring of power systems under various operating conditions. This PMU-based Robust Dynamic State Estimator (PRDSE) makes feasible the combination of historical measurements, obtained from the Supervisory Control And Data Acquisition (SCADA) system, with present more precision measurements obtained from PMUs. A new state accuracy-based weighting function is proposed to increase the robustness when the system encounters a large unwanted disturbance. Several IEEE test systems under normal and dynamic operation conditions are used to demonstrate the high performance of the PRDSE. Numerical results show the effectiveness and robustness of the PRDSE.

Protection system monitoring for the prevention of cascading events in smart transmission grids

The authors present a methodology for assessing centralized control of active and reactive distributed resources in a smart distribution grid. The methodology is based on three-phase optimal power flow and is able to deal properly with unbalanced conditions and both single-phase and three-phase control resources. Single-phase resources that can be exploited by means of this approach are domestic loads, photovoltaic and distributed micro-generation. The methodology is developed on an open-source simulating environment and tested on the IEEE 123-bus Radial Distribution Feeder test case.