Faruk Kazi

Support-Vector-Machine-Based Proactive Cascade Prediction in Smart Grid Using Probabilistic Framework

The worldwide major blackout events of power network are highlighting the need for technology upgradation in traditional grid. One of the major upgradations required is in the area of early warning generation in case of any grid disturbances such as line contingency leading to cascade failure. This paper proposes a proactive blackout prediction model for a smart grid early warning system. The proposed model evaluates system performance probabilistically, in steady state and under dynamical (line contingency) state, and prepares a historical database for normal and cascade failure states. A support vector machine (SVM) has been trained with this historical database and is used to predict blackout events in advance. The key contribution of this paper is to capture the essence of the cascading failure using probabilistic framework and integration of SVM machine learning tool to build a prediction rule, which would be able to predict the scenarios of the blackout as early as possible. The proposed model is validated using the IEEE 30-bus test-bed system. Proactive prediction of cascade failure using the proposed model may help in realizing the grid resilience feature of smart grid.

Cascading Failure Analysis for Indian Power Grid

Major power grid blackouts in various parts of the world are characterized by voltage collapse. This paper studies the blackout case in the Indian power grid due to voltage collapse in the inter-regional corridor. First, the computer simulation models are tuned to match responses from the phasor measurement units at various locations in the grid. The inter-area mode with the frequency of 0.3 and 0.5 Hz with reduced damping were observed and resulted due to switching actions that occurred during the disturbance. This paper simulates the complex power grid network for various loading conditions of Northern region using power system simulator for engineering. Further, the system variables are analyzed using Prony method to estimate the inter-area mode for different NR loading conditions. The eigen values associated with the 0.3 Hz mode depict the movement from open left half plane into open right half plane with a slight increase in the parameter indicating “hopf bifurcation.” This paper also discusses the maximum loading capacity for the inter-regional lines in-order avoid loss of small signal stability, and highlights the use of real time phasor measurement unit measurements in-order to estimate and track the oscillatory modes.

Shaping the Energy of Mechanical Systems Without Solving Partial Differential Equations

Control of underactuated mechanical systems via energy shaping is a well-established, robust design technique. Unfortunately, its application is often stymied by the need to solve partial differential equations (PDEs). In this technical note a new, fully constructive, procedure to shape the energy for a class of mechanical systems that obviates the solution of PDEs is proposed. The control law consists of a first stage of partial feedback linearization followed by a simple proportional plus integral controller acting on two new passive outputs. The class of systems for which the procedure is applicable is identified imposing some (directly verifiable) conditions on the systems inertia matrix and its potential energy function. It is shown that these conditions are satisfied by three benchmark examples.

Total energy-shaping IDA-PBC control of the 2D-SpiderCrane

The objective of this paper is to further extend the application of the Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) technique to the 2D-SpiderCrane mechanism with both kinetic and potential energy being shaped. An earlier effort had focused exclusively on potential energy alone. By shaping the total energy and by adding appropriate damping we achieve almost global asymptotic stability of the desired equilibrium.

Stabilization of a 2D-SpiderCrane Mechanism Using Damping Assignment Passivity-based Control

Cable-operated manipulators, also termed cable robots, possess a number of unique properties which make them suitable for tasks involving high payloads, large workspaces, and interacting with dangerous materials. But the fact that cables can only pull the end effector but not push it, makes their feedback control law more challenging than their counterpart, the rigid robots. In this paper, we present a modeling and control strategy for a cable suspended structure called the \lq{SpiderCrane}\rq. By avoiding heavy mobile components, the design of this crane makes it particularly useful for work requiring high speeds. The modeling of such a multiple cable mechanism is challenging due to the number of constraints arising from cable interactions. From a control theoretical point of view, such mechanical systems are underactuated, which gives rise to challenging control issues. In this paper, we consider a 2-dimensional version of SpiderCrane that captures most of its control-related aspects. We employ a novel approach, by which we separate the cable and pulley dynamics from the payload dynamics for the ease of controller design. This enables us to view the payload as a pendulum suspended from a cable whose suspension point lies on a mass that moves in a two-dimensional space. We apply interconnection and damping assignment passivity-based control to both shape the potential energy and change the interconnection structure for swing minimization. Damping is injected to ensure (asymptotic) stabilization.

Impact of Topology on the Propagation of Cascading Failure in Power Grid

In the past two decades the frequent occurrences of large scale blackouts and catastrophic events has reduced the reliability of power grid to a great extent. A thorough analysis of the propagation of failures, in terms of line outages, combined with the topological characteristics of the grid aids, has been done to take corrective actions to save the system from complete collapse. It also helps to investigate the progress and understand the nature and intensity of blackouts. This motivates to establish the relationship between the network topological characteristics and cascading failure in the power grid. In this paper, the basic topological characteristics of the power network are studied in detail and the average propagation of failure under varying topological conditions is calculated as a branching process parameter. The variation in the mean propagation is studied in detail using a number of test bed networks with the alternate realistic networks derived from the standard IEEE networks imitating the real network conditions. The results confirm a qualitative agreement between the variations in topological parameter and the failure propagation rate in the cascading regime. Based on the analysis mentioned above, data clearly shows that the average failure propagation factor varies linearly with the variations in the statistical metrics.

Analysis of PCA based compression and denoising of smart grid data under normal and fault conditions

This paper describes application of principal component analysis (PCA) based data compression approaches for smart grid (SG) data storage. PCA methods are applied and compared for steady state operations and various system fault conditions. For signals with Gaussian noise data, a variant of PCA, labelled Iterative PCA (IPCA) is applied to simulated phasor data. The phasor data is simulated for IEEE New England 30-bus system using ETAP software. The simulated data is then stored using the PCA and IPCA, which exploit the sparsity and collinearity among variables in the simulated data. The results indicate that proposed methods compress both the steady state and transient signals effectively while simultaneously removing the Gaussian noise contained in the signals.

Passivity based controller for underactuated PVTOL system

This paper proposes a control law for Planar Vertical Take Off and Landing (PVTOL) system based on feedback passivation method. The PVTOL system is a benchmark control system problem which embodies in itself many control theoretic challenges due to its nonlinear and underactuaed dynamics. Trajectory tracking of PVTOL system with its roll angle control is investigated in the paper. Stability of the PVTOL roll angle is ensured by the property that the equilibrium point of a passive system always remains stable. The equivalence of PVTOL dynamics with the pendulum dynamics is exploited to design a simple passivity based feedback controller. The proposed framework interprets PVTOL dynamics as pendulum dynamics and integrator systems whose interconnection can be made passive under the action of the designed control law. The forces exerted by the actuators can be synthesized from the control law.

Dynamics and control of 2D SpiderCrane: A controlled Lagrangian approach

In this paper we present control of a multicable suspended mechanism called the ‘2D SpiderCrane’ based on controlled Lagrangian approach. SpiderCrane does not have any conventional heavy mobile components by virtue of which high transfer speeds are achievable. Using the method of controlled Lagrangian a control law is developed based on continuous-time kinetic and potential energy shaping. Simulations are carried out in MATLAB.

Neural Network Based Early Warning System for an Emerging Blackout in Smart Grid Power Networks

Worldwide power blackouts have attracted great attention of researchers towards early warning techniques for cascading failure in power grid. The key issue is how to analyse, predict and control cascading failures in advance and prevent system against emerging blackouts. This paper proposes a model which analyse power flow of the grid and predict cascade failure in advance with the integration of Artificial Neural Network (ANN) machine learning tool. The Key contribution of this paper is to introduce machine learning concept in early warning system for cascade failure analysis and prediction. Integration of power flow analysis with ANN machine learning tool has a potential to make present system more reliable which can prevent the grid against blackouts. An IEEE 30 bus test bed system has been modeled in powerworld and used in this paper for preparation of historical blackout data and validation of proposed model. The proposed model is a step towards realizing smart grid via intelligent ANN prediction technique.