Tracking and surveillance in wide-area spatial environments using the abstract hidden markov model.

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of the well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.

Robust abandoned object detection integrating wide area visual surveillance and social context

This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner).

A probabilistic framework for tracking in wide-area environments

Surveillance in wide-area spatial environments is characterised by complex spatial layouts, large state space, and the use of multiple cameras/sensors. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. This requirement is particularly suited to the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN). In this paper, we propose the use of LDPN as the integrated framework for tracking in wide-area environments. We illustrate, with the help of a synthetic tracking scenario, how the parameters of the LDPN can be estimated from training data, and then used to draw predictions and answer queries about unseen tracks at various levels of detail.

Correction of systematic errors in Wide Area Multilateration

This work presents a method to estimate and correct slow time-dependent position errors due to non perfect ground station synchronization and tropospheric propagation. It uses opportunity traffic emissions, i.e. signals transmitted from the aircrafts within the coverage zone. This method is used to overcome the difficulty of installing reference beacons simultaneously visible by all the base stations in a given Wide Area Multilateration (WAM) system.

A wide area monitoring system based load restoration method

Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

Wide area control through aggregation of power systems

This thesis was a step forward in improving the stability of power systems by applying new control and modelling techniques. The developed methods use the data obtained from voltage angle measurement devices which are synchronized with GPS signals to stabilize the system and avoid system-wide blackouts in the event of severe faults. New approaches were developed in this research for identifying and estimating reduced dynamic system models using phasor measurement units. The main goal of this research is achieved by integrating the developed methods to obtain a feasible wide-area control system for stabilizing the power systems.

Utilizing Wide-Area Signals for off-center SVCs to damp interarea oscillations

Wide-Area Measurement Systems (WAMS) provide the opportunity of utilizing remote signals from different locations for the enhancement of power system stability. This paper focuses on the implementation of remote measurements as supplementary signals for off-center Static Var Compensators (SVCs) to damp inter-area oscillations. Combination of participation factor and residue method is used for the selection of most effective stabilizing signal. Speed difference of two generators from separate areas is identified as the best stabilizing signal and used as a supplementary signal for lead-lag controller of SVCs. Time delays of remote measurements and control signals is considered. Wide-Area Damping Controller (WADC) is deployed in Matlab Simulink framework and is tested under different operating conditions. Simulation results reveal that the proposed WADC improve the dynamic characteristic of the system significantly.

Wide-area control of aggregated power systems

This paper proposes a new method for stabilizing disturbed power systems using wide area measurement and FACTS devices. The approach focuses on both first swing and damping stability of power systems following large disturbances. A two step control algorithm based on Lyapunov Theorem is proposed to be applied on the controllers to improve the power systems stability. The proposed approach is simulated on two test systems and the results show significant improvement in the first swing and damping stability of the test systems.

Wide area controls for transient and dynamic stability enhancement

This paper presents a study done into the effectiveness of using local acceleration measurements vs. remote angle measurements in providing stabilising control via SVCs following large disturbances. The system studied was an analogue of the Queensland-New South Wales Interconnection (QNI) and involved the control of an existing Static Var Compensators (SVC) at Sydney West. This study is placed in the context of wide area controls for large systems using aggregated models for groups of machines.

Wide area control of SVCs for first swing stabilisation and damping in longitudinal systems

A non-linear Kalman filter based control strategy for SVCs located in major load groups is presented. This focusses on the limitation and damping of inter-area modes. It does this through treating local modes as noise and uses a tunable nonlinear control algorithm to improve both first swing stability and system damping. Simulation on a four machine system shows that the Kalman filer can successfully lock on to a desired inter-area mode and obtain a 31% improvement in critical clearing time as well as improved damping.

Wide-area damping control for inter-area oscillations using inverse filtering technique

In this study, a non-linear excitation controller using inverse filtering is proposed to damp inter-area oscillations. The proposed controller is based on determining generator flux value for the next sampling time which is obtained by maximising reduction rate of kinetic energy of the system after the fault. The desired flux for the next time interval is obtained using wide-area measurements and the equivalent area rotor angles and velocities are predicted using a non-linear Kalman filter. A supplementary control input for the excitation system, using inverse filtering approach, to track the desired flux is implemented. The inverse filtering approach ensures that the non-linearity introduced because of saturation is well compensated. The efficacy of the proposed controller with and without communication time delay is evaluated on different IEEE benchmark systems including Kundur's two area, Western System Coordinating Council three-area and 16-machine, 68-bus test systems.

Real-time wide-area loading margin sensitivity (WALMS) in power systems

Loading margin sensitivity (LMS) has been widely used in applications in the realm of voltage stability assessment and control. Typically, LMS is derived based on system equilibrium equations near bifurcation and therefore requires full detailed system model and significant computation effort. Availability of phasor measurement units (PMUs) due to the recent development of wide-area monitoring system (WAMS) provides an alternative computation-friendly approach for calculating LMS. With such motivation, this work proposes measurement-based wide-area loading margin sensitivity (WALMS) in bulk power systems. The proposed sensitivity, with its simplicity, has great potential to be embedded in real-time applications. Moreover, the calculation of the WALMS is not limited to low voltage near bifurcation point. A case study on IEEE 39-bus system verifies the proposed sensitivity. Finally, a voltage control scenario demonstrates the potential application of the WALMS.

Wide area kinematic positioning with BeiDou triple frequency signals

A key challenge of wide area kinematic positioning is to overcome the effects of the varying hardware biases in code signals of the BeiDou system. Based on three geometryfree/ionosphere-free combinations, the elevation-dependent code biases are modelled for all BeiDou satellites. Results from the data sets of 30-day for 5 baselines of 533 to 2545 km demonstrate that the wide-lane (WL) integer-fixing success rates of 98% to 100% can be achieved within 25 min. Under the condition of HDOP of less than 2, the overall RMS statistics show that ionospheric-free WL single-epoch solutions achieve 24 to 50 cm in the horizontal direction. Smoothing processing over the moving window of 20 min reduces the RMS values by a factor of about 2. Considering distance-independent nature, the above results show the potential that reliable and high precision positioning services could be provided in a wide area based on a sparsely distributed ground network.