Alison Griffiths

Simulation of Distributed Wireless Networked Control Systems over MANET using OPNET

This paper investigates the simulation of distributed wireless networked control systems (WNCS) over mobile ad-hoc network (MANET). The simulation model includes multiple plants with a single controller and random node mobility. The widely used network simulation software optimised network engineering tool (OPNET) has been utilised to implement a realistic wireless signal propagation model using path loss and fading effects. System performances for two ad-hoc network routing protocols: DSR and AODV have been explored.

An Interface between MATLAB and OPNET to Allow Simulation of WNCS with MANETs

MATLAB is a software simulator which is good for simulating the mathematical modeling and feedback control, while OPNET is a software tool which is good for simulating the network communication behavior. However, currently simulating the communication behavior of a wireless ad hoc network within MATLAB is difficult, where complex queuing models in OPNET are also difficult to create and manipulate. In this paper, we have created an interface between MATLAB and OPNET to allow MATLAB to use its strong mathematical functionality and OPNET to use its ability to manipulate network simulations.

Capacitor voltage balancing strategy based on sub-module capacitor voltage estimation for modular multilevel converters

The modular multilevel converter (MMC) is expected to be used extensively in high-voltage direct current (HVDC) transmission networks because of its superior characteristics over the line-commutated converter (LCC). A key issue of concern is balancing sub-module capacitor voltages in the MMCs, which is critical for the correct operation of these converters. The majority of voltage balancing techniques proposed thus far require that the measurement of the capacitor voltages use a reliable measuring system. This can increase the capital cost of the converters. This paper presents a voltage balancing strategy based on capacitor voltage estimation using the adaptive linear neuron (ADALINE) algorithm. The proposed estimation unit requires only three voltage sensors per phase for the arm reactors and the output phase voltages. Measurements of sub-module capacitor voltages and associated communication links with the central controller are not needed. The proposed strategy can be applied to MMC systems that contain a large number of sub-modules. The method uses PSCAD/EMTDC, with particular focus on dynamic performance under a variety of operating conditions.

Characterization of Field-of-View for Energy Efficient Application-Aware Visual Sensor Networks

Energy consumption is one of the primary concerns in a resource-constrained visual sensor network (VSN). The existing VSN design solutions under particular resource-constrained scenarios are application specific, whereas the degree of sensitivity of the resource constraints varies from one application to another. This limits the implementation of the existing energy efficient solutions within a VSN node, which may be considered to be a part of a heterogeneous network. The heterogeneity of image capture and processing within a VSN can be adaptively reflected with a dynamic field-of-view (FoV) realization. This is expected to allow the implementation of a generalized energy efficient solution to adapt with the heterogeneity of the network. In this paper, an energy efficient FoV characterization framework is proposed, which can support a diverse range of applications. The context of adaptivity in the proposed FoV characterization framework is considered to be: 1) sensing range selection; 2) maximizing spatial coverage; 3) adaptive task classification; and 4) minimizing the number of required nodes. Soft decision criteria is exploited, and it is observed that for a given detection reliability, the proposed framework provides energy efficient solutions, which can be implemented within heterogeneous networks. It is also found that the proposed design solution for heterogeneous networks leads to 49.8% energy savings compared with the trivial design solution.

Fault detection in Multi-Terminal Modular Multilevel Converter (MMC) based High Voltage DC (HVDC) transmission system

A Multi-Terminal High Voltage Direct Current (MT-HVDC) network is being considered for utilising the full potential of offshore wind power whereas its realisation is currently being hampered by protection issues. In this paper, a protection strategy for future DC grids based on Modular Multilevel Converter (MMC) based HVDC system is presented. Firstly, a fault detection technique based on initial di/dt measurement is presented and thereafter protection strategies for future DC grids are presented. The fault detection technique presented is based on estimating the initial rate of rise of the current, IRRC (di/dt) at fault inception using measured data and thereafter calculating the line inductance. The calculated line inductance is compared with a setting value to determine whether or not a fault has occurred, thus paving the way for a distance protection strategy. Simulations were carried out using Matlab/SIMULINK for varying fault distances. The results obtained show the validity of the technique in detecting and locating DC side short circuits. An advantage of this technique is that it relies only on information from the local end terminal and as such, no communication channel is required, hence satisfying the protection requirement of fast fault detection and location technique for MT-HVDC systems.

Energy Efficient Self-Reconfiguration Scheme for Visual Information Based M2M Communication

Machine-to-machine (M2M) communication is one of the latest technologies to support connectivity among numerous intelligent devices. The intelligence of M2M systems can be enhanced by incorporating visual sensor networks (VSNs) and utilising visual information. The conservation of energy within VSNs is one of the primary concerns for resource constrained scenarios, which can be achieved from targeted threshold based optimisation. However, such optimisation may impact the quality-of-information (QoI), which quantifies the degree to which the visual data is suitable for a given application. To cope with such optimisation challenges, this paper presents a self-reconfiguration scheme for visual sensor nodes to dynamically find optimal configurations as well as guaranteeing satisfactory performance to achieve the given QoI target. The optimisation is achieved by selecting suitable configurations for the removal of feature redundancy which minimises the transmission cost and results in a feasible solution that enhances the energy and bandwidth efficiency for M2M communication. The performance evaluation of the proposed scheme is carried out for different required QoI targets, and it is observed that the proposed scheme outperforms the conventional scheme by providing up to 59.21% energy savings at a QoI target of 30dB.

Detection and diagnosis of sub-module faults for modular multilevel converters

This paper presents a new fault detection technique for the diagnosis and localization of sub-module faults that are developed due to failures in switching devices inside Modular Multilevel Converters (MMC). Unlike other fault detection strategies that have been proposed in literature, the proposed fault detection technique does not need extra sensors or special power circuits as it depends on an ADAptive LINEar Neuron (ADALINE) capacitor voltage estimation algorithm. The proposed fault detection technique is validated by Hardware In the Loop (HIL) real time simulations through which different case studies are simulated to test the algorithm under different operating conditions.

Reliability enhancement of modular multilevel converter by applying fault tolerant control

Modular Multilevel Converters (MMC) are considered very suitable for the transmission of bulk power. Increasing the reliability of MMCs forms a real challenge since they are built from series connection of sub-modules. Applying the concept of fault tolerance to the MMC control system can significantly increase the reliability of the MMC as it will be available in normal as well as faulty conditions. This paper presents an analysis of the MMC reliability enhancement gained from applying different fault tolerant control techniques. The reliability is investigated through solving differential equations generated from Markov chains.

QoI-Aware Unified Framework for Node Classification and Self-Reconfiguration Within Heterogeneous Visual Sensor Networks

Due to energy and throughput constraints of visual sensing nodes, in-node energy conservation is one of the prime concerns in visual sensor networks (VSNs) with wireless transceiving capability. To cope with these constraints, the energy efficiency of a VSN for a given level of reliability can be enhanced by reconfiguring its nodes dynamically to achieve optimal configurations. In this paper, a unified framework for node classification and dynamic self-reconfiguration in VSNs is proposed. The proposed framework incorporates quality-of-information (QoI) awareness using peak signal-to-noise ratio-based representative metric to support a diverse range of applications. First, for a given application, the proposed framework provides a feasible solution for the classification of visual sensing nodes based on their field-of-view by exploiting the heterogeneity of the targeted QoI within the sensing region. Second, with the dynamic realization of QoI, a strategy is devised for selecting suitable configurations of visual sensing nodes to reduce redundant visual content prior to transmission without sacrificing the expected information retrieval reliability. The robustness of the proposed framework is evaluated under various scenarios by considering: 1) target QoI thresholds; 2) degree of heterogeneity; and 3) compression schemes. From the simulation results, it is observed that for the second degree of heterogeneity in targeted QoI, the unified framework outperforms its existing counterparts and results in up to 72% energy savings with as low as 94% reliability.

Investigation of sub-module fault types of modular multi-level converters in HVDC networks

The modular multilevel converters (MMC) form the backbone of the modern voltage source converter (VSC) based HVDC system due to their unique features. Faults within the MMC affect the performance of the HVDC system. In this paper the fault types that can occur in the MMC are investigated. The reported work focuses on sub-module faults. A nine level MMC was simulated using PSCAD/EMTDC in this investigation.