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© 2020 Elsevier Ltd Leveraging on graph automorphic properties of complex networks (CNs), this study investigates three robustness aspects of CNs including the robustness of controllability, disturbance decoupling, and fault tolerance against failure in a network element. All these aspects are investigated using a quantified notion of graph symmetry, namely the automorphism group, which has been found implications for the network controllability during the last few years. The typical size of automorphism group is very big. The study raises a computational issue related to determining the whole set of automorphism group and proposes an alternative approach which can attain the emergent symmetry characteristics from the significantly smaller groups called generators of automorphisms. Novel necessary conditions for network robust controllability following a failure in a network element are attributed to the properties of the underlying graph symmetry. Using a symmetry related concept called determining set and a geometric control property called controlled invariant, the new necessary and sufficient conditions for disturbance decoupling are proposed. In addition, the critical nodes/edges of the network are identified by determining their role in automorphism groups. We verify that nodes with more repetition in symmetry groups of the network are more critical in characterizing the network robustness. Further, the impact of elimination of critical network elements on its robustness is analyzed by calculating a new improved index of symmetry which considers the orbital impacts of automorphisms. The importance of all symmetry inspired findings of this paper is highlighted via simulation on various networks.

Optimal placement of flexible AC transmission systems (FACTS) devices and the cyber-security of associated data exchange are crucial for the controllability of wide area power networks. The placement of FACTS devices is studied in this paper from a novel graph theoretic perspective, which unlike the existing approaches, purely relies on topological characteristics of the underlying physical graphs of power networks. To this end, the maximum matching principle (MMP) is used to find the set of required FACTS devices for the grid controllability. In addition, the cyber-security of the most critical data related to the FACTS controllers is guaranteed by introducing the concept of moderated- k -security where k is a measure of data obscurity from the adversary perspective. The idea of moderated- k -symmetry is proposed to facilitate the arrangement of the published cyber graph based on a permutation of nodes within the symmetry group of the grid, called generator of automorphism. It is then verified that the published cyber-graph can significantly obscure the data exchange over the cyber graph for adversaries. Finally, a similarity is observed and demonstrated between the set of critical nodes attained from the symmetry analysis and the solution of the FACTS devices placement that further highlights the importance of symmetry for the analysis and design of complex power networks. Detailed simulations are applied to three power networks and analyzed to demonstrate the performance and eligibility of the proposed methods and results.

This paper proposes analytical approaches to extend the capacity of existing networks of electric vehicles (EVs) by placement of additional charging stations (CSs) as well as determining the sizes of existing and new CSs in order to handle future expansions of EVs. The EV flow at CSs is modeled by a graph where nodes are potential locations for CSs and edges are uncertain parameters representing the variable EV flow at CSs. The required extra CS locations are explored by transforming the CS placement problem into a controllability framework addressed by maximum matching principle (MMP). To find the sizes of each CS, the graph of CS network is partitioned featuring only one CS in each subgraph. The size of CS in each subgraph is then determined by transforming the problem into the problem of robust stability of a system with uncertain parameters where each parameter is associated with an edge of subgraph. The zero exclusion principle is then tested for the related Kharitonov rectangles and polygonal polynomials of closed loop system with selected feedback gain as CS capacity. The proposed analytical approach is tested on the existing Tesla CS Network of Sydney. The locations of extra required CSs as well as the sizes of existing and new CSs are determined to maintain the waiting times at all stations below the threshold level.

This paper proposes a novel graph-based approach with automorphic grouping for the modelling, synthesis, and analysis of electric vehicle (EV) networks with charging stations (CSs) that considers the impacts of traffic. The EV charge demands are modeled by a graph where nodes are positioned at potential locations for CSs, and edges represent traffic flow between the nodes. A synchronization protocol is assumed for the network where the system states correspond to the waiting time at each node. These models are then utilized for the placement and sizing of CSs in order to limit vehicle waiting times at all stations below a desirable threshold level. The main idea is to reformulate the CS placement and sizing problems in a control framework. Moreover, a strategy for the deployment of portable charging stations (PCSs) in selected areas is introduced to further improve the quality of solutions by reducing the overshooting of waiting times during peak traffic hours. Further, the inherent symmetry of the graph, described by graph automorphisms, are leveraged to investigate the number and positions of CSs. Detailed simulations are performed for the EV network of Perth Metropolitan in Western Australia to verify the effectiveness of the proposed approach.

This paper presents the Particle Swarm Optimization (PSO) algorithm to improve the quality of the power supply in a microgrid. This algorithm is proposed for a real-time selftuning method that used in a power controller for an inverter based Distributed Generation (DG) unit. In such system, the voltage and frequency are the main control objectives, particularly when the microgrid is islanded or during load change. In this work, the PSO algorithm is implemented to find the optimal controller parameters to satisfy the control objectives. The results show high performance of the applied PSO algorithm of regulating the microgrid voltage and frequency.

The paper presents a novel method of evaluating the square root function in FPGA. The method uses a linear approximation subsystem with a reduced size of a look-up table. The reduction in the size of the lookup table is twofold. Firstly, a simple linear approximation subsystem uses the lookup table only for the node points. Secondly, a concept of a variable step look-up table is introduced, where the node points are not uniformly spaced, but the spacing is determined by how close to the linear function the approximated function is. The proposed method of evaluating nonlinear function and specifically the square root function is practical for word lengths of up to 24 bits. The evaluation is performed in one clock cycle.

Mobile multimedia communication has rapidly become a significant area of research and development. The processing requirements for the capture, conversion, compression, decompression, enhancement, display, etc. of high quality multimedia content places heavy demands even on current ULSI (ultra large scale integration) systems, particularly for mobile applications where area and power are primary considerations. The system presented is designed as a vertically integrated (3D) system comprising two distinct layers bonded together using indium bump technology. The top layer is a CMOS imaging array containing analog-to-digital converters, and a buffer memory. The bottom layer takes the form of a configurable array processor (CAP), a highly parallel array of soft programmable processors capable of carrying out complex processing tasks directly on data stored in the top plane. Until recently, the dominant format of data in imaging devices has been analog. The analog photocurrent or sampled voltage is transferred to the ADC via a column or a column/row bus. In the proposed system, an array of analog-to-digital converters is distributed, so that a one-bit cell is associated with one sensor. The analog-to-digital converters are algorithmic current-mode converters. Eight such cells are cascaded to form an 8-bit converter. Additionally, each photosensor is equipped with a current memory cell, and multiple conversions are performed with scaled values of the photocurrent for colour processing.

A superconducting magnetic energy storage (SMES) system containsa high inducting coil and combines with power conversion system can act as a constant source of direct current. SMES unit connected to a power system is able to absorb and store both active and reactive power from this system and to inject these powers into the power system in the demand periods. These injected powers are controlled by changing both the duty cycle of the dc-dc chopper switches and its operation modes. This paper presents an efficient design based on an SMES unit controlled by the artificial neural network (ANN) to improve transient stability by regulating the dc link voltage and to damp the voltage and frequency fluctuations that are always associated with wind power generator. The authors propose interfacing the SMES between wind power farm and the power grid connected through the DC Link capacitor to rapidly stabilize the voltage and frequency fluctuations in the power system.The system behavior is tested with three different events for both voltage and frequency fluctuations of wind power generation with and without applying the SMES unit. The results show that both voltage and frequency stabilities are significantly increased when the SMES unit is applied in these three events.

A superconducting Magnetic Energy Storage (SMES) includes a high inductance coil that can act as a constant source of direct current. A SMES unit connected to a power system is able to absorb and store both active and reactive power from this system and to inject these powers into this system when they are needed. The injected power can be controlled by changing both the duty cycle of the dc-dc chopper switches and its operation modes. A SMES is always associated with a power conversion system consisting of two identical converters connected by a de link capacitor. This paper presents an efficient system, based on a SMES unit, to improve transient stability by regulating the dc link voltage to reduce the voltage and frequency fluctuations that occur after disturbances or rapid load changes. The authors propose using a SMES as an interface device connected to the DC Link capacitor and located between the power supply and load sides to act as a universal stabilizer of voltage and frequency on both sides. The system behavior is tested with three faults/events for both power supply and load with and without applying the SMES unit. The results show that the SMES unit increases the dc link voltage stability significantly whenever any of these three events occur.

This paper presents an optimal power control strategy, for an inverter based Distributed Generation (DG) unit, in an autonomous microgrid operation based on real-time self-tuning method. This research seeks to improve the quality of power supplied by DG units connected to the grid. Voltage and frequency regulation, dynamic response, steady-state response, and harmonic distortion are the main performance parameters considered, particularly when the microgrid is islanded or under the load change condition. The controller scheme comprises an inner current control loop and an outer power control loop based on a synchronous reference frame and conventional PI regulators. The power controller is designed for voltage-frequency (Vf) power control mode. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that when the microgrid is islanded or under load change condition, the DG unit adopts the Vf control mode in order to regulate the system voltage and frequency. The simulation results show that the proposed controller provided an excellent response to satisfy the power quality requirements and proved the validity of the proposed strategy.

This paper presents an optimal power flow controller for a utility connected microgrid based on a real-time self-tuning method. The purpose is to control the flow of the active and reactive power between the main grid and the microgrid composed of Distributed Generation (DG) units. Sharing power at the desired ratio by the DG units is the main performance parameter which is considered during the load change. This paper also shows the response of the controller in situations, where the load is either higher or greatly lower than the rated power of the DG unit. In this work, the controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. The power controller is designed for active-reactive power (PQ) control strategy. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that the required load power is shared equally between the microgrid and the utility based on the PSO algorithm during the load change. The utility supplies the difference power when the load is more than the power generated by the microgrid, while it injects the extra power to the grid when the load is less than the power generated by the microgrid. The results show that the proposed controller offers an excellent response and proves the validity of the proposed strategy.

In this paper COMSOL model is used to model the s-parameters of the electromagnetic shielding of layer/layers of Polyaniline (PAni) for Wi-Fi Electromagnetic Interference (EMI) shielding. PAni has a good future for minimizing the problems with Electromagnetic Shielding (EMS), and will be increasingly be used to provide protection from Electromagnetic Radiation (EMR) and Electromagnetic Interference (EMI). With the increased development in Wi-Fi and telecommunications equipment, a simple model is required to test for transmission losses. In this paper the electromagnetic radiation from antenna, positioned 30cm from PAni shielding device is modelled using COMSOL 4.2. The paper predicts the radiation reduction after using PAni shielding device. The prediction of electromagnetic radiation distribution with PAni shielding device is simulated, the focus of the simulation is on the Wi-Fi microwave frequency of 2.45 GHz and the modelling of the PAni as an Intrinsic Conducting Polymer (ICP) for transmission losses that was obtained from the COMSOL simulation is compared with PAni shielding test data obtained from the experiential set up. The COMSOL model is used to predict both the electric field intensity around the PAni material and establish the plot of transmission losses.

In this paper COMSOL model is used to model the s-parameters of the electromagnetic shielding of layer/layers of Polyaniline (PAni) for Wi-Fi Electromagnetic Interference (EMI) shielding. PAni has a good future for minimizing the problems with Electromagnetic Shielding (EMS), and will be increasingly be used to provide protection from Electromagnetic Radiation (EMR) and Electromagnetic Interference (EMI). With the increased development in Wi-Fi and telecommunications equipment, a simple model is required to test for transmission losses. In this paper the electromagnetic radiation from antenna, positioned 30cm from PAni shielding device is modelled using COMSOL 4.2. The paper predicts the radiation reduction after using PAni shielding device. The prediction of electromagnetic radiation distribution with PAni shielding device is simulated, the focus of the simulation is on the Wi-Fi microwave frequency of 2.45 GHz and the modelling of the PAni as an Intrinsic Conducting Polymer (ICP) for transmission losses that was obtained from the COMSOL simulation is compared with PAni shielding test data obtained from the experiential set up. The COMSOL model is used to predict both the electric field intensity around the PAni material and establish the plot of transmission losses.

Developing a good demand forecasting model is the art of identifying the best modelling parameters. Improving the forecasting performance needs to study the input/output parameters of the system to identify the effective forecasting variables. In this paper, the energy demand of Joondalup Campus of Edith Cowan University (ECU) in Western Australia has been selected as a case study for the design and verification of a suitable forecasting model. Fuzzy Subtractive Clustering Method (FSCM) based Adaptive Neuro Fuzzy Inference System (ANFIS) is used as a proposed modelling network in this paper. Basically, three-input forecasting models have been developed based on 12-month models to perform ECU energy demand forecasting. The input/output parameters selection was made after analysing the historical demand pattern in ECU energy system. Generally, increasing the number inputs in model network may have wider training scope and better forecasting accuracy. However, the wrong choice of the additional input would deteriorate the forecasting accuracy. From analysing the historical operation of ECU energy system, four and five-input variables could be identified and modelling has been performed. The result show that four-input models were the best in the prediction performance among 12-month models of the annual demand predicion of ECU.

A robust current control strategy for PV (photovoltaic) grid-connected systems is required for reliable use of solar energy as an abundant and clean renewable energy. This paper presents real time optimization parameters of the current control strategy for a 3-phase photovoltaic grid-connected Voltage Source Inverter (VSI) system. The proposed controller scheme is implemented based on a synchronous reference frame; the Phase-Locked Loop (PLL) is used as grid phase detector. Particle Swarm Optimization (PSO) algorithm is an intelligent searching algorithm that is used to implement the real time self-tuning method for the current control parameters. Two conventional PI controllers are used and feed-forward compensation is applied with the inner inverter current control loop to achieve fast dynamic response. The main aim of this work is to achieve high dynamic response for the inverter output current with acceptable harmonics level in steady-state condition all of which is required for power quality improvement. The results show that the proposed strategy provides an excellent dynamic response within real time optimization.

In this paper, a Tuning Fuzzy System (TFS) is used to improve the energy demand forecasting for a medium-size microgrid. As a case study, the energy demand of the Joondalup Campus of Edith Cowan University (ECU) in Western Australia is modelled. The developed model is required to perform economic dispatch for the ECU microgrid in islanding mode. To achieve an active economic dispatch demand prediction model, actual load readings are considered. A fuzzy tuning mechanism is added to the prediction model to enhance the prediction accuracy based on actual load changes. The demand prediction is modelled by a Fuzzy Subtractive Clustering Method (FSCM) based Adaptive Neuro Fuzzy Inference System (ANFIS). Three years of historical load data which includes timing information is used to develop and verify the prediction model. The TFS is developed from the knowledge of the error between the actual and predicted demand values to tune the prediction output. The results show that the TFS can successfully tune the prediction values and reduce the error in the subsequent prediction iterations. Simulation results show that the proposed prediction model can be used for performing economic dispatch in the microgrid.

This paper presents an optimal power control strategy for an autonomous microgrid operation based on a real-time self-tuning method. The purpose of this work is to improve the quality of power supply where Distributed Generation (DG) units are connected to the grid. Dynamic response and harmonics distortion are the two main performance parameters which are considered in this work, particularly when the microgrid is islanded. The controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the system. The results show that the proposed controller provides an excellent dynamic response with acceptable harmonics level.

This paper presents a novel method of reducing the spurious signal content in a digitally synthesized sine wave at the output of a numerically controlled oscillator (NCO). The proposed method uses a linear approximation subsystem with a reduced size look-up table (LUT). Two NCO architectures are considered. Architecture 0 - which is the standard - in which the accumulator word length is longer than the LUT address word, is compared with Architecture 1, where the accumulator bits beyond the LUT address space are used for the linear approximation of the value in between the entries of the LUT. Analysis of both architectures demonstrates that the spurious free dynamic range (SFDR) in Architecture 1 equates to 12 dBc per bit of the address space of the LUT as opposed to 6 dBc for Architecture 0. The system was implemented and tested using the Xilinx Spartan 3 platform.

We propose a joint optimization model for capacity design of networks with p-cycles. The model is based on a modified definition of network fundamental cycles and the available straddling links. Concepts about visible and hidden straddling links, which are essential components of our model are also introduced. This is the first ILP model for joint optimization of p-cycle network that can be solved without enumerating p-cycle candidates, and has the ability to achieve optimum solutions. In addition, the complexity of our proposed model is much smaller than any conventional models, particularly when applying to a planar network. This model is suitable large size networks and for shared risk link group networks or backbone networks protected by p-cycle schemes.

This paper introduces a novel 3-Dimensional (3D) vertically integrated adaptive computing system. This 3D-SoftChip is a combination of state-of-the-art processing and interconnection technology. It comprises the vertical integration of two chips (a Configurable Array Processor and an Intelligent Configurable Switch) through indium bump 3D interconnections. The Configurable Array Processor (CAP) is an array of heterogeneous processing elements (PEs) while the Intelligent Configurable Switch (ICS) comprises a switch block, 32-bit dedicated RISC processor for control, on-chip program/data memory, data frame buffer along with a Direct Memory Access (DMA) controller. This paper introduces the 3D-Softchip architecture for real-time communication and multimedia signal processing as a next generation computing system and describes the HW/SW codesign and verification methodology using SystemC.

The crosstalk in CMOS photodiodes has been measured, at two wavelengths of 543 and 633 nm, by an experimental structure containing several types of photodiodes with varying dimensions. The role of the design of the junction in reducing crosstalk is studied. The measurements indicate that to reduce crosstalk it is essential to optically shield the gap between junctions and to reverse bias the adjacent junctions. Crosstalk is significantly reduced in double-junction photodiodes, but at the cost of lower quantum efficiency. The results indicate that with properly designed layout, the crosstalk may be small. However, there is a tradeoff between small crosstalk, reduced fill factor and quantum efficiency.

The Australian Commonwealth government recently announced a grant of $4.75 million as part of a $13.5 million program to establish a world class networked IC tele-test facility in Australia. The facility will be based on a state-of-the-art semiconductor tester located at Edith Cowan University in Perth that will operate as a virtual centre spanning Australia. Satellite nodes will be located at the University of Western Australia, Griffith University, Macquarie University, Victoria University and the University of Adelaide. The facility will provide vital equipment to take Australia to the frontier of critically important and expanding fields in microelectronics research and development. The tele-test network will provide state of the art environment for the electronics and microelectronics research and the industry community around Australia to test and prototype Very Large Scale Integrated (VLSI) circuits and other System On a Chip (SOC) devices, prior to moving to the manufacturing stage. Such testing is absolutely essential to ensure that the device performs to specification. This paper presents the current context in which the testing facility is being established, the methodologies behind the integration of design and test strategies and the target shape of the tele-testing Facility.