A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

Multiscale coupling and multiphysics approaches in earth sciences : applications

Geoscientists are confronted with the challenge of assessing nonlinear phenomena that result from multiphysics coupling across multiple scales from the quantum level to the scale of the earth and from femtoseconds to the 4.5 Ga of history of our planet. We neglect in this review electromagnetic modelling of the processes in the Earth’s core, and focus on four types of couplings that underpin fundamental instabilities in the Earth. These are thermal (T), hydraulic (H), mechanical (M) and chemical (C) processes which are driven and controlled by the transfer of heat to the Earth’s surface. Instabilities appear as faults, folds, compaction bands, shear/fault zones, plate boundaries and convective patterns. Convective patterns emerge from buoyancy overcoming viscous drag at a critical Rayleigh number. All other processes emerge from non-conservative thermodynamic forces with a critical critical dissipative source term, which can be characterised by the modified Gruntfest number Gr. These dissipative processes reach a quasi-steady state when, at maximum dissipation, THMC diffusion (Fourier, Darcy, Biot, Fick) balance the source term. The emerging steady state dissipative patterns are defined by the respective diffusion length scales. These length scales provide a fundamental thermodynamic yardstick for measuring instabilities in the Earth. The implementation of a fully coupled THMC multiscale theoretical framework into an applied workflow is still in its early stages. This is largely owing to the four fundamentally different lengths of the THMC diffusion yardsticks spanning micro-metre to tens of kilometres compounded by the additional necessity to consider microstructure information in the formulation of enriched continua for THMC feedback simulations (i.e., micro-structure enriched continuum formulation). Another challenge is to consider the important factor time which implies that the geomaterial often is very far away from initial yield and flowing on a time scale that cannot be accessed in the laboratory. This leads to the requirement of adopting a thermodynamic framework in conjunction with flow theories of plasticity. This framework allows, unlike consistency plasticity, the description of both solid mechanical and fluid dynamic instabilities. In the applications we show the similarity of THMC feedback patterns across scales such as brittle and ductile folds and faults. A particular interesting case is discussed in detail, where out of the fluid dynamic solution, ductile compaction bands appear which are akin and can be confused with their brittle siblings. The main difference is that they require the factor time and also a much lower driving forces to emerge. These low stress solutions cannot be obtained on short laboratory time scales and they are therefore much more likely to appear in nature than in the laboratory. We finish with a multiscale description of a seminal structure in the Swiss Alps, the Glarus thrust, which puzzled geologists for more than 100 years. Along the Glarus thrust, a km-scale package of rocks (nappe) has been pushed 40 km over its footwall as a solid rock body. The thrust itself is a m-wide ductile shear zone, while in turn the centre of the thrust shows a mm-cm wide central slip zone experiencing periodic extreme deformation akin to a stick-slip event. The m-wide creeping zone is consistent with the THM feedback length scale of solid mechanics, while the ultralocalised central slip zones is most likely a fluid dynamic instability.

A vibrational spectroscopic study of the phosphate mineral lulzacite Sr2Fe2+(Fe2+,Mg)2Al4(PO4)4(OH)10

The mineral lulzacite from Saint-Aubin des Chateaux mine, France, with theoretical formula Sr2Fe2+(Fe2+,Mg)2Al4(PO4)4(OH)10 has been studied using a combination of electron microscopy with EDX and vibrational spectroscopic techniques. Chemical analysis shows a Sr, Fe, Al phosphate with minor amounts of Ga, Ba and Mg. Raman spectroscopy identifies an intense band at 990 cm�1 with an additional band at 1011 cm�1. These bands are attributed to the PO3� 4 m1 symmetric stretching mode. The m3 antisymmetric stretching modes are observed by a large number of Raman bands. The Raman bands at 1034, 1051, 1058, 1069 and 1084 together with the Raman bands at 1098, 1116, 1133, 1155 and 1174 cm�1 are assigned to the m3 antisymmetric stretching vibrations of PO3� 4 and the HOPO2� 3 units. The observation of these multiple Raman bands in the symmetric and antisymmetric stretching region gives credence to the concept that both phosphate and hydrogen phosphate units exist in the structure of lulzacite. The series of Raman bands at 567, 582, 601, 644, 661, 673 and 687 cm�1 are assigned to the PO3� 4 m2 bending modes. The series of Raman bands at 437, 468, 478, 491, 503 cm�1 are attributed to the PO3� 4 and HOPO2� 3 m4 bending modes. No Raman bands of lulzacite which could be attributed to the hydroxyl stretching unit were observed. Infrared bands at 3511 and 3359 cm�1 are ascribed to the OH stretching vibration of the OH units. Very broad bands at 3022 and 3299 cm�1 are attributed to the OH stretching vibrations of water. Vibrational spectroscopy offers insights into the molecular structure of the phosphate mineral lulzacite.

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

From nucleation to nanowires : a single-step process in reactive plasmas

This feature article introduces a deterministic approach for the rapid, single-step, direct synthesis of metal oxide nanowires. This approach is based on the exposure of thin metal samples to reactive oxygen plasmas and does not require any intervening processing or external substrate heating. The critical roles of the reactive oxygen plasmas, surface processes, and plasma-surface interactions that enable this growth are critically examined by using a deterministic viewpoint. The essentials of the experimental procedures and reactor design are presented and related to the key process requirements. The nucleation and growth kinetics is discussed for typical solid-liquid-solid and vapor-solid-solid mechanisms related to the synthesis of the oxide nanowires of metals with low (Ga, Cd) and high (Fe) melting points, respectively. Numerical simulations are focused on the possibility to predict the nanowire nucleation points through the interaction of the plasma radicals and ions with the nanoscale morphological features on the surface, as well as to control the localized 'hot spots' that in turn determine the nanowire size and shape. This generic approach can be applied to virtually any oxide nanoscale system and further confirms the applicability of the plasma nanoscience approaches for deterministic nanoscale synthesis and processing.

Grid-side cascade inverter system as an interface for wind energy storage

Additional converters that are used to interface energy storage devices incur power losses as well as increased system cost and complexity. The need for additional converters can be eliminated if the grid side inverter can itself be effectively used as the interface for energy storage. This paper therefore proposes a technique whereby the grid side inverter can also be used as an interface to connect a supercapacitor energy storage for wind energy conversion systems. The proposed grid side inverter is formed by cascading a 3-level inverter and a 2-level inverter through a coupling transformer. The three-level inverter is the main inverter and it is powered by the rectified output of the wind turbine coupled AC generator while the 2-level auxiliary inverter is connected to the super capacitor bank that is used to compensate short term power fluctuations. Novel modulation and control techniques are proposed to address the problems associated with non-integer and dynamically-changing dc-link voltage ratio, which is caused by the random nature of wind. Simulation results are presented to verify the efficacy of the proposed system in suppressing short term wind power fluctuations.

A Battery Energy Storage interface for wind power systems with the use of grid side inverter

This paper presents a novel concept of Energy Storage System (ESS) interfacing with the grid side inverter in wind energy conversion systems. The inverter system used here is formed by cascading a 2-level inverter and a three level inverter through a coupling transformer. The constituent inverters are named as the “main inverter” and the “auxiliary inverter” respectively. The main inverter is connected with the rectified output of the wind generator while the auxiliary inverter is attached to a Battery Energy Storage System (BESS). The BESS ensures constant power dispatch to the grid irrespective of change in wind condition. Furthermore, this unique combination of BESS and inverter eliminates the need of additional dc-dc converters. Novel modulation and control techniques are proposed to address the problem of non-integer, dynamically-changing dc-link voltage ratio, which is due to random wind changes. Strategies used to handle auxiliary inverter dc-link voltage imbalances and controllers used to charge batteries at different rates are explained in detail. Simulation results are presented to verify the efficacy of the proposed modulation and control techniques in suppressing random wind power fluctuations.

A business perspective of legacy systems

Abstract Legacy information systems evolved incrementally in response to changes in business strategy and information technology. Organizations are now being forced to change much more radically and quickly than previously and this change places new demands on information systems. Legacy information systems are usually considered from a technical perspective, addressing issues such as age, complexity, maintainability, design and technology. We wish to demonstrate that the business dimension to legacy information systems, represented by the organisation structure, business processes and procedures that are bound up in the design and operation of the existing IT systems, is also significant. This paper identifies the important role of legacy information systems in the formation of new strategies. We show that the move away from a stable to an unstable business environment accelerates the rate of change. Furthermore, the gap between what the legacy information systems can deliver and the strategic vision of the organization widens when the legacy information systems are unable to adapt to meet the new requirements. An analysis of fifteen case studies provides evidence that legacy information systems include business and technical dimensions and that the systems can present problems when there is a misalignment between the strategic vision of the business, the IT legacy and the old business model embodied in the legacy.

Building energy simulation and parallel computing : opportunities and challenges

Increased focus on energy cost savings and carbon footprint reduction efforts improved the visibility of building energy simulation, which became a mandatory requirement of several building rating systems. Despite developments in building energy simulation algorithms and user interfaces, there are some major challenges associated with building energy simulation; an important one is the computational demands and processing time. In this paper, we analyze the opportunities and challenges associated with this topic while executing a set of 275 parametric energy models simultaneously in EnergyPlus using a High Performance Computing (HPC) cluster. Successful parallel computing implementation of building energy simulations will not only improve the time necessary to get the results and enable scenario development for different design considerations, but also might enable Dynamic-Building Information Modeling (BIM) integration and near real-time decision-making. This paper concludes with the discussions on future directions and opportunities associated with building energy modeling simulations.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Dual-functional gum arabic binder for silicon anodes in lithium ion batteries

Si has attracted enormous research and manufacturing attention as an anode material for lithium ion batteries (LIBs) because of its high specific capacity. The lack of a low cost and effective mechanism to prevent the pulverization of Si electrodes during the lithiation/ delithiation process has been a major barrier in the mass production of Si anodes. Naturally abundant gum arabic (GA), composed of polysaccharides and glycoproteins, is applied as a dualfunction binder to address this dilemma. Firstly, the hydroxyl groups of the polysaccharide in GA are crucial in ensuring strong binding to Si. Secondly, similar to the function of fiber in fiberreinforced concrete (FRC), the long chain glycoproteins provide further mechanical tolerance to dramatic volume expansion by Si nanoparticles. The resultant Si anodes present an outstanding capacity of ca. 2000 mAh/g at a 1 C rate and 1000 mAh/g at 2 C rate, respectively, throughout 500 cycles. Excellent long-term stability is demonstrated by the maintenance of 1000 mAh/g specific capacity at 1 C rate for over 1000 cycles. This low cost, naturally abundant and environmentally benign polymer is a promising binder for LIBs in the future.

Systematic constellations of neurons are activated in lateral amygdala following Pavlovian fear conditioning

How memory is organized within neural networks is a fundamental question in neuroscience. We used Pavlovian fear conditioning to study the discrete organization patterns of neurons activated in an associative memory paradigm. In Pavlovian fear conditioning a neutral stimulus, such as an auditory tone, is temporally paired with an aversive unconditioned stimulus (US), such as a foot shock...