Stability analysis and control of multiple converter based autonomous microgrid

In this paper, the stability of an autonomous microgrid with multiple distributed generators (DG) is studied through eigenvalue analysis. It is assumed that all the DGs are connected through Voltage Source Converter (VSC) and all connected loads are passive. The VSCs are controlled by state feedback controller to achieve desired voltage and current outputs that are decided by a droop controller. The state space models of each of the converters with its associated feedback are derived. These are then connected with the state space models of the droop, network and loads to form a homogeneous model, through which the eigenvalues are evaluated. The system stability is then investigated as a function of the droop controller real and reac-tive power coefficients. These observations are then verified through simulation studies using PSCAD/EMTDC. It will be shown that the simulation results closely agree with stability be-havior predicted by the eigenvalue analysis.

Power quality enhanced operation and control of a microgrid based custom power park

This paper describes the operation of a microgrid that contains a custom power park (CPP). The park may contain an unbalanced and/or nonlinear load and the microgrid may contain many dis-tributed generators (DGs). One of the DGs in the microgrid is used as a compensator to achieve load compensation. A new method is proposed for current reference generation for load compensation, which takes into account the real and reactive power to be supplied by the DG connected to the compensator. The real and reactive power from the DGs and the utility source is tightly regulated assuming that dedicated communication channels are available. Therefore this scheme is most suitable in cases where the loads in CPP and DGs are physically located close to each other. The proposal is validated through extensive simulation studies using EMTDC/PSCAD software package (version 4.2).

A feasibility study for model based estimating for concrete bridges.

Designing and estimating civil concrete structures is a complex process which to many practitioners is tied to manual or semi-manual processes of 2D design and cannot be further improved by automated, interacting design-estimating processes. This paper presents a feasibility study for the development an automated estimator for concrete bridge design. The study offers a value proposition: an efficient automated model-based estimator can add value to the whole bridge design-estimating process, i.e., reducing estimation errors, shortening the duration of success estimates, and increasing the benefit of doing cost estimation when compared with the current practice. This is then followed by a description of what is in an efficient automated model-based estimator and how it should be used. Finally the process of model-based estimating is compared with the current practice to highlight the values embedded in the automated processes.

Towards a rule-based matrix for evaluating distress mechanisms in bridges

The effective management of bridge stock involves making decisions as to when to repair, remedy, or do nothing, taking into account the financial and service life implications. Such decisions require a reliable diagnosis as to the cause of distress and an understanding of the likely future degradation. Such diagnoses are based on a combination of visual inspections, laboratory tests on samples and expert opinions. In addition, the choice of appropriate laboratory tests requires an understanding of the degradation mechanisms involved. Under these circumstances, the use of expert systems or evaluation tools developed from “realtime” case studies provides a promising solution in the absence of expert knowledge. This paper addresses the issues in bridge infrastructure management in Queensland, Australia. Bridges affected by alkali silica reaction and chloride induced corrosion have been investigated and the results presented using a mind mapping tool. The analysis highights that several levels of rules are required to assess the mechanism causing distress. The systematic development of a rule based approach is presented. An example of this application to a case study bridge has been used to demonstrate that preliminary results are satisfactory.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

On feasibility of regional frequency-based emergency control plans

Decentralized and regional load-frequency control of power systems operating in normal and near-normal conditions has been well studied; and several analysis/synthesis approaches have been developed during the last few decades. However in contingency and off-normal conditions, the existing emergency control plans, such as under-frequency load shedding, are usually applied in a centralized structure using a different analysis model. This paper discusses the feasibility of using frequency-based emergency control schemes based on tie-line measurements and local information available within a control area. The conventional load-frequency control model is generalized by considering the dynamics of emergency control/protection schemes and an analytic approach to analyze the regional frequency response under normal and emergency conditions is presented.

Situated case-based reasoning as a constructive memory model for design reasoning

This paper describes an extended case-based reasoning model that addresses the notion of situatedness in designing through constructive memory. The model is illustrated through an application for predicting the corrosion rate for a specific material on a specific building.

Transitioning students to work through authentic employment-based training in an Australian senior secondary VET program.

A common challenge among OECD countries has been the development of education and training pathways that accommodate student needs and interests at the upper secondary level (OECD, 2000). The introduction of trade-focussed Australian Technical Colleges (ATCs) has met with mixed response. The ATCs aim to create a supported transition from school to work through dual pathway programs enabling students to follow a trade career while completing their upper secondary studies. There has been little explicit examination of the effectiveness of such senior secondary school arrangements. Using one such Australian Technical College as a case-study, this paper investigates the perceptions of the employers and students who were associated with the college. Using mixed-methods consisting of quantitative perception surveys and focus interviews, the results of this study show that students and employers are very satisfied with the College and illustrate that students have made significant gains in relating their learning to the workplace and everyday life.

Relative entropy rate based multiple hidden Markov Model Approximation

This paper proposes a novel relative entropy rate (RER) based approach for multiple HMM (MHMM) approximation of a class of discrete-time uncertain processes. Under different uncertainty assumptions, the model design problem is posed either as a min-max optimisation problem or stochastic minimisation problem on the RER between joint laws describing the state and output processes (rather than the more usual RER between output processes). A suitable filter is proposed for which performance results are established which bound conditional mean estimation performance and show that estimation performance improves as the RER is reduced. These filter consistency and convergence bounds are the first results characterising multiple HMM approximation performance and suggest that joint RER concepts provide a useful model selection criteria. The proposed model design process and MHMM filter are demonstrated on an important image processing dim-target detection problem.

Completing the jigsaw : ESL and EFL undergraduate views on interactive peer-based learning

English as a Second Language (ESL) and English as a Foreign Language (EFL) students often face incongruence with Western teaching methods and learning expectations. The aim of this paper is to explore the potential for interactive peer-based learning to engage ESL and EFL language learners provide authentic communication experiences and accelerate learning through two case studies in different contexts. A study was undertaken to investigate student ‘voice’ (Rudduck, 1999, 2005; Rudduck & Flutter, 2004) during an intervention of communicative language teaching using peer-based learning strategies. This article describes unique similarities and subtle differences between ESL and EFL undergraduate learning in two different cultural contexts, using a 'stages of learning matrix' teaching tool to encourage civic skills and self-efficacy. It also suggests ways for teachers to improve on inconsistencies in group-based learning in order to promote more inclusive and congruent learning experiences for English language learners.

Heavy truck suspension optimization based on modified skyhook damping control

This paper presents a multi-objective optimization strategy for heavy truck suspension systems based on modified skyhook damping (MSD) control, which improves ride comfort and road-friendliness simultaneously. A four-axle heavy truck-road coupling system model was established using functional virtual prototype technology; the model was then validated through a ride comfort test. As the mechanical properties and time lag of dampers were taken into account, MSD control of active and semi-active dampers was implemented using Matlab/Simulink. Through co-simulations with Adams and Matlab, the effects of passive, semi-active MSD control, and active MSD control were analyzed and compared; thus, control parameters which afforded the best integrated performance were chosen. Simulation results indicated that MSD control improves a truck’s ride comfort and roadfriendliness, while the semi-active MSD control damper obtains road-friendliness comparable to the active MSD control damper.

Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

A study of Chinese private passenger cars based on BP neural network

This study employs BP neural network to simulate the development of Chinese private passenger cars. Considering the uncertain and complex environment for the development of private passenger cars, indicators of economy, population, price, infrastructure, income, energy and some other fields which have major impacts on it are selected at first. The network is proved to be operable to simulate the progress of chinese private passenger cars after modeling, training and generalization test. Based on the BP neural network model, sensitivity analysis of each indicator is carried on and shows that the sensitivity coefficients of fuel price change suddenly. This special phenomenon reveals that the development of Chinese private passenger cars may be seriously affected by the recent high fuel price. This finding is also consistent with facts and figures

Real world contexts in PISA science : implications for context-based science education

The PISA assessment instruments for students’ scientific literacy in 2000, 2003 and 2006 have each consisted of units made up of a real world context involving Science and Technology, about which students are asked a number of cognitive and affective questions. This paper discusses a number of issues from this use of S&T contexts in PISA and the implications they have for the current renewed interest in context-based science education. Suitably chosen contexts can engage both boys and girls. Secondary analyses of the students’ responses using the contextual sets of items as the unit of analysis provides new information about the levels of performance in PISA 2006 Science. .Embedding affective items in the achievement test did not lead to gender/context interactions of significance, and context interactions were less than competency ones. A number of implications for context-based science teaching and learning are outlined and the PISA 2006 Science test is suggested as a model for its assessment.