A smart load appliance application using a single compressor fridge-freezer to support grid operations

This paper describes a fridge-freezer smart load model, which responds to external signals from the wholesale electricity market to support grid operations while switching the fridge-freezer on and off to maintain optimum operations for the owner. The key parameters of the model are the appliance dimensions, thermal mass, the fridge and freezer thermal time constants and the compressor power consumption. The model demonstrates that control strategies help to minimise load at times when the grid is under stress from high demand, and shift some load to a lower wholesale price or when there is excess renewable power. Three control strategies are proposed, based on peak shaving and valley filling, price signals and wind availability.

From Smart Meters To Smart Decisions: Web-Based Support For The Water Efficient Household

Smart water metering technologies for residential buildings offer, in principle, great opportunities for sustainable urban water management. However, much of this potential is as yet unrealized. Despite that several ICT solutions have already been deployed aiming at optimum operations on the water utilities side (e.g. real time control for water networks, dynamic pump scheduling etc.), little work has been done to date on the consumer side. This paper presents a web-based platform targeting primarily the household end user. The platform enables consumers to monitor, on a real-time basis, the water demand of their household, providing feedback not only on the total water consumption and relevant costs but also on the efficiency (or otherwise) of specific indoor and outdoor uses. Targeting the reduction of consumption, the provided feedback is combined with notifications about possible leakages\bursts, and customised suggestions to improve the efficiency of existing household uses. It also enables various comparisons, with past consumption or even with that of similar households, aiming to motivate further the householder to become an active player in the water efficiency challenge. The issue of enhancing the platform’s functionality with energy timeseries is also discussed in view of recent advances in smart metering and the concept of “smart cities”. The paper presents a prototype of this web-based application and critically discusses first testing results and insights. It also presents the way in which the platform communicates with central databases, at the water utility level. It is suggested that such developments are closing the gap between technology availability and usefulness to end users and could help both the uptake of smart metering and awareness raising leading, potentially, to significant reductions of urban water consumption. The work has received funding from the European Union FP7 Programme through the iWIDGET Project, under grant agreement no318272.

Optimization of multipulse converters with delta and Y-differential connections

This work presents a study regarding the optimization of multipulse converters. A general expression for the connection (Δ or Y) for both 12 and 18-pulses is obtained and describes the output voltages on the secondary windings, depending on the voltage reference from the primary. These generalized expressions allows choosing different ratios between input and output voltages and as result an optimum operation point for the converter can be calculated. Considering Δ-connected converters the optimum point occurs when the magnetic core of the autotransformer processes 18% and 17% of the output power for 12 and 18-pulses, respectively. For Y-connected converters the optimum point occurs when the kVA rating is 13% and 18% for 12 and 18-pulses, respectively. Based on these results magnetic elements can be calculated and designed leading to a great weight and volume reduction and also to lower costs and losses. Finally an analysis is made to improve the kVA rating of the transformers for 12 and 18 pulses converters. © 2009 IEEE.

Random Breath Testing in Australia: Is there an Optimum Level of Intensity?

Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.

On the optimum buoyancy-weight relation for a bottom trawl

Comparative fishing operations were carried out with 0.55; 0.75 and 1.00 buoyancy-weight relations of bottom trawl in order to find out the optimum relation. Two nets, 18.26 m. (60') two seam nylon and 16.16 m. (23') two seam cotton trawls, were used for the experiment. The results showed that the total catch per trawling hour with 0.75 B-W relation was 16.5% and 32.08% more than that with 0.55 and 1.00 B-W relation for nylon net used. A similar trend was noticed with cotton trawl also as the catch rate with 0.75 B-W relation was 13.89% and 25.78% more than that with 0.55 and 1.00 B-W relations. However, the analysis of catch composition indicated that the off bottom fishes like lactarius, upenoides sp., synagris sp. etc., were of more percentage with 1.00 B-W relation, near bottom fish like saurida, sciaenids etc., were more with 0.75 B-W relation, while the bottom fishes like soles, prawns, skates and rays etc., were more with 0.55 B-W relation.

Fast petroleum well drilling monitoring through optimum-path forest

Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the Optimum-Path Forest classifier. Given that the cutting's volume at the vibrating shale shaker can provide several information about drilling, we used computer vision techniques to extract texture informations from cutting images acquired by a digital camera. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and effciency. We used the Optimum-Path Forest (OPF), EOPF (Efficient OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP) Support Vector Machines (SVM), and a Bayesian Classifier (BC) to assess the robustness of our proposed schema for petroleum well drilling monitoring through cutting image analysis.

Using simulation to assess the introduction of technology in a continuous operations process

Purpose – To investigate the role of simulation in the introduction of technology in a continuous operations process. Design/methodology/approach – A case-based research method was chosen with the aim to provide an exemplar of practice and test the proposition that the use of simulation can improve the implementation and running of conveyor systems in continuous process facilities. Findings – The research determines the optimum rate of re-introduction of inventory to a conveyor system generated during a breakdown event. Research limitations/implications – More case studies are required demonstrating the operational and strategic benefits that can be gained by using simulation to assess technology in organisations. Practical implications – A practical outcome of the study was the implementation of a policy for the manual re-introduction of inventory on a conveyor line after a breakdown event had occurred. Originality/value – The paper presents a novel example of the use of simulation to estimate the re-introduction rate of inventory after a breakdown event on a conveyor line. The paper highlights how by addressing this operational issue, ahead of implementation, the likelihood of the success of the strategic decision to acquire the technology can be improved.

Faster group operations on elliptic curves

This paper improves implementation techniques of Elliptic Curve Cryptography. We introduce new formulae and algorithms for the group law on Jacobi quartic, Jacobi intersection, Edwards, and Hessian curves. The proposed formulae and algorithms can save time in suitable point representations. To support our claims, a cost comparison is made with classic scalar multiplication algorithms using previous and current operation counts. Most notably, the best speeds are obtained from Jacobi quartic curves which provide the fastest timings for most scalar multiplication strategies benefiting from the proposed 12M + 5S + 1D point doubling and 7M + 3S + 1D point addition algorithms. Furthermore, the new addition algorithm provides an efficient way to protect against side channel attacks which are based on simple power analysis (SPA). Keywords: Efficient elliptic curve arithmetic,unified addition, side channel attack.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia