Parallel ABM for electricity distribution grids : a case study

This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

Rural masculinities and the internalisation of violence in agricultural communities

This article is based on research we conducted in two agricultural communities as part of a broader study that included mining communities in rural Australia. The data from the agricultural locations tell a different story to that of the mining communities. In the latter, alcohol-fuelled, male-on-male assaults in public places caused considerable anxiety among informants. By contrast, people in the agricultural communities seemed more troubled by hidden violent harms which were largely privatised and individualised, including self-harm, suicide, isolation and threats to men’s general wellbeing and mental health; domestic violence; and other forms of violence largely unreported and thus unacknowledged within the wider community (including sexual assault and bullying linked to homophobia). We argue one reason for the different pattern in the agricultural communities is the decline of pub(lic) masculinity, and with this, the increasing isolation of rural men and the increasing propensity to internalise violence. We argue that the relatively high rates of suicide in agricultural communities experiencing rural decline are symptomatic of the internalisation of violence.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Modelling for the electricity distribution network

Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

Comparing skin biopsy with confocal microscopy : diagnostic yield of nerve fiber density

Background and aims: The assessment of intra-epidermal nerve fiber density (IENFD) in skin biopsies and corneal nerve fiber density (CNFD) using corneal confocal microscopy (CCM) provides promising techniques to detect small nerve fiber damage in patients with peripheral neuropathy. To help define the clinical utility of each of these techniques in patients with diabetic neuropathy we have assessed sensitivity and specificity of IENFD and CNFD in predicting the following: 1) diabetic polyneuropathy (DPN); 2) risk of foot ulceration (RFU); 3) initial small fiber neuropathy (iSFN); 4) severe small fiber neuropathy (sSFN)...

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of -1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the 'most' appropriate system when a review or upgrade of the network infrastructure is required.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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β-Arrestin2 regulates RANKL and Ephrins gene expression in response to bone remodeling in mice

PTH-stimulated intracellular signaling is regulated by the cytoplasmic adaptor molecule barrestin. We reported that the response of cancellous bone to intermittent PTH is reduced in b-arrestin22/2 mice and suggested that b-arrestins could influence the bone mineral balance by controlling RANKL and osteoprotegerin (OPG) gene expression. Here, we study the role of b-arrestin2 on the in vitro development and activity of bone marrow (BM) osteoclasts (OCs) and Ephrins ligand (Efn), and receptor (Eph) mRNA levels in bone in response to PTH and the changes of bone microarchitecture in wildtype (WT) and barrestin2 2/2 mice in models of bone remodeling: a low calcium diet (LoCa) and ovariectomy (OVX). The number of PTH-stimulated OCs was higher in BM cultures from b-arrestin22/2 compared with WT, because of a higher RANKL/OPG mRNA and protein ratio, without directly influencing osteoclast activity. In vivo, high PTH levels induced by LoCa led to greater changes in TRACP5b levels in b-arrestin22/2 compared with WT. LoCa caused a loss of BMD and bone microarchitecture, which was most prominent in b-arrestin22/2. PTH downregulated Efn and Eph genes in b-arrestin22/2, but not WT. After OVX, vertebral trabecular bone volume fraction and trabecular number were lower in b-arrestin22/2 compared with WT. Histomorphometry showed that OC number was higher in OVX-b-arrestin22/2 compared with WT. These results indicate that b-arrestin2 inhibits osteoclastogenesis in vitro, which resulted in decreased bone resorption in vivo by regulating RANKL/OPG production and ephrins mRNAs. As such, b-arrestins should be considered an important mechanism for the control of bone remodeling in response to PTH and estrogen deprivation.

Analysis of unsaturated lipids by ozone-induced dissociation

Recent developments in analytical technologies have driven significant advances in lipid science. The sensitivity and selectivity of modern mass spectrometers can now provide for the detection and even quantification of many hundreds of lipids in a single analysis. In parallel, increasing evidence from structural biology suggests that a detailed knowledge of lipid molecular structure including carbon-carbon double bond position, stereochemistry and acyl chain regiochemistry is required to fully appreciate the biochemical role(s) of individual lipids. Here we review the capabilities and limitations of tandem mass spectrometry to provide this level of structural specificity in the analysis of lipids present in complex biological extracts. In particular, we focus on the capabilities of a novel technology termed ozone-induced dissociation to identify the position (s) of double bonds in unsaturated lipids and discuss its possible role in efforts to develop workflows that provide for complete structure elucidation of lipids by mass spectrometry alone: so-called top-down lipidomics. This article is part of a Special Issue entitled: Lipodomics and Imaging Mass Spectrom. (C) 2011 Elsevier B.V. All rights reserved.

Integrating the impact of climate into event based failure models for water pipes

This paper presents an event-based failure model to predict the number of failures that occur in water distribution assets. Often, such models have been based on analysis of historical failure data combined with pipe characteristics and environmental conditions. In this paper weather data have been added to the model to take into account the commonly observed seasonal variation of the failure rate. The theoretical basis of existing logistic regression models is briefly described in this paper, along with the refinements made to the model for inclusion of seasonal variation of weather. The performance of these refinements is tested using data from two Australian water authorities.

Seasonal factors influencing the failure of buried water reticulation pipes

While the use of environmental factors in the analysis and prediction of failures of buried reticulation pipes in cold environments has been the focus of extensive work, the same cannot be said for failures occurring on pipes in other (non-freezing) environments. A novel analysis of pipe failures in such an environment is the subject of this paper. An exploratory statistical analysis was undertaken, identifying a peak in failure rates during mid to late summer. This peak was found to correspond to a peak in the rate of circumferential failures, whilst the rate of longitudinal failures remained constant. Investigation into the effect of climate on failure rates revealed that the peak in failure rates occurs due to differential soil movement as the result of shrinkage in expansive soils.

Sewer performance reporting : factors that influence blockages

Managing sewer blockages represents a significant operational challenge for water utilities. In Australia, company-level blockage rates are used to compare the effectiveness of the management strategies of different utilities. Anecdotal evidence suggests this may not be a fair basis for comparison because blockages are influenced by a range of factors beyond management control and that vary from company to company. This issue was investigated as part of a broader research effort on sewer blockage management undertaken in conjunction with the Water Services Association of Australia (WSAA) and its members. A Web-based survey was used to collate expert opinion on factors that influence blockage rate. The identified factors were then investigated in an exploratory analysis of blockage-related data provided by two participating utilities, supported by literature reviews. The results indicate that blockage rate is influenced by a range of factors, including asset attributes, climatic conditions, water consumption, and soil type. Since these factors vary from utility to utility, this research supports the assertion that company-level blockage rate is not in itself an appropriate metric for comparing management effectiveness.

Understanding how the Australian climate can affect pipe failure

This paper details a statistical analysis of historical failure data, which focuses on determining the manner in which local climate affects pipe failure rates. It was found that seasonality exists in the data, indicating an affect of local climate on failure rate. Significant variation in failure rates was seen between the months of December and May, especially in February/March, whilst limited variations were seen in other months of the year. Further analysis found that failure rates were strongly correlated with minimum antecedent precipitation index and net evaporation and that climate affected failure rate by influencing soil moisture content. Interaction affects between static attributes of the pipe-environment system and local climate were also investigated.

Application of GIS in understanding and communicating interaction between environmental parameters and sewer blockages

Sewer main chokes (blockages) are a key performance indicator for Australian water utilities. Blockages caused by tree roots often result in wastewater overflow posing an environmental and health risk and also requiring service interruptions to repair asset. The purpose of the research project outlined in this paper was to understand the role of environmental parameters, in particular soil type and tree density, in determining the propensity of a sewer to become blocked. The paper demonstrates the application of spatial analysis to inform and communicate the results of the analysis. GIS was used to explore the relationship between tree density and previously recorded sewer blockages for a Melbourne utility. Initial results from the research reveal a relationship between increased tree densities and occurrence of sewer blockages. An improved understanding of the influence of environmental parameters on the inherent risk of sewer blockage will enable asset managers to identify those assets requiring proactive management in order to minimise service interruptions, repairs and environmental impacts.

Aggregating energy supply and demand

Energy usage in general, and electricity usage in particular, are major concerns internationally due to the increased cost of providing energy supplies and the environmental impacts of electricity generation using carbon-based fuels. If a "systems" approach is taken to understanding energy issues then both supply and demand need to be considered holistically. This paper examines two research projects in the energy area with IT tools as key deliverables, one examining supply issues and the other studying demand side issues. The supply side project used hard engineering methods to build the models and software, while the demand side project used a social science approach. While the projects are distinct, there was an overlap in personnel. Comparing the knowledge extraction, model building, implementation and interface issues of these two deliverables identifies both interesting contrasts and commonalities.