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.

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.

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.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Impact of technology uptake on an Australian electricity distribution network

This paper presents simulation results for future electricity grids using an agent-based model developed with MODAM (MODular Agent-based Model). MODAM is introduced and its use demonstrated through four simulations based on a scenario that expects a rise of on-site renewable generators and electric vehicles (EV) usage. The simulations were run over many years, for two areas in Townsville, Australia, capturing variability in space of the technology uptake, and for two charging methods for EV, capturing people's behaviours and their impact on the time of the peak load. Impact analyses of these technologies were performed over the areas, down to the distribution transformer level, where greater variability of their contribution to the assets peak load was observed. The MODAM models can be used for different purposes such as impact of renewables on grid sizing, or on greenhouse gas emissions. The insights gained from using MODAM for technology assessment are discussed.

Compositional agent-based models for electricity distribution networks

This thesis presents a novel approach to building large-scale agent-based models of networked physical systems using a compositional approach to provide extensibility and flexibility in building the models and simulations. A software framework (MODAM - MODular Agent-based Model) was implemented for this purpose, and validated through simulations. These simulations allow assessment of the impact of technological change on the electricity distribution network looking at the trajectories of electricity consumption at key locations over many years.

The three Eichenwald children, Fritz, Hanne and Hans Portraits; Family

Digital Image

Studio portrait of the women of the Oppenheimer family.

l-r: Thekla Oppenheimer-Benedick, Jenny Oppenheimer-Frank, Fanny Oppenheimer and Adele Oppenheimer-Nathan

Studio portrait of the women of the Oppenheimer family.

l-r: Sisters Adele Oppenheimer-Nathan, Thekla Oppenheimer-Benedick, Jenny Oppenheimer-Frank and their mother Fanny Oppenheimer

Family portrait at double wedding ceremony of the Heimann and Rosenfelder families Portraits; Family

Double Wedding Ceremony Heimann-Rosenfelder August 17, 1909