Impact of weather dependency on planning decisions in the australian national electricity market

A long-term planning method for the electricity market is to simulate market operation into the future. Outputs from market simulation include indicators for transmission augmentation and new generation investment. A key input to market simulations is demand forecasts. For market simulation purposes, regional demand forecasts for each half-hour interval of the forecasting horizon are required, and they must accurately represent realistic demand profiles and interregional demand relationships. In this paper, a demand model is developed to accurately model these relationships. The effects of uncertainty in weather patterns and inherent correlations between regional demands on market simulation results are presented. This work signifies the advantages of probabilistic modeling of demand levels when making market-based planning decisions.

The design of a real-time nowcasting system for localised weather

National meteorological offices are largely concerned with synoptic-scale forecasting where weather predictions are produced for a whole country for 24 hours ahead. In practice, many local organisations (such as emergency services, construction industries, forestry, farming, and sports) require only local short-term, bespoke, weather predictions and warnings. This thesis shows that the less-demanding requirements do not require exceptional computing power and can be met by a modern, desk-top system which monitors site-specific ground conditions (such as temperature, pressure, wind speed and direction, etc) augmented with above ground information from satellite images to produce `nowcasts'. The emphasis in this thesis has been towards the design of such a real-time system for nowcasting. Local site-specific conditions are monitored using a custom-built, stand alone, Motorola 6809 based sub-system. Above ground information is received from the METEOSAT 4 geo-stationary satellite using a sub-system based on a commercially available equipment. The information is ephemeral and must be captured in real-time. The real-time nowcasting system for localised weather handles the data as a transparent task using the limited capabilities of the PC system. Ground data produces a time series of measurements at a specific location which represents the past-to-present atmospheric conditions of the particular site from which much information can be extracted. The novel approach adopted in this thesis is one of constructing stochastic models based on the AutoRegressive Integrated Moving Average (ARIMA) technique. The satellite images contain features (such as cloud formations) which evolve dynamically and may be subject to movement, growth, distortion, bifurcation, superposition, or elimination between images. The process of extracting a weather feature, following its motion and predicting its future evolution involves algorithms for normalisation, partitioning, filtering, image enhancement, and correlation of multi-dimensional signals in different domains. To limit the processing requirements, the analysis in this thesis concentrates on an `area of interest'. By this rationale, only a small fraction of the total image needs to be processed, leading to a major saving in time. The thesis also proposes an extention to an existing manual cloud classification technique for its implementation in automatically classifying a cloud feature over the `area of interest' for nowcasting using the multi-dimensional signals.

Automatic processing, quality assurance and serving of real-time weather data over lightweight protocols

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Automatic processing, quality assurance and serving of real-time weather data

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Reduced dimension models for weather forecasting

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Building up resilience of construction sector SMEs and their supply chains to extreme weather events

Wider scientific community now accept that the threat of climate change as real and thus acknowledge the importance of implementing adaptation measures in a global context. In the UK , the physical effects of climate change are likely to be directly felt in the form of extreme weather events, which are predicted to escalate in number and severity in future under the changing climatic conditions. Construction industry; which consists of supply chains running across various other industries, economies and regions, will also be affected due to these events. Thus, it is important that the construction organisations are well prepared to withstand the effects of extreme weather events not only directly affecting their organisations but also affecting their supply chains which in turn might affect the organisation concerned. Given the fact that more than 99% of construction sector businesses are SMEs, the area can benefit significantly from policy making to improve SME resilience and coping capacity. This paper presents the literature review and synthesis of a doctoral research study undertaken to address the issue of extreme weather resilience of construction sector SMEs and their supply chains. The main contribution of the paper to both academia and practitioners is a synthesis model that conceptualises the factors that enhances resilience of SMEs and their supply chains against extreme weather events. This synthesis model forms the basis of a decision making framework that will enable SMEs to both reduce their vulnerability and enhance their coping capacity against extreme weather. The value of this paper is further extended by the overall research design that is set forth as the way forward.

Case study as a research strategy : investigating extreme weather resilience of construction SMEs in the UK

Determining an appropriate research methodology is considered as an important element in a research study; especially in a doctoral research study. It involves approach to the entire process of a research study, starting from theoretical underpinnings and spanning to data collection and analysis, and extending to developing the solutions for the problems investigated. Research methodology in essence is focused around the problems to be investigated in a research study and therefore varies according to the problems investigated. Thus, identifying the research methodology that best suits a research in hand is important, not only as it will benefit achieving the set objectives of a research, but also as it will serve establishing the credibility of the work. Research philosophy, approach, strategy, choice, and techniques are inherent components of the methodology. Research strategy provides the overall direction of the research including the process by which the research is conducted. Case study, experiment, survey, action research, grounded theory and ethnography are examples for such research strategies. Case study is documented as an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident. Case study was adopted as the overarching research strategy, in a doctoral study developed to investigate the resilience of construction Small and Medium-sized Enterprises (SMEs) in the UK to extreme weather events. The research sought to investigate how construction SMEs are affected by EWEs, respond to the risk of EWEs, and means of enhancing their resilience to future EWEs. It is argued that utilising case study strategy will benefit the research study, in achieving the set objectives of the research and answering the research questions raised, by comparing and contrasting with the alternative strategies available. It is also claimed that the selected strategy will contribute towards addressing the call for improved methodological pluralism in construction management research, enhancing the understanding of complex network of relationships pertinent to the industry and the phenomenon being studied.

Extreme weather events and construction SMEs:vulnerability, impacts and responses

Purpose – The UK experienced a number of Extreme Weather Events (EWEs) during recent years and a significant number of businesses were affected as a result. With the intensity and frequency of weather extremes predicted in the future, enhancing the resilience of businesses, especially of Small and Medium-sized Enterprises (SMEs), who are considered as highly vulnerable, has become a necessity. However, little research has been undertaken on how construction SMEs respond to the risk of EWEs. In seeking to help address this dearth of research, this investigation sought to identify how construction SMEs were being affected by EWEs and the coping strategies being used. Design/methodology/approach – A mixed methods research design was adopted to elicit information from construction SMEs, involving a questionnaire survey and case study approach. Findings – Results indicate a lack of coping strategies among the construction SMEs studied. Where the coping strategies have been implemented, these were found to be extensions of their existing risk management strategies rather than radical measures specifically addressing EWEs. Research limitations/implications – The exploratory survey focused on the Greater London area and was limited to a relatively small sample size. This limitation is overcome by conducting detailed case studies utilising two SMEs whose projects were located in EWE prone localities. The mixed method research design adopted benefits the research by presenting more robust findings. Practical implications – A better way of integrating the potential of EWEs into the initial project planning stage is required by the SMEs. This could possibly be achieved through a better risk assessment model supported by better EWE prediction data. Originality/value – The paper provides an original contribution towards the overarching agenda of resilience of SMEs and policy making in the area of EWE risk management. It informs both policy makers and practitioners on issues of planning and preparedness against EWEs.

Developing a conceptual framework for investigating the resilience of construction SMEs and their supply chains against extreme weather events

Projections into future increasingly suggest that the intensity and frequency of Extreme Weather Events (EWEs) will increase in the future. This has demanded the business organisations as well to be prepared to face the increasing risk of EWEs, in order to ensure their business continuity. However, current evidence base suggests that businesses, especially SMEs, are not adequately prepared to face the threat of such events. Ability to adequately prepare them has been hindered by the lack of in depth studies addressing this issue. The paper presents a doctoral study designed to investigate the resilience of SMEs operating in the construction sector; which is said to be a highly vulnerable sector for the impacts of EWEs, and their supply chains to EWEs. A conceptual framework developed to investigate this issue is presented and explained. It is argued that the resilience of construction SMEs and their supply chains against EWEs can be improved by a combination of reducing their vulnerability, enhancing coping capacity and implementing coping mechanisms. Importance of undertaking a broader view to include the whole supply chain in making business decisions with regard to EWEs by SMEs is also highlighted.

Coping strategies against extreme weather events:a survey of SMEs in the UK

Small and Medium-scale Enterprises (SMEs); which generate more than one half of the employment and turnover, form an important sector of the UK economy. In fact, SMEs are considered as the backbone of the UK economy due to their significant economic and societal importance. Despite SMEs being the main drivers of the UK economy, they are also said to be the most vulnerable to the impacts from various disruptions such as Extreme Weather Events (EWEs). Consequently, increased intensity and frequency of weather extremes in the UK during the recent past has created a significant impact on the SME community. As the threat of EWEs is expected to further increase in future, the need for SMEs to implement effective coping mechanisms to manage the effects of EWEs is also increasing. This paper aims to identify and evaluate the current coping mechanisms implemented by SMEs to ensure their business continuity in the event of a weather extreme. The paper presents the findings of a questionnaire survey, conducted as part of "Community Resilience to Extreme Weather - CREW" research project, addressing this issue. It is identified that SMEs mostly rely on generic business continuity strategies as opposed to property level protection measures. The paper highlights the importance of raising the uptake of coping strategies by SMEs, as many were found without adequate coping strategies to deal with the risk of EWEs.