Demand Response for Residential Appliances in a Smart Electricity Distribution Network: Utility and Customer Perspectives

This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

Making smart decisions : key steps towards a typology for emergency communication during natural hazards

Governments, authorities, and organisations dedicate significant resources to encourage communities to prepare for and respond to natural hazards such as cyclones, earthquakes, floods, and bushfires. However, recent events, media attention, and ongoing academic research continue to highlight cases of non-compliance including swift water rescues. Individuals who fail to comply with instructions issued during natural hazards significantly impede the emergency response because they divert resources to compliance-enforcement and risk the lives of emergency service workers who may be required to assist them. An initial investigation of the field suggests several assumptions or practices that influence emergency management policy, communication strategy, and community behaviours during natural hazards: 1) that community members will comply with instructions issued by governments and agencies that represent the most authoritative voice, 2) that communication campaigns are shaped by intuition rather than evidence-based approaches (Wood et al., 2012), and 3) that emergency communication is linear and directional. This extended abstract represents the first stage of a collaborative research project that integrates industry and cross-disciplinary perspectives to provide evidence-based approaches for emergency and risk communication during the response and recovery phases of a natural hazard. Specifically, this abstract focuses on the approach taken and key elements that will form the development of a typology of compliance-gaining messages during the response phase of natural hazards, which will be the focus of the conference presentation.

“To educate you to be smart”: disaffected students and the purpose of school in the (not so clever) “lucky country”

This paper contributes to conversations about school, post-compulsory and further education policy by reporting findings from a three-year study with disaffected students who have been referred to special “behaviour” schools. Contrary to popular opinion, our research finds that these “ignorant yobs” (Tomlinson, 2012) do value education and know what it is for. They also have aspirations for a secure, productive and fulfilled life, although it may not involve university level study. Importantly, we found that students who responded negatively with regard to the importance of schooling tended to envision future lives and occupations for which they believed school knowledge was unnecessary. The implications of this research for school, post-compulsory and further education policy are discussed.

Corneal confocal microscopy shown an improvement in small-fibre neuropathy in subjects with type 1 diabetes on continuous subcutaneous insulin infusion compared to multiple daily injection

Improved glycemic control is the only treatment that has been shown to be effective for diabetic peripheral neuropathy in patients with type 1 diabetes (1). Continuous subcutaneous insulin infusion (CSII) is superior to multiple daily insulin injection (MDI) for reducing HbA1c and hypoglycemic events (2). Here, we have compared the benefits of CSII compared withMDI for neuropathy over 24months....

Passenger segmentation using smart card data

Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.

Smart coordinated distribution system control to enable high level penetration of rooftop PVs

This thesis addresses voltage violation problem, the most critical issue associated with high level penetration of photovoltaic (PV) in electricity distribution network. A coordinated control algorithm using the reactive power from PV inverter and integrated battery energy storage has been developed and investigated in different network scenarios in the thesis. Probable variations associated with solar generation, end-user participation and network parameters are also considered. Furthermore, a unified data model and well-defined communication protocol to ensure the smooth coordination between all the components during the operation of the algorithm is described. Finally this thesis incorporated the uncertainties of solar generation using probabilistic load flow analysis.

Smart phones and tablets in the early years : a waste of time or a valuable opportunity for accessing information and communicating?

New digital media surrounds us. Little is known, however, about the influence of technology devices such as tablets (e.g. iPads) and smart phones on young children’s lives in home and school settings, and what it means for them throughout their schooling and beyond. Most research to date has focused on children aged six years and older, and much less (with a few exceptions) on preschool-aged children. This article draws on parent interviews to show how family members engage with technology as part of the flow of everyday life. Only time and increased understandings of everyday practices will tell the real values and scope of using digital media.

Smart cities: An effective urban development and management model?

It is argued that the smart cities model promise solutions to fuel sustainable development and a high quality of life with a wise management of natural resources, through participatory action and engagement. The paper provides a critical review of this model and application attempts of smart urban technologies in contemporary cities by particularly looking into emerging practices of ubiquitous eco-cities as exemplar smart cities initiatives. Through a thorough review of literature and best practices on the smart cities model, this paper attempts to address the research question of whether smart cities model is just another fashionable city brand or an effective urban development and management model to solve the problems of our cities. The findings shed light on urban planning and development considerations for the integration of smart urban technologies and their possible implications in shaping up of the built environment to produce prosperous and sustainable urban futures.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Analysis of distributed beamforming in cooperative communications network with phase shifter based smart antenna nodes

This research study investigates the application of phase shifter-based smart antenna system in distributed beamforming. It examines the way to optimise the transmit power by jointly maximising the directivity of the array antennas and the weight vector for distributed beamforming. This research study concludes that maximising directivity can lead to better transmit power minimisation compared to maximising field intensity. This study also concludes that signal to noise power ratio maximisation subject to a power constraint and power minimisation subject to a signal to noise power ratio constraint yield the same results.