Residential voltage dip and swell mitigation using Plug-in Hybrid Electric Vehicle in smart grid

Solutions to remedy the voltage disturbances have been mostly suggested only for industrial customers. However, not much research has been done on the impact of the voltage problems on residential facilities. This paper proposes a new method to reduce the effect of voltage dip and swell in smart grids equipped by communication systems. To reach this purpose, a voltage source inverter and the corresponding control system are employed. The behavior of a power system during voltage dip and swell are analyzed. The results demonstrate reasonable improvement in terms of voltage dip and swell mitigation. All simulations are implemented in MATLAB/Simulink environment.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

Smart Inter-Phase Switching of Residential Loads in Low Voltage Distribution Feeders

In order to dynamically reduce voltage unbalance along a low voltage distribution feeder, a smart residential load transfer system is discussed. In this scheme, residential loads can be transferred from one phase to another to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch and a controller. The master controller, installed at the transformer, observes the power consumption in each house and will determine which house(s) should be transferred from an initially connected phase to another in order to keep the voltage unbalance minimum. The performance of the smart load transfer scheme is demonstrated by simulations.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

State Estimation in Smart Power Grids

In this chapter, the role of State Estimation (SE) in smart power grids is presented. The trend of SE error with respect to the increasing of the smart grids implementation investigated. The observability analysis as a prior task of SE is demonstrated and an analytical method to consider the impedance values of the branches is developed and discussed by examples. Since most principles of smart power grids are appropriate to distribution networks, the Distribution SE (DSE)considering load correlation is argued and illustrated by an example. The main features of smart grid SE, which is here named as “Smart Distributed SE” (SDSE), are discussed. Some characteristics of proposed SDES are distributed, hybrid, multi-micro grid and islanding support, Harmonic State Estimation (HSE), observability analysis and restore, error processing, and network parameter estimation. Distribution HSE (DHSE) and meter placement for SDSE are also presented.

Towards a smart cancer registry

Aims Pathology notification for a Cancer Registry is regarded as the most valid information for the confirmation of a diagnosis of cancer. In view of the importance of pathology data, an automatic medical text analysis system (Medtex) is being developed to perform electronic Cancer Registry data extraction and coding of important clinical information embedded within pathology reports. Methods The system automatically scans HL7 messages received from a Queensland pathology information system and analyses the reports for terms and concepts relevant to a cancer notification. A multitude of data items for cancer notification such as primary site, histological type, stage, and other synoptic data are classified by the system. The underlying extraction and classification technology is based on SNOMED CT1 2. The Queensland Cancer Registry business rules3 and International Classification of Diseases – Oncology – Version 34 have been incorporated. Results The cancer notification services show that the classification of notifiable reports can be achieved with sensitivities of 98% and specificities of 96%5, while the coding of cancer notification items such as basis of diagnosis, histological type and grade, primary site and laterality can be extracted with an overall accuracy of 80%6. In the case of lung cancer staging, the automated stages produced were accurate enough for the purposes of population level research and indicative staging prior to multi-disciplinary team meetings2 7. Medtex also allows for detailed tumour stream synoptic reporting8. Conclusions Medtex demonstrates how medical free-text processing could enable the automation of some Cancer Registry processes. Over 70% of Cancer Registry coding resources are devoted to information acquisition. The development of a clinical decision support system to unlock information from medical free-text could significantly reduce costs arising from duplicated processes and enable improved decision support, enhancing efficiency and timeliness of cancer information for Cancer Registries.

Interconnected autonomous microgrids in smart grids with self-healing

In order to minimize the number of load shedding in a Microgrid during autonomous operation, islanded neighbour microgrids can be interconnected if they are on a self-healing network and an extra generation capacity is available in Distributed Energy Resources (DER) in one of the microgrids. In this way, the total load in the system of interconnected microgrids can be shared by all the DERs within these microgrids. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and microgrid levels. In this chapter, first a hierarchical control structure is discussed for interconnecting the neighbour autonomous microgrids where the introduced primary control level is the main focus. Through the developed primary control level, it demonstrates how the parallel DERs in the system of multiple interconnected autonomous microgrids can properly share the load in the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralized power sharing algorithm based on droop control. The switching in the converters is controlled using a linear quadratic regulator based state feedback which is more stable than conventional proportional integrator controllers and this prevents instability among parallel DERs when two microgrids are interconnected. The efficacy of the primary control level of DERs in the system of multiple interconnected autonomous microgrids is validated through simulations considering detailed dynamic models of DERs and converters.

Smart material interfaces : a vision

In this paper, we introduce a vision called Smart Material Interfaces (SMIs), which takes advantage of the latest generation of engineered materials that has a special property defined “smart”. They are capable of changing their physical properties, such as shape, size and color, and can be controlled by using certain stimuli (light, potential difference, temperature and so on). We describe SMIs in relation to Tangible User Interfaces (TUIs) to convey the usefulness and a better understanding of SMIs.

Smart material interfaces : a new form of physical interaction

Smart Material Interface (SMI) is the latest generation of user interface that makes use of engineered materials and leverages their special properties. SMIs are capable of changing their physical properties such as shape, size and color, and can be controlled under certain (external) conditions. We provide an example of such an SMI in the form of a prototype of a vacuum cleaner. The prototype uses schematic electrochromic polymer at the suction nozzle of the vacuum cleaner, which changes its color depending on the dust level on a floor. We emphasize on the new affordances and communication language supported by SMIs, which challenges the current metaphors of user interfaces in the field of HCI.

Dry tropics water smart : a community based approach to residential outdoor water consumption

This paper discusses the Townsville City Council Dry Tropics Water Smart (DTWS) initiative, developed by TCC Integrated Sustainability Services (ISS) and Townsville Water, and informed by The University of Adelaide. The program draws on many years of experience by the TCC team to blend key community-based research approaches in order to develop this residential outdoor water conservation program. Several community pilots have been conducted to test different behaviour change strategies and messages. This paper outlines recent steps taken to develop the community trials, as guided by a combination of behaviour change theories including community-based social marketing and thematic communications methods. Some preliminary results are outlined focused on community uptake of different strategies, community perceptions of communication materials, and some insights into the effectiveness of outdoor water hardware.

An assessment of the geographical scale of recurrent gene flow in wild populations of two species of Mekong River carps (Henicorhynchus spp.)

The Mekong is the most productive river fishery in the world, and such as, the Mekong River Basin (MRB) is very important to very large human populations across the region as a source of revenue (through fishing and marketing of aquatic resources products) and as the major source for local animal protein. Threats to biodiversity in the MRB, either to the fishery sector itself or to other sectors are a major concern, even though currently, fisheries across this region are still very productive. If not managed properly however, fish population declines will cause significant economic impact and affect livelihoods of local people and will have a major impact on food security and nutrition. Biodiversity declines will undoubtedly affect food security, income and socio-economic status of people in the MRB that depend on aquatic resources. This is an indicator of unsustainable development and hence should be avoided. Genetic diversity (biodiversity) that can be measured using techniques based on DNA markers; refers to variation within and among populations within the same species or reproductive units. In a population, new genetic variation is generated by sexual recombination contributed by individuals with mutations in genes and chromosomes. Over time, populations of a species that are not reproducing together will diverge as differential impacts of selection and genetic drift change their genetic attributes. For mud carp (Henicorhynchus spp.), understanding the status of breeding units in the MRB will be important for their long term persistence, sustainability and for implementing effective management strategies. Earlier analysis of stock structure in two economically important mud carp species (Henicorhynchus siamensis and H. lobatus) in the MRB completed with mtDNA markers identified a number of populations of both species where gene flow had apparently been interrupted or reduced but applying these data directly to management unit identification is potentially compromised because information was only available about female dispersal patterns. The current study aimed to address this problem and to fully assess the extent of current gene flow (nDNA) and reproductive exchange among selected wild populations of two species of carp (Henicorhynchus spp.) of high economic importance in the MRB using combined mtDNA and nDNA markers. In combination, the data can be used to define effective management units for each species. In general, nDNA diversity for H. lobatus (with average allelic richness (A) 7.56 and average heterozygosity (Ho) 0.61) was very similar to that identified for H. siamensis (A = 6.81 and Ho = 0.75). Both mud carp species show significant but low FST estimates among populations as a result of lower genetic diversity among sampled populations compared with genetic diversity within populations that may potentially mask any 'real' population structure. Overall, population genetic structure patterns from mtDNA and nDNA in both Henicorhynchus species were largely congruent. Different population structures however, were identified for the two Henicorhynchus species across the same geographical area. Apparent co-similarity in morphology and co-distribution of these two relatively closely related species does not apparently imply parallel evolutionary histories. Differences in each species population structure likely reflect historical drainage rearrangement of the Mekong River. The data indicate that H. siamensis is likely to have occupied the Mekong system for much longer than has H. lobatus in the past. Two divergent stocks were identified for H. lobatus in the MRB below the Khone Falls while a single stock had been evident in the earlier mtDNA study. This suggests that the two Henicorhynchus species may possess different life history traits and that different patterns of gene flow has likely influenced modern genetic structure in these close congeners. In combination, results of the earlier mtDNA and the current study have implications for effective management of both Henicorhynchus species across the MRB. Currently, both species are essentially treated as a single management unit in this region. This strategy may be appropriate for H. lobatus as a single stock was evident in the main stream of the MRB, but may not be appropriate for H. siamensis as more than a single stock was identified across the same range for this species. Management strategies should consider this difference to conserve overall biodiversity (local discrete populations) and this will include maintaining natural habitat and migration pathways, provision of fish sanctuaries (refuges) and may also require close monitoring of any stock declines, a signal that may require effective recovery strategies.

Epidemiological patterns of Ross River virus disease in Queensland, Australia, 2001-2011

Ross River virus (RRV) infection is a debilitating disease which has a significant impact on population health, economic productivity and tourism in Australia. This study examined epidemiological patterns of the RRV disease in Queensland, Australia between January 2001 and December 2011 at a statistical local area level. Spatial-temporal analyses were used to identify the patterns of the disease distribution over time stratified by age, sex and space. The results show that the mean annual incidence was 54 per 100,000 people, with a male: female ratio of 1:1.1. Two space-time clusters were identified: the areas adjacent to Townsville, on the eastern coast of Queensland; and the south east areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on these high risk regions, particularly during the summer and autumn to reduce the social and economic impacts of RRV.

Pressure state response-based method for evaluating social benefits from smart grid development

In this paper, the inherent mechanism of social benefits associated with smart grid development is examined based on the pressure state response (PSR) model from resource economics. The emerging types of technology brought up by smart grid development are regarded as pressures. The improvements of the performance and efficiency of power system operation, such as the enhanced capability of accommodating renewable energy generation, are regarded as states. The effects of smart grid development on society are regarded as responses. Then, a novel method for evaluating social benefits from smart grid development is presented. Finally, the social benefits from smart grid development in a province in northwest China are carried out by using the developed evaluation system, and reasonable evaluation results are attained.

Smart resource control in distribution network to improve the integration level of PV

This project was an innovative approach in developing smart coordination of available energy resources to improve the integration level of PV in distribution network. Voltage and loading issues are considered as the main concerns for future electricity grid which need to be avoided using such resources. A distributed control structure was proposed for the resources in distribution network to avoid noted power quality issues.

All-environment visual place recognition with SMART

This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.