Development of health risk-based metrics for defining a heatwave : a time series study in Brisbane, Australia

Background: This study attempted to develop health risk-based metrics for defining a heatwave in Brisbane, Australia. Methods: Poisson generalised additive model was performed to assess the impact of heatwaves on mortality and emergency hospital admissions (EHAs) in Brisbane. Results: In general, the higher the intensity and the longer the duration of a heatwave, the greater the health impacts. There was no apparent difference in EHAs risk during different periods of a warm season. However, there was a greater risk of mortality in the second half of a warm season than that in the first half. While elderly (>75 years)were particularly vulnerable to both the EHA and mortality effects of a heatwave, the risk for EHAs also significantly increased for two other age groups (0-64 years and 65-74 years) during severe heatwaves. Different patterns between cardiorespiratory mortality and EHAs were observed. Based on these findings, we propose the use of a teiered heat warning system based on the health risk of heatwave. Conclusions: Health risk-based metrics are a useful tool for the development of local heatwave definitions. thsi tool may have significant implications for the assessment of heatwave-related health consequences and development of heatwave response plans and implementation strategies.

Overvoltage and overloading prevention using coordinated PV inverters in distribution network

Overvoltage and overloading due to high utilization of PVs are the main power quality concerns for future distribution power systems. This paper proposes a distributed control coordination strategy to manage multiple PVs within a network to overcome these issues. PVs reactive power is used to deal with over-voltages and PVs active power curtailment are regulated to avoid overloading. The proposed control structure is used to share the required contribution fairly among PVs, in proportion to their ratings. This approach is examined on a practical distribution network with multiple PVs.

A framework for understanding and generating integrated solutions for residential peak energy demand

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.

Fault detection of wind turbine drivetrain utilizing power-speed characteristics

Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.

A coordinated voltage control approach for coordination of OLTC, voltage regulator, and DG to regulate voltage in a distribution feeder

Integration of small-scale electricity generators, known as distributed generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of the synchronous-type generator has potential to give DG a better chance at participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of DG as a voltage regulator and, at the same time, minimize interaction with other active devices, such as an on-load tap changing transformer and a voltage regulator. The technique has been developed based on the concept of control zone, line drop compensation, dead band, as well as the choice of controllers' parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

Sectionalizing strategies for minimizing outage durations of critical loads in parallel power system restoration with bi-level programming

Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.

Wide-area damping control for inter-area oscillations using inverse filtering technique

In this study, a non-linear excitation controller using inverse filtering is proposed to damp inter-area oscillations. The proposed controller is based on determining generator flux value for the next sampling time which is obtained by maximising reduction rate of kinetic energy of the system after the fault. The desired flux for the next time interval is obtained using wide-area measurements and the equivalent area rotor angles and velocities are predicted using a non-linear Kalman filter. A supplementary control input for the excitation system, using inverse filtering approach, to track the desired flux is implemented. The inverse filtering approach ensures that the non-linearity introduced because of saturation is well compensated. The efficacy of the proposed controller with and without communication time delay is evaluated on different IEEE benchmark systems including Kundur's two area, Western System Coordinating Council three-area and 16-machine, 68-bus test systems.

Cross-border malaria: a major obstacle for malaria elimination

Movement of malaria across international borders poses a major obstacle to achieving malaria elimination in the 34 countries that have committed to this goal. In border areas, malaria prevalence is often higher than in other areas due to lower access to health services, treatment-seeking behaviour of marginalised populations that typically inhabit border areas, difficulties in deploying prevention programs to hard-to-reach communities, often in difficult terrain, and constant movement of people across porous national boundaries. Malaria elimination in border areas will be challenging, and key to addressing the challenges is strengthening of surveillance activities for rapid identification of any importation or reintroduction of malaria. This could involve taking advantage of technological advances, such as spatial decision support systems, which can be deployed to assist program managers to carry out preventive and reactive measures, and mobile phone technology, which can be used to capture the movement of people in the border areas and likely sources of malaria importation. Additionally, joint collaboration in the prevention and control of cross-border malaria by neighbouring countries, and reinforcement of early diagnosis and prompt treatment are ways forward in addressing the problem of cross-border malaria.

Fast unscented transformation-based transient stability margin estimation incorporating uncertainty of wind generation

Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

Where do ED patients come from?

A lack of access to primary care services, decreasing numbers of general practitioners (GPs) and free of charge visits have been cited as factors contributing to the rising demand on emergency departments. This study aims to investigate the sources of patients' referrals to emergency departments and track changes in the source of referral over a six-year period in Queensland. Data from Queensland Emergency Departments Information Systems were analyzed based on records from 21 hospitals for the periods 2003–04 to 2008–09. The emergency department data were compared with publicly available data on GPs services and patients attendance rates. In Queensland, the majority of patients are self-referred and a 6.6% growth between 2003–04 and 2008–09 (84.4% to 90% respectively) has been observed. The number of referrals made by GPs, hospitals and community services decreased by 29.4%, 40%, 42% respectively during the six-year period. The full-time workload equivalent GPs per 100,000 people increased by 4.5% and the number of GP attendances measured per capita rose by 4% (4.25 to 4.42). An examination of changes in the triage category of self-referred patients revealed an increase in triage category 1-3 by 60%, 36.2%, and 14.4% respectively. The number of self-referred patients in triage categories 4–5 decreased by 10.5% and 21.9% respectively. The results of this analysis reveal that although the number of services provided by GPs increased, the amount of referrals decreased, and the proportion of self-referred patients to emergency departments rose during the six-year period. In addition, a growth in urgent triage categories (1–3) has been observed, with a decline in the number of non-urgent categories (4–5) among patients who came directly to emergency departments. Understanding the reasons behind this situation is crucial for appropriate demand management. Possible explanations will be sought and presented based on patients' responses to an emergency department users' questionnaire.

Evaluating emergency nurse practitioner service effectiveness on achieving timely analgesia: A pragmatic randomized controlled trial

Objectives The rapid uptake of nurse practitioner (NP) services in Australia has outpaced evaluation of this service model. A randomized controlled trial was conducted to compare the effectiveness of NP service versus standard medical care in the emergency department (ED) of a major referral hospital in Australia. Methods Patients presenting with pain were randomly assigned to receive either standard ED medical care or NP care. Primary investigators were blinded to treatment allocation for data analyses. The primary outcome measure was the proportion of patients receiving analgesia within 30 minutes from being seen by care group. Secondary outcome measures were time to analgesia from presentation and documentation of and changes in pain scores. Results There were 260 patients randomized; 128 received standard care (medical practitioner led), and 130 received NP care. Two patients needed to be excluded due to incomplete consent forms. The proportion of patients who received analgesia within 30 minutes from being seen was 49.2% (n = 64) in the NP group and 29.7% (n = 38) in the standard group, a difference of 19.5% (95% confidence interval [CI] = 7.9% to 31.2%; p = 0.001). Of 165 patients who received analgesia, 64 (84.2%) received analgesia within 30 minutes in the NP group compared to 38 (42.7%) in the standard care group, a difference in proportions of 41.5% (95% CI = 28.3% to 54.7%; p < 0.001). The mean (±SD) time from being seen to analgesia was 25.4 (±39.2) minutes for NP care and 43.0 (±35.5) minutes for standard care, a difference of 17.6 minutes (95% CI = 6.1 to 29.1 minutes; p = 0.003). There was a difference in the median change in pain score of 0.5 between care groups, but this was not statistically significant (p = 0.13). Conclusions Nurse practitioner service effectiveness was demonstrated through superior performance in achieving timely analgesia for ED patients.