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It is widely recognised that improving the visibility and controllability of distributed energy resources (DERs) within electricity distribution networks will have significant benefits, particularly for the management of low-voltage (LV) and medium-voltage (MV) networks. Much work within the electricity distribution industry is currently focused on improving the visibility of DERs on LV networks. From a control-theoretic perspective, this enables closing the loop between the DER and the control room and enables a shift towards utilising data-driven model-based control strategies for DERs. The result is a system-wide performance that is closer to the theoretical optimal. In the Australian context, several jurisdictions are trialling techniques such as dynamic operating envelopes to enhance DER hosting capacity, using IEEE 2030.5-based architectures, with the implementation of distributed energy resource management (DERMS) systems at the enterprise level still quite limited. While there is significant activity focused on DER behaviour and control techniques by way of inverter grid codes and standards, the core issue of interoperability with distribution management systems (DMSs), market operators or participants, electric vehicles (EVs) or other DERs is still a work in progress. Importantly, this is also an impediment to realising distributed architectures for DER control in the grid. The unique characteristics of Australian distribution networks highlights several challenging problems for DER control and management. The objective of this paper is to provide a broad overview of DER control and management strategies in the Australian context, with an application focus on DER control in distribution network management. [ABSTRACT FROM AUTHOR]

Assessments of the hosting capacity of electricity distribution networks are of paramount importance, as they facilitate the seamless integration of rooftop photovoltaic systems into the grid, accelerating the transition towards a more carbon neutral and sustainable system. This paper employs a deep reinforcement learning-based approach to evaluate the real-time hosting capacity of low voltage distribution networks in a model-free manner. The proposed approach only requires real-time customer voltage data and solar irradiation data to provide a fast and accurate estimate of real-time hosting capacity at each customer connection point. This study addresses the imperative for accurate electrical models, which are frequently unavailable, in evaluating the hosting capacity of electricity distribution networks. To meet this challenge, the proposed approach utilizes a deep neural network-based, data-driven model of a low-voltage electricity distribution network. This proposed methodology incorporates model-free elements, enhancing its adaptability and robustness. In addition, a comparative analysis between model-based and model-free hosting capacity assessment methods is presented, highlighting their respective strengths and weaknesses. The utilization of the proposed hosting capacity estimation model enables distribution network service providers to make well-informed decisions regarding grid planning, leading to cost minimization. [ABSTRACT FROM AUTHOR]

Large-scale renewable energy plants, flexible AC (alternating current) and high voltage DC (direct current) transmission systems, and modern consumer devices utilize power electronics that tend to increase harmonic emissions. Furthermore, such emissions are nowadays known to exceed the traditional 2 kHz range typically considered for harmonic analysis. However, the accuracy of such harmonic measurements in medium and high voltage networks is questionable due to the lack of accuracy specifications for the respective instrument transformers that are being used in the measurement chain. Therefore, the motivation of this study is to review the existing techniques for measuring high-frequency voltage harmonics, i.e., those in the range 2–9 kHz, in medium-, high-, and extra high-voltage electricity networks, where most large-scale power electronic converters are being connected. Different transducer types are compared in terms of measurement accuracy. The reviewed literature indicates that some transducers can introduce errors due to their nonlinearities. The study also identifies the limitations of calibrating these transducers at frequencies above 2 kHz due to the unavailability of suitable sources capable of generating the required test waveforms. Furthermore, the study emphasizes the necessity for establishing accuracy limits for harmonic measurements above 2 kHz. [ABSTRACT FROM AUTHOR]

Increasing connection rates of rooftop photovoltaic (PV) systems to electricity distribution networks has become a major concern for the distribution network service providers (DNSPs) due to the inability of existing network infrastructure to accommodate high levels of PV penetration while maintaining voltage regulation and other operational requirements. The solution to this dilemma is to undertake a hosting capacity (HC) study to identify the maximum penetration limit of rooftop PV generation and take necessary actions to enhance the HC of the network. This paper presents a comprehensive review of two topics: HC assessment strategies and reinforcement learning (RL)-based coordinated voltage control schemes. In this paper, the RL-based coordinated voltage control schemes are identified as a means to enhance the HC of electricity distribution networks. RL-based algorithms have been widely used in many power system applications in recent years due to their precise, efficient and model-free decision-making capabilities. A large portion of this paper is dedicated to reviewing RL concepts and recently published literature on RL-based coordinated voltage control schemes. A non-exhaustive classification of RL algorithms for voltage control is presented and key RL parameters for the voltage control problem are identified. Furthermore, critical challenges and risk factors of adopting RL-based methods for coordinated voltage control are discussed. [ABSTRACT FROM AUTHOR]

Voltage rise caused by high levels of distributed generation is manifesting as voltage regulation challenges for many electricity network service providers. In this environment it would be ideal to reduce supply voltage magnitudes, however, many network operators are hesitant to do so due to concerns related to consumer appliance performance at reduced supply voltage magnitudes. Voltage regulation requirements are defined by network standards and network service providers must ensure voltages remain within specified limits. Through an evaluation of domestic appliance performance when supplied at various voltage magnitudes, this paper examines the impact of varying voltage levels on residential appliances. Equipment energy demand, operation and actuation were monitored for each applied voltage magnitude. While no equipment failures were recorded, appliance behaviour varied significantly with applied voltage magnitude. Individual appliance conservation voltage reduction (CVR) factors have also been established. The results highlight the importance of good voltage regulation and provide substantiated appliance performance figures for future studies. The outcomes of this paper allow electricity network service providers to understand the implications of supply voltage magnitude on domestic appliance performance, whether it be understating of the impact of higher voltage magnitudes caused by distributed generation or implications of reducing voltage magnitudes to provide headroom for distributed generation integration. [ABSTRACT FROM AUTHOR]

This article presents two low bandwidth distributed model predictive control (MPC) based algorithms for the coordinated control of residential energy storage (ES) to mitigate overvoltage and reduce peak demand along LV radial distribution feeders. Each ES unit consists of a low level controller (LLC) that utilises MPC with three distinct objective functions that can optimise for financial benefit, voltage regulation and peak shaving. These modes are activated via binary signals sent by the high level controller (HLC). The HLC, operating at the feeder level, determines if any network violations such as overvoltage or overloading are predicted to occur. Using inter-bus $\boldsymbol{P}$ , $\boldsymbol{|V|}$ and $\boldsymbol{\Delta P}$ data, the HLC determines the minimum ES units to dispatch to mitigate these issues. The result is a very low bandwidth distributed control architecture with low computational complexity, that can achieve acceptable network operating conditions while dispatching the minimum number of ES units. The proposed distributed MPC algorithms were shown to outperform decentralised control strategies for voltage regulation and peak shaving from the Australian Standards and also had significantly less computational requirements than a centralised MPC controller to achieve the same network overvoltage and peak load objectives. [ABSTRACT FROM AUTHOR]

Objective To describe the successful use of an autotransfusion technique utilizing 2 syringes in 4 dogs. Case Series Summary All 4 dogs in this series had a hemoabdomen and subsequent hypovolemic shock. During surgery blood was collected from the abdominal cavity by the surgeon and passed to an assistant. The blood was then transferred to a second syringe for direct IV administration. The blood was passed through an inline blood filter prior to reaching the patient. Given the transfusion volume and administration time frame, 3 cases were classified as a massive transfusion. All 4 dogs survived the transfusion, were discharged within 3 days of surgery/transfusion and no complications were noted. New or Unique Information Provided This case series describes a relatively simple method of performing an autotransfuion in patients with hemoabdomen and hypovolemic shock. [ABSTRACT FROM AUTHOR]

• Unbalance load sharing in islanded microgrids using negative sequence power droop. • New consensus-based secondary-level control scheme for cooperative adjustment of droop gains. • Cooperative controller reduces voltage unbalance at sensitive load buses. • Small signal analysis of the consensus dynamics for a converter-based Microgrid. • Simulation model demonstration for a 4-bus microgrid power system. It is common for industrial and commercial microgrids to experience high levels of load unbalance when operating in islanded mode, which degrades the real output power capability of inverters, causes power quality problems, and impacts on the protection regime. Conventional droop control methods are not designed for sharing of unbalance power where multiple inverters are used, and existing proposals for negative sequence power sharing have several practical disadvantages which are identified. This paper proposes a novel secondary scheme for cooperative adjustment of negative sequence droop gains for voltage source converters. The new design provides an option for sharing of unbalance power, while also correcting voltage unbalance at sensitive buses. In contrast to other designs, the scheme proposes hierarchical unbalance control using a fully distributed architecture. It is robust to communication network failure and adapts to impedance changes in the electrical network. A simulation model of the proposed scheme is demonstrated using MATLAB/Simulink for a reference case. [ABSTRACT FROM AUTHOR]

Energy efficiency is a complex topic to integrate into higher education curricula, with limited success internationally or in Australia. This paper discusses one of the successful initiatives within the Energy Efficiency Training Program , which was jointly managed and implemented by the New South Wales Office of Environment and Heritage and Department of Education and Communities. The state government initiative aimed to increase the knowledge and skills of the New South Wales workforce, help business to identify and implement energy efficiency projects, and provide professional development for the training providers. Key sectors targeted included property, construction, manufacturing and services. The Program was externally evaluated over the three years 2011–2013 and a range of insights were gained through these facilitated reflective opportunities, confirming and building upon literature on the topic to date. This paper presents lessons learned from the engineering part of the program (‘the project’), spanning government agencies, academic institutions, and academia. The paper begins with a contextual summary, followed by a synthesis of key learnings and implications for future training initiatives. It is intended that sharing these lessons will contribute to literature in the field, and assist other organisations in Australia and overseas planning similar initiatives. [ABSTRACT FROM AUTHOR]

The development of cooperative control strategies for microgrids has become an area of increasing research interest in recent years, often a result of advances in other areas of control theory such as multi-agent systems and enabled by rapid advances in wireless communications technology and power electronics. Though the basic concept of cooperative action in microgrids is intuitively well-understood, a comprehensive survey of this approach with respect to its limitations and wide range of potential applications has not yet been provided. The objective of this paper is to provide a broad overview of cooperative control theory as applied to microgrids, introduce other possible applications not previously described, and discuss recent advances and open problems in this area of microgrid research. [ABSTRACT FROM AUTHOR]

In recent years, integration of solar photovoltaic (PV) systems into distribution networks has been increasing rapidly, as it has become the most promising renewable energy source (RES) in the transition of power generation from centralised to decentralised systems. With the power electronic (PE) interfaces that use high-frequency internal switching, all renewable energy sources are considered to be harmonic emitters, especially near switching frequencies, i.e., above 2 kHz. This paper evaluates the behaviour of high-frequency harmonics in the 2–20 kHz range due to the parallel operation of multiple solar PV inverters connected to a low-voltage (LV) network. The circulation current component that flows within the installation due to the low impedance paths at higher frequencies is analysed. Summation of high-frequency harmonic currents is observed with phase diversity analysis. The circulating current component can become 14 times higher than the grid current component at higher frequencies. [ABSTRACT FROM AUTHOR]

This study presents an agglomerative hierarchical clustering-based strategy using Shared Nearest Neighbours and multiple dissimilarity measures to identify typical daily electricity usage profiles of university library buildings. The proposed strategy takes the advantages of three dissimilarity measures (i.e. Euclidean distance, Pearson distance and Chebyshev distance) to calculate the difference between daily electricity usage profiles. Two-year hourly electricity usage data collected from two different university library buildings were employed to evaluate the performance of this strategy. It was shown that this strategy, which considered both magnitude dissimilarity and variation dissimilarity simultaneously, can identify more informative typical daily electricity usage profiles, in comparison with other twelve clustering-based strategies which used a single dissimilarity measure. Some interesting information related to building energy usage behaviours was also discovered with the help of visualisation techniques. Additional or hidden information discovered using this strategy can potentially be useful for fault detection and diagnosis and performance enhancement of library buildings. • A clustering-based strategy for multi-function educational buildings was presented. • It was developed based on three dissimilarity measures and Shared Nearest Neighbours. • An agglomerative hierarchical clustering method was used to group the load profiles. • It outperformed twelve other strategies that used a single dissimilarity measure. [ABSTRACT FROM AUTHOR]

Highlights • A strategy was developed to identify building typical electricity usage profiles. • This strategy consists of intra-building clustering and inter-building clustering. • This strategy can discover electricity usage behaviors of multiple buildings. • This strategy outperformed two single-step clustering strategies. Abstract This paper presents a clustering-based strategy to identify typical daily electricity usage (TDEU) profiles of multiple buildings. Different from the majority of existing clustering strategies, the proposed strategy consists of two levels of clustering, i.e. intra-building clustering and inter-building clustering. The intra-building clustering used a Gaussian mixture model-based clustering to identify the TDEU profiles of each individual building. The inter-building clustering used an agglomerative hierarchical clustering to identify the TDEU profiles of multiple buildings based on the TDEU profiles identified for each individual building through intra-building clustering. The performance of this strategy was evaluated using two-year hourly electricity consumption data collected from 40 university buildings. The results showed that this strategy can discover useful information related to building electricity usage, including typical patterns of daily electricity usage (DEU) and periodical variation of DEU. It was also shown that this proposed strategy can identify additional electricity usage patterns with a less computational cost, in comparison to two single-step clustering strategies including a Partitioning Around Medoids-based clustering strategy and a hierarchical clustering strategy. The results obtained from this study could be potentially used to assist in improving energy performance of university buildings and other types of buildings. [ABSTRACT FROM AUTHOR]

Objectives: There is a high incidence of asymptomatic sexually transmitted infections (STIs) in emergency department (ED) patients. There is no historical indication, physical examination finding, or rapidly available laboratory testing specific for detecting STIs in women. This study was conducted to describe the performance of an ED call-back system for STI screening and linkage to care for treatment. Success was defined as the ability to contact STI-positive women who were undertreated and confirm their return for definitive treatment. Methods: This retrospective, observational study of women 16 years and older evaluated those undertreated for STIs in the ED during the 13-month study period. A structured chart review was performed to determine the proportion of patients returning to an affiliated hospital ED or clinic for treatment after contact by telephone or letter. Results: Of 361 patients identified as undertreated, 29.4% (95% confidence interval [CI] 24.7-34.1) did not return for definitive treatment. The method of contact was associated with patient return for treatment. Of the 276 patients contacted by telephone, 19.6% did not return for treatment (95% CI 14.9-24.3); of the 83 patients contacted by letter, 60.2% did not return for treatment (95% CI 49.7-70.8; P < 0.0001). Conclusions: A large proportion of patients undertreated for an STI did not return despite a notification of need for further treatment. This study had a high rate of successful telephone contact (76.5%), but contact did not substantially increase the overall proportion of patients who were linked to care and returned to the ED for treatment. [ABSTRACT FROM AUTHOR]

Although it is commonly assumed that power swing is symmetrical and will have identical effects on all three-phase voltages and currents, there is another type of power swing, which is asymmetrical and mainly occurs during single-pole tripping (SPT), the impact of which on power systems integrated with the inverter-based resources (IBRs) has not been investigated so far. Since the likelihood of the occurrence of asymmetrical power swing is increasing in today's heavily loaded transmission lines, this article investigates the impact of IBR integration on the performance of distance protection during single-pole tripping. Furthermore, a new scheme is proposed to detect earth faults that occur during asymmetrical power swings to enhance the performance of power swing blocking functions. To do so, the superimposed component of the zero-sequence current during SPT is extracted. Then, the moving average window is used to calculate the average of both zero-sequence current and its superimposed component. Furthermore, to enhance the security of the proposed scheme, a new technique based on the phase angle shift between the three-phase currents is devised to detect the asymmetrical power swing conditions. This article shows that as the penetration level of IBRs increases, the standard reclosing dead-time needs to be revisited otherwise it can create an unstable power swing condition, even during SPT. Moreover, this article shows that the proposed earth fault detection scheme can efficiently detect all single-line-to-ground faults occurring during SPT. [ABSTRACT FROM AUTHOR]

Power generation through solar photovoltaics has shown significant growth in recent years. However, high penetration of solar PV creates power system operational issues as a result of solar PV variability and uncertainty. Short-term PV variability mainly occurs due to the intermittency of cloud cover. Therefore, to mitigate the effects of PV variability, a sky-image-based, localized, global horizontal irradiance forecasting model was introduced considering the individual cloud motion, cloud thicknesses, and the elevations of clouds above the ground level. The proposed forecasting model works independently of any historical irradiance measurements. Two inexpensive sky camera systems were developed and placed in two different locations to obtain sky images for cloud tracking and cloud-based heights. Then, irradiance values for onsite and for a PV site located with a distance of 2 km from the main camera were forecasted for 1 minute, 5 minutes, and 15 minutes ahead of real-time. Results show that the three-level cloud categorization and the individual cloud movement tracking method introduced in this paper increase the forecasting accuracy. For partially cloudy and sunny days, the forecasting model for 15 min forecasting time interval achieved a positive skill factor concerning the persistent model. The accuracy of determining the correct irradiance state for a 1 min forecasting time interval using the proposed model is 81%. The average measures of RMSE, MAE, and SF obtained using the proposed method for 15 min forecasting time horizon are 101 Wm-2, 64 Wm-2, and 0.26, respectively. These forecasting accuracy levels are much higher than the other benchmarks considered in this paper. [ABSTRACT FROM AUTHOR]

This study presents a new strategy using cluster analysis, Cubist regression models and Particle Swarm Optimization to forecast next-day total electricity usage and peak electricity demand of a building portfolio. Cluster analysis with a combined dissimilarity measure was first used to group daily electricity usage profiles of the building portfolio. The clustering result was then considered in the training of the Cubist-based forecasting models in order to improve the forecasting accuracy. A Particle Swarm Optimization algorithm was used to determine the optimal parameters in the cluster analysis to further improve the forecasting accuracy. The performance of this strategy was evaluated using the electricity usage data of 40 university buildings. The results showed that the difference between the measured and predicted daily total electricity usage was 4.7% in terms of the coefficient of variation of the root-mean-squared error (CV(RMSE)) and 3.3% in terms of mean absolute percentage error (MAPE) and the difference between the measured and predicted daily peak load was 6.0% in CV(RMSE) and 5.3% in MAPE. The proposed strategy can effectively improve the accuracy of the forecasting result by up to 18.1% and 12.2% when compared to the strategy which did not consider the clustering result of the daily electricity usage profiles in the forecasting models and the strategy which considered the clustering result obtained using a single dissimilarity measure. Compared to the mean level of the nine strategies that used different regression methods, the proposed strategy can improve the forecasting accuracy by up to 42.2%. The results of this study can be further used to assist in the development of building optimal control and operation strategies. • A strategy was developed for electricity usage forecasting of campus buildings. • Clustering with a combined distance was used to improve forecasting performance. • Parameters in the clustering were optimized using Particle Swarm Optimization. • Cubist regression models were used to increase forecasting accuracy. • This strategy outperformed other electricity usage forecasting strategies compared. [ABSTRACT FROM AUTHOR]

OBJECTIVE To compare the torsional mechanical properties of 2 external skeletal fixators (ESFs) placed with 2 intramedullary pin (IP) and transfixation pin (TP) size combinations in a model of raptor tibiotarsal bone fracture. SAMPLE 24 ESF-synthetic tibiotarsal bone model (polyoxymethylene) constructs. PROCEDURES Synthetic bone models were fabricated with an 8-mm (simulated fracture) gap. Four types of ESF-synthetic bone model constructs (6/group) were tested: a FESSA with a 1.6-mm IP and 1.6-mm TPs, a FESSA with a 2.0-mm IP and l.l-mm TPs, an acrylic connecting bar with a 1.6-mm IP and 1.6-mm TPs, and an acrylic connecting bar with a 2.0-mm IP and l.l-mm TPs. Models were rotated in torsion (5°/s) to failure or the machine angle limit (80°). Mechanical variables at yield and at failure were determined from load deformation curves. Effects of overall construct type, connecting bar type, and IP and TP size combination on mechanical properties were assessed with mixed-model ANOVAs. RESULTS Both FESSA constructs had significantly greater median stiffness and median torque at yield than both acrylic bar constructs; FESSA constructs with a 1.6-mm IP and 1.6-mm TPs had greatest stiffness of all tested constructs and lowest gap strain at yield. No FESSA constructs failed during testing; 7 of 12 acrylic bar constructs failed by fracture of the connecting bar at the interface with a TP. CONCLUSIONS AND CLINICAL RELEVANCE Although acrylic bar ESFs have been successfully used in avian patients, the FESSA constructs in this study were mechanically superior to acrylic bar constructs, with greatest benefit resulting from use with the larger TP configuration. [ABSTRACT FROM AUTHOR]

OBJECTIVE To describe the torsional and axial compressive properties of tibiotarsal bones of red-tailed hawks (8uteo jamaicensis). SAMPLE 16 cadaveric tibiotarsal bones from 8 red-tailed hawks. PROCEDURES I tibiotarsal bone from each bird was randomly assigned to be tested in torsion, and the contralateral bone was tested in axial compression. Intact bones were monotonically loaded in either torsion (n = 8) or axial compression (8) to failure. Mechanical variables were derived from loaddeformation curves. Fracture configurations were described. Effects of sex, limb side, and bone dimensions on mechanical properties were assessed with a mixed-model ANOVA. Correlations between equivalent torsional and compressive properties were determined. RESULTS Limb side and bone dimensions were not associated with any mechanical property. During compression tests, mean ultimate cumulative energy and postyield energy for female bones were significantly greater than those for male bones. All 8 bones developed a spiral diaphyseal fracture and a metaphyseal fissure o r fracture during torsional tests. During compression tests, all bones developed a crushed metaphysis and a fissure or comminuted fracture of the diaphysis. Positive correlations were apparent between most yield and ultimate torsional and compressive properties. CONCLUSIONS AND CLINICAL RELEVANCE The torsional and axial compressive properties of tibiotarsal bones described in this study can be used as a reference for investigations into fixation methods for tibiotarsal fractures in red-tailed hawks. Although the comminuted and spiral diaphyseal fractures induced in this study were consistent with those observed in clinical practice, the metaphyseal disruption observed was not and warrants further research. [ABSTRACT FROM AUTHOR]

Low voltage devices connected to public electricity supply networks can be subjected to a wide range of voltage quality, including sustained overvoltage. Assessing the impact of sustained overvoltage on devices connected to the distribution network is important in determining the appropriate variance of standard voltage levels without unduly impacting the utility and customers from a technical and economic perspective. Therefore, a clear understanding of the impact that sustained overvoltage has on the lifetime of the connected equipment is a necessary task. This paper investigates the impact of sustained overvoltage through a series of accelerated-life testing experiments on a custom designed test device representative of a common interface between the power supply and distribution network, a switch mode power supply. The switch mode power supply with combined rectifier and filtering capacitor represents one of the most common front ends of LV equipment in modern appliances, and the work here concentrates on the impact of overvoltage on capacitor ageing. The results of the testing indicate that there is an accelerated ageing impact correlated with the applied voltage magnitude. Furthermore, analysis shows that mismatches between appliance voltage rating and sustained network voltage, leading to accelerated ageing, may result in premature device failure without the consumer being aware of the root cause. [ABSTRACT FROM AUTHOR]

• High frequency (HF) emissions are a new power quality concern. • Photovoltaic (PV) inverters are major HF emission sources. • No PV inverter models suitable for HF studies are found in current literature. • A generic method is proposed to develop black box models of PV inverters for HF studies. • The models developed have less than 6.5% errors with 95% confidence. There is a growth of high frequency (HF) emissions in the range of 2–150 kHz (also known as Supraharmonics) in electricity distribution networks, primarily due to the increasing number and capacity of AC grid connected equipment having power electronic interfaces. Although PV inverters are a major HF source in electricity distribution networks, PV inverter models that are suitable for HF emission studies are yet to be developed. To this end, a generic method that can be used to develop HF models of small-scale (<5 kW), grid-tied, single-phase PV inverters using a black box approach is presented in this paper. Accordingly, HF models of three PV inverters that are commonly used in domestic and commercial installations are developed assuming standard network conditions. It is shown that these HF models are capable of successfully capturing the HF performance of the selected PV inverters under a wide range of operating conditions. The outcomes of this work are expected to broaden the knowledge pertaining to the HF emissions in the frequency range considered. [ABSTRACT FROM AUTHOR]