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BackgroundMental ill health has a high economic impact on society and employers. National and international policy advocates line manager (LM) training in mental health as a key intervention, but little is known about employer training provisions.AimsTo explore the prevalence and characteristics of organizations that offer LM training in mental health.MethodsSecondary analysis of existing longitudinal anonymised organizational-level survey data derived from computer-assisted telephone interview surveys collected in four waves (2020:1900 firms, 2021:1551, 2022:1904, 2023:1902) in England, before, during and after a global pandemic.ResultsThe proportion of organizations offering LM training in mental health increased pre- to post-pandemic (2020:50%, 2023:59%) but 41% do not currently provide it. Logistic regression confirmed that LM training is more likely to be offered by large-sized enterprises, organizations with a larger proportion of employees who are younger (aged 25-49), female, disabled and from ethnic minority communities. Sector patterns were inconsistent, but in 2023, organizations from the 'Hospitality' and 'Business Services' sectors were more likely to provide LM training than other sectors.ConclusionsContinued efforts are needed to increase the proportion of employers offering LM training in mental health, particularly small- to medium-sized enterprises, and organizations with predominantly male, White and/or older workforces.

In Australia and New Zealand, >50% of people with cystic fibrosis (CF) are adults and many of these people are pursuing vocational training and undertaking paid employment. More than 6% of adults with CF are working in health care. There is limited guidance in literature to support health care workers with CF (HCWcf) in training and in employment to support safe practice and to provide protection for themselves and their patients from the acquisition of health care associated infection. A multidisciplinary team of CF and Infectious Disease Clinicians, Infection Prevention and Control Practitioners, HCWcf, academic experts in medical ethics and representatives from universities, appraised the available evidence on the risk posed to and by HCWcf. Specific recommendations were made for HCWcf, CF health care teams, hospitals and universities to support the safe practice and appropriate support for HCWcf.Copyright © 2018 The Authors Respirology published by John Wiley & Sons Australia, Ltd on behalf of Asian Pacific Society of Respirology

A novel intelligent online demand side management system is proposed for peak load management in low voltage distribution networks. 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 by simulations of three different feeder types.

This paper proposes a comprehensive approach to the planning of distribution networks and the control of microgrids. Firstly, a Modified Discrete Particle Swarm Optimization (MDPSO) method is used to optimally plan a distribution system upgrade over a 20 year planning period. The optimization is conducted at different load levels according to the anticipated load duration curve and integrated over the system lifetime in order to minimize its total lifetime cost. Since the optimal solution contains Distributed Generators (DGs) to maximize reliability, the DG must be able to operate in islanded mode and this leads to the concept of microgrids. Thus the second part of the paper reviews some of the challenges of microgrid control in the presence of both inertial (rotating direct connected) and non-inertial (converter interfaced) DGs. More specifically enhanced control strategies based on frequency droop are proposed for DGs to improve the smooth synchronization and real power sharing minimizing transient oscillations in the microgrid. Simulation studies are presented to show the effectiveness of the control.

Protection of a distribution network in the presence of distributed generators (DGs) using overcurrent relays is a challenging task because of the changes in fault current levels and reverse power flow. Specifically, in the presence of current limited converter interfaced DGs, overcurrent relays may fail to isolate the faulted section either in grid connected or islanded mode of operation. In this study, a new inverse-type relay is presented to protect a distribution network, which may have several DG connections. The new relay characteristic is designed based on the measured admittance of the protected line. The relay is capable of detecting faults under changing fault current levels. The relay performance is evaluated using PSCAD simulation and laboratory experiments.

A novel intelligent demand side management system is proposed for peak load management in LV residential distribution networks in the presence of plug-in electric vehicles. This method uses low cost controllers with low bandwidth two-way communication, installed in the householders' premises and distribution transformers, to manage the peak load while maximizing customer comfort. 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 in reducing peak load while satisfying customer load objectives is verified by simulation.

In this paper, the placement and sizing of Distributed Generators (DG) in distribution networks are determined using optimization. The objective is to minimize the loss and to improve the reliability at lowest cost. The constraints are the bus voltage, feeder current and the reactive power flowing back to the source side. The placement and size of DGs are optimized using a combination of Discrete Particle Swarm Optimization (DPSO) and Genetic Algorithm (GA). This increases the diversity of the optimizing variables in DPSO not to be trapped in a local minimum. To evaluate the proposed algorithm, the semi-urban 37-bus distribution system connected at bus 2 of the Roy Billinton Test System (RBTS), which is located at the secondary side of a 33/11 kV distribution substation, is used. The results illustrate the efficiency of the proposed method.

This paper compares the performance of two droop control schemes in a hybrid microgrid. With presence of both converter interfaced and inertial sources, the droop controller share power in a decentralized fashion. Both the droop controllers facilitate reactive power sharing based on voltage droop. However in frequency droop control, the real power sharing depends on the frequency, while in angle droop control, it depends on output voltage angle. For converter interfaced sources this reference voltage is tracked while for inertial DG, reference power for the prime mover is calculated from the reference angle with the proposed angle control scheme. This coordinated control scheme shows significant improvement in system performance. The comparison with the conventional frequency droop shows that the angle control scheme shares power with much lower frequency deviation. This is a significant improvement particularly in a frequent load changing scenario.

This paper describes the optimization of conductor size and the voltage regulator location & magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.

In this paper, a new power sharing control method for a microgrid with several distributed generation units is proposed. The presence of both inertial and non-inertial sources with different power ratings, maximum power point tracking, and various types of loads pose a great challenge for the power sharing and system stability. The conventional droop control method is modified to achieve the desired power sharing ensuring system stability in a highly resistive network. A transformation matrix is formed to derive equivalent real and reactive power output of the converter and equivalent feedback gain matrix for the modified droop equation. The proposed control strategy, aimed for the prototype microgrid planned at Queensland University of Technology, is validated through extensive simulation results using PSCAD/EMTDC software.

This paper reports the initial steps of research on planning of rural networks for MV and LV. In this paper, two different cases are studied. In the first case, 100 loads are distributed uniformly on a 100 km transmission line in a distribution network and in the second case, the load structure become closer to the rural situation. In case 2, 21 loads are located in a distribution system so that their distance is increasing, distance between load 1 and 2 is 3 km, between 2 and 3 is 6 km, etc). These two models to some extent represent the distribution system in urban and rural areas, respectively. The objective function for the design of the optimal system consists of three main parts: cost of transformers, and MV and LV conductors. The bus voltage is expressed as a constraint and should be maintained within a standard level, rising or falling by no more than 5%.

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

The design and implementation of a high-power (2 MW peak) vector control drive is described. The inverter switching frequency is low, resulting in high-harmonic-content current waveforms. A block diagram of the physical system is given, and each component is described in some detail. The problem of commanded slip noise sensitivity, inherent in high-power vector control drives, is discussed, and a solution is proposed. Results are given which demonstrate the successful functioning of the system