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In Australia and many other countries, distribution network service providers (DNSPs) have an obligation to their customers to provide electrical power that is reliable and of high quality. Failure to do so may have significant implications ranging from financial penalties theoretically through to the loss of a license to distribute electricity. In order to ensure the reliability and quality of supply are met, DNSPs engage in monitoring and reporting practice. This paper provides an overview of a large long-running power-quality monitoring project that has involved most of Australia's DNSPs at one time or another. This paper describes the challenges associated with conducting the project as well as some of the important outcomes and lessons learned. A number of novel reporting techniques that have been developed as part of the monitoring project are also presented. A discussion about large-volume data management, and issues related to reporting requirements in future distribution networks is included. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel peak load management scheme for rural areas. The scheme transfers certain customers onto local nonembedded generators during peak load periods to alleviate network under voltage problems. This paper develops and presents this system by way of a case study in Central Queensland, Australia. A methodology is presented for determining the best location for the nonembedded generators as well as the number of generators required to alleviate network problems. A control algorithm to transfer and reconnect customers is developed to ensure that the network voltage profile remains within specification under all plausible load conditions. Finally, simulations are presented to show the performance of the system over a typical maximum daily load profile with large stochastic load variations. [ABSTRACT FROM AUTHOR]

The electricity industry in Australia has recently undergone significant restructuring. Generation, transmission and distribution have been unbundled and placed under private or public corporate ownership. Industry restructuring, together with concerns about the environment, have resulted in a noticeable increase in distributed electricity generation, especially small-scale generation. This development has important ramifications for the electricity industry and the wider economy. This paper provides an empirical analysis of the recent growth in distributed electricity generation in Australia, and analyzes the factors driving this resurgence of interest. The paper also attempts to identify the underlying factors contributing to the development of distributed generation. Past and current distributed generation projects are classified according to which technical or institutional factor was dominant in the realization of each project. This enables us to identify changes over time in the rationale for distributed generation. A comparative analysis of the developments in the different Australian states provides additional insights into the roles played by factors such as geography, the availability of low-cost industrial by-products for fuel, and the introduction of competitive markets. [ABSTRACT FROM AUTHOR]

A high penetration of rooftop solar photovoltaic (PV) resources into low-voltage (LV) distribution networks creates reverse power-flow and voltage-rise problems. This generally occurs when the generation from PV resources substantially exceeds the load demand during high insolation period. This paper has investigated the solar PV impacts and developed a mitigation strategy by an effective use of distributed energy storage systems integrated with solar PV units in LV networks. The storage is used to consume surplus solar PV power locally during PV peak, and the stored energy is utilized in the evening for the peak-load support. A charging/discharging control strategy is developed taking into account the current state of charge (SoC) of the storage and the intended length of charging/discharging period to effectively utilize the available capacity of the storage. The proposed strategy can also mitigate the impact of sudden changes in PV output, due to unstable weather conditions, by putting the storage into a short-term discharge mode. The charging rate is adjusted dynamically to recover the charge drained during the short-term discharge to ensure that the level of SoC is as close to the desired SoC as possible. A comprehensive battery model is used to capture the realistic behavior of the distributed energy storage units in a distribution feeder. The proposed PV impact mitigation strategy is tested on a practical distribution network in Australia and validated through simulations. [ABSTRACT FROM PUBLISHER]

Abstract-Harmonic monitoring has become an important tool for harmonic management in distribution system. A comprehensive harmonic monitoring program has been designed and implemented on a typical electrical medium-voltage distribution system in Australia. The monitoring program involved measurements of the three-phase harmonic currents and voltages from the residential, commercial, and industrial load sectors. Data over a three year period have been downloaded and available for analysis. The large amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. More sophisticated analysis methods are required to automatically determine which part of the measurement data are of importance. Based on this information, a closer inspection of smaller data sets can then be carried out to determine the reasons for its detection. In this paper, we classify the measurement data using unsupervised learning based on clustering techniques using the minimum message length technique, which can provide the engineers with a rapid, visually oriented method of evaluating the underlying operational information contained within the clusters. Supervised learning is then used to describe the generated clusters and to predict the occurrences of unusual clusters in future measurement data. [ABSTRACT FROM AUTHOR]

Abstract: Integration of distributed generation (DG) in a distribution network may introduce adverse effects including control interaction, oscillatory transients and operational conflicts. This paper investigates the operation of multiple voltage regulators such as on-load tap changer (OLTC) and step voltage regulator (SVR), and DG in a medium voltage distribution feeder. Investigations have been carried out using time domain simulation studies conducted using MATLAB-SimPowerSystems. The results are reported for a case study involving radial distribution feeder, derived from New South Wales (NSW) electricity distribution network in Australia. [Copyright &y& Elsevier]

The article discusses the origin and development of hydraulic power equipment and systems in Great Britain and Australia. It discusses the formation of the Melbourne Hydraulic Power Co., a public utility company, in 1888 and also states its early success and competition faced by the company from electricity distributors. It also states the acquisition of the company through legislation by the Melbourne City Council, a City Corporation. The customer base of the company is also discussed.

Virtual power plants (VPPs) have become a driving force for the decentralized energy industry, due to their efficient management and control of distributed energy resources. Most of the operation strategies for VPPs are designed based on the day-ahead forecasts. However, the prediction errors of the renewable energy sources (RES) and loads in the power dispatch schedule can lead to a suboptimal operation. In this article, an adaptive and predictive energy management strategy for a real-time optimal operation of VPPs is proposed based on the model predictive control technique with a feedback correction (FC) to compensate for the prediction error. This strategy has two parts: 1) receding-horizon optimization (RHO), and 2) FC. In the first part, a hybrid prediction algorithm based on the integration of the time-series model and the Kalman filter is used to forecast the output powers of RES and the loads. Based on the prediction, the RHO model schedules the operation following the latest forecast information. In the second part, the receding schedule is adjusted based on the fast-rolling gray model's ultrashort-term error prediction. The FC is applied to minimize the adjustments for compensating the prediction error. The proposed strategy is implemented on a VPP in a real electricity distribution system in New South Wales, Australia. The simulation results demonstrate the effectiveness of the proposed strategy with a better tracking of the actual available resources and a minimal mismatch between demand and supply. [ABSTRACT FROM AUTHOR]

• A private reliability service is proposed and can be traded in the electricity market. • A novel group double side auction method for market clearing is designed and verified. • Dynamic elasticities considering real-time preference are applied in this model. • The model provides the advised price interval for customers. • Real historical data of customers in Australia are used to verify the proposed model. Due to the rapid development of distributed renewable generation, emerging prosumers are encouraged to participate in the energy market. Meanwhile, blackout events, planned and unplanned outages due to weather, component failures and other causes, can also impact users' experience. To maintain reliability and improve users' experience under outage conditions, it is possible to transform the service reliability from a public good (compulsory and uniform) to a private good (self-selection). In this paper, a new restore mechanism based on private reliability service is proposed, the reliability service is no longer uniform. Customers with a higher reliability requirement are willing to pay to maintain their desired consumption in outage conditions. The customers are classified by dynamic elasticity considering historical data and real-time customer preferences. Then the advised unit price, trading amount and reliability level are provided to customer. Once they submit this information to market operator, the price and transaction amount is matched in each group, and floated average clearing price is applied to obtain the bidding results. The trading mechanism is proved to satisfy incentive compatibility, and the transaction process for a specific area in Australia is analyzed in a case study to verify the proposed model. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a consideration of the role of battery energy storage in enhancing electricity grid stability at a time of increased use of non-hydro renewable generation sources, focusing on the Australian case. Besides the creation of a strategic reserve one measure that might reduce this instability that have being increasingly attracted much attention by both the operators of power systems and electricity distribution networks is the use of battery energy storage. Together, the multitude of regulatory and advisory bodies operating in and around the National Electricity Market of Australia (NEM), and the diverse and sometimes contrary opinions as to the best underlying foundational architecture for the NEM, overlaid by ongoing disagreement at the government policy level, point to continuing uncertainty and difficulties for an Australian electricity system in a state of transition. [ABSTRACT FROM AUTHOR]

In Australia, geothermal energy technology is still considered an emerging technology for energy generation. Like other emerging energy technologies, how the public perceive the technology and under what conditions they are likely to accept or oppose the technology, remains relatively unknown. In response, this exploratory research utilised online focus groups to identify: (1) the extent of agreement with geothermal technology before and after information, including media reports focusing on a range of the technology's attributes; and (2) how the characteristics of individuals with different levels of agreement vary. After information, within the sample of 101 participants, fewer reported being unsure, the minority disagreed and the majority agreed. Overall, the preference was for projects to be located away from communities. Participants that disagreed or were unsure, were more likely to report lower subjective knowledge of the technology, lower perceived benefits and higher risks, and were less likely to believe people in their community would have the opportunity to participate in consultation. These characteristics suggest there are advances to be made by analyzing what contributes to different levels of acceptance. The findings also suggest that the location of projects will be an important consideration and that the conditions of acceptance are likely to vary amongst community members. [ABSTRACT FROM AUTHOR]

From the perspective of energy providers, accurate short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. However, it is hard to achieve a satisfactory result because the historical data is irregular, non-smooth, non-linear and noisy. To handle these challenges, in this work, we introduce a novel model based on the Transformer network to provide an accurate day-ahead load forecasting service. Our model contains a similar day selection approach involving the LightGBM and k-means algorithms. Compared to the traditional RNN-based model, our proposed model can avoid falling into the local minimum and outperforming the global search. To evaluate the performance of our proposed model, we set up a series of simulation experiments based on the energy consumption data in Australia. The performance of our model has an average MAPE (mean absolute percentage error) of 1.13, where RNN is 4.18, and LSTM is 1.93. [ABSTRACT FROM AUTHOR]