• Energy Research

Transmission lines play an important role in providing all participants the access to supply and demand in a competitive electricity market. Market size could be limited by the physical ability of transmission network to deliver electricity. Transmission line congestion as a primary indicator for transmission expansion planning has been investigated in this paper. The calculation on congestion cost under single side bid Poolco market is proposed and is defined as the social surplus difference between before the transmission line violation and after congestion. The generator's bidding price change is considered as a result of market factors in a deregulated electricity market. Finally, a numerical example is applied on IEEE Reliability Test Systems (RTS) for illustrating the essential features of the proposed congestion cost evaluation approach. The results are conducted using the well-known Monte-Carlo Simulation method.

On 4 August 1888, Reefton became the first town in New Zealand to have its own public electricity supply powered by hydrogeneration. In Australia, the first supply of electricity to the public at large was in two small country towns in New South Wales. Tamworth, with a population of 3,000, switched on arc and incandescent street lighting on 9 November 1888. In April 1889, the smaller town of Young switched on its incandescent street lighting and shortly thereafter went on to connect shops, offices, and homes within reach of its lines. However, the history of electricity supply in Australia traces back earlier, with Brisbane as one of the first cities in Australia to use electricity commercially, in 1882. Thus, electricity utilization down under coincided with the history of its emergence among the countries of the Northern Hemisphere.

This paper addresses the problem of diagnosing the fault symptoms of power transformers with measurement originated uncertainties, which arise from the imprecision of samples (i.e. due to noises and outliers) and the effect of class imbalance (i.e. samples are unequally distributed between different fault types) in a training dataset used to identify different fault types. Two fuzzy support vector machine (FSVM) algorithms namely fuzzy c-means clustering-based FSVM (FCM-FSVM) and kernel fuzzy c-means clustering-based FSVM (KFCM-FSVM) have been applied in this paper to deal with any noises and outliers in training dataset. In order to reduce the effect of class imbalance in training dataset, two approaches including between-class weighting and random oversampling have been adopted and integrated with FCM-FSVM and KFCM-FSVM. The case studies show that KFCM-FSVM algorithm and its variants have consistent tendency to attain satisfied classification accuracy in transformer fault diagnosis using dissolved gas analysis (DGA) measurements.

Load profiling is essential in power systems operation and planning. Accurate load profiles lead to a better load scheduling as well as load and price forecasting. Clustering techniques are used to provide an enhanced knowledge on electrical load patterns. This paper deals with clustering methods to analyze Queensland's load data. The K-means clustering method is used here, where its accuracy is measured using the clustering dispersion indicator (CDI). This method is applied on the Queensland load curves in 2013, where distinct monthly and yearly load profiles are obtained. In addition, the characteristic of each load profile depending on the day type and weather conditions are analyzed.

Increasing electrical energy demand, modern lifestyles and energy usage patterns have made the world fully dependant on power systems. This instigated mandatory requirements for the operators to maintain high reliability and stability of the power system grid. However, the power system is a highly nonlinear system, which changes its operations continuously. Therefore, it is very challenging and uneconomical to make the system be stable for all disturbances. The system is usually designed to handle a single outage at a time. However, during the last decade several major blackouts were reported and all of them started with single outages. Each major blackout was mandatorily and transparently reported to the public. The properly written blackout reports help to minimize the operational risk, by strengthening the system and its operations based on selected high risk contingencies. In the last decade, several major blackouts were reported separately in many research papers. This paper lists a good collection of properly reported literatures on power system stability and reliability including history of blackouts. Some critical comments on root causes, lessons learnt from the blackouts and solutions are addressed while briefly discussing the blackout events presented in published literatures.

This paper demonstrates the applicability of a recently reported mixed integer quadratically constrained programming (MIQCP) placement algorithm on a large scale real-world power system, based on maximizing loadability. The MIQCP algorithm partially incorporates key quadratic constraints, which were absent in MILP placement methods reported in the past. A case study based on Powerlink Queensland's HV transmission network is presented, with the system containing 886 buses and 1087 branches. A comparison is presented between the MIQCP approach and the MILP approach, showing significant improvements in solution accuracy. Additionally, through verification by an exhaustive load flow search, MIQCP is shown to provide correct SVC placement in the 886 bus network. Finally, some observations are presented based on results involving multiple SVC placements in the network.

This paper proposes and practically validates a control approach for distribution network (DN) support with customers’ battery energy storage systems (BESSs). Use of customers’ BESSs for DN support incurs a cost (disutility) to customers because a part of the storage capacity is used for DN support instead of solely benefitting the customer. An optimization problem is formulated to perform a tradeoff between the benefits to network operator and disutility to consumers. Control actions, i.e., charge and discharge trajectories of BESSs, are obtained by solving the optimization problem. Hardware in the loop (HIL) simulations of the proposed method, using a real-time digital simulator and a dSPACE controller board, are performed to assess its performance on a low voltage distribution network. HIL simulations show that in the presence of rooftop solar, the method is able to reduce voltage excursions while simultaneously reducing customers’ cost.

Partial discharge (PD) signals acquired from on-line measurements of power transformers are easily overwhelmed by various interference and noise. This paper proposes an automatic blind equalization (BE) and morphological thresholding method for PD signal de-noising. Firstly, BE automatically selects an equalized signal that reveals PD impulses from an acquired noise-corrupted signal. Then, automatic morphological thresholding (AMT) is adopted for determining thresholds on the equalized signal. After de-noising with BE and AMT, phase-resolved pulse sequence (PRPS) is constructed and used for analyzing the types of insulation defects that cause discharges. To verify the proposed method, PD measurements on experimental PD models and a distribution transformer have been conducted. The results show that PD impulses can be extracted from severely noise-corrupted signals by using the proposed method. Also, PRPS constructed from de-noised signals can achieve consistency in revealing the types of insulation defects even different types of PD sensors and measurement systems are used.