Impact of dynamic PHEVs load on renewable sources based distribution system

In this paper, charging effect of dynamic Plug in Hybrid Electric Vehicle (PHEV) is presented in a renewable energy based electricity distribution system. For planning and designing a distribution system, PHEVs are one of the most important factor as it is going to be a spinning reserve of energy, and also a major load for distribution network. A dynamic load model of PHEVs is introduced here based on third order battery model. To determine the system adequacy, it is necessary to do a micro level analysis to know the PHEVs load impact on grid. Scope of such analysis will cover the performance of wind and solar generation with dynamic PHEVs load, as well as the stability analysis of the power grid to demonstrate that it is important to consider the dynamics of PHEVs load in a renewable energy based distribution network.

Determination of the embedded lengths of electricity timber poles utilizing flexural wave generated from impacts

Round timbers are extensively used as utility poles in Australia for electricity distribution and communication. Lack of information on their conditions results in great difficulties on asset management for industries. Despite the development of various non-destructive testing (NDT) techniques for evaluating the condition of piles, few NDTs are reported for applications on timber poles. This paper addresses challenges and issues on development of NDTs for condition assessment and embedded length of timber poles. For this paper, it is mainly focusing on determining the embedded length of the pole considering loss of the sufficient embedment length is a main factor compromising capacity and safety of timber poles. Since it is impractical for generating longitudinal waves by impacting from the top of poles, utilizing flexural wave from side impact on poles becomes attractive. However, the flexural wave is known by its highly dispersive nature. In this paper, one dimensional wave theory, guided wave theory and advanced signal processing techniques have been introduced in order to provide a solution for the problem. Two signal processing techniques, namely short kernel method and continuous wavelet transform, have been investigated for processing flexural wave signals to evaluate wave velocity and embedment length of timber poles in service.

Can the electricity market be characterised by asymmetric behaviour?

In this paper, we test for asymmetric behaviour of industrial and residential electricity demand for the G7 countries, using the entropy-based test for symmetry suggested by [Racine, J., and Maasoumi, E., 2007. A versatile and robust metric entropy test of time-reversibility, and other hypotheses. Journal of Econometrics 138(2), 547–567; Racine, J., and Maasoumi, E., 2008. A robust entropy-based test of asymmetry for discrete and continuous processes. Econometric Reviews 28, 246–261], the Triples test of [Randles, R., Flinger, M., Policello, G., and Wolfe, D., 1980. An asymptotically distribution-free test for symmetry versus asymmetry. Journal of the American Statistical Association 75, 168–172] and the [Bai, J., and Ng, S., 2001. A consistent test for conditional symmetry in time series models. Journal of Econometrics 103, 225–258] test for conditional symmetry. Using data that spans over three decades, we find overwhelming evidence of conditional symmetry of residential and industrial electricity consumption. This finding implies that the use of econometric tests based on linear data generating processes is credible.

Impacts of DG penetration in the Bamaga and Gununa isolated distribution networks

Isolated distribution systems are dispersed throughout regional Queensland to supply small isolated communities that are distant from the main supply grid. The costs of maintaining the electricity supply to these areas is costly; mainly due to the cost of diesel fuel. Furthermore, there is a community focus on climate change, and Ergon Energy aims to reduce the reliance on fossil fuels whilst optimising cost efficiencies and greenhouse gas emissions. The objective of this study is to examine the impacts of renewable energy sources in isolated power systems. For the locations studied, viable renewable energy sources have been integrated into these networks. Anticipated challenges and issues with the integration of the intermittent renewable energy sources were addressed, using mitigation techniques, including energy storage solutions. The investigation and findings demonstrated that network improvements can be achieved by an ideal level of renewable penetration, which has been the main focus of the project. The project involved the development and simulation of MATLAB Simulink and SINCAL models of the two isolated networks at Gununa and Bamaga. The subsequent analysis of these systems has shown a modest penetration level of renewables can be combined with energy storage solutions, which reduces fuel consumption and greenhouse gas emissions at these locations.

Prediction interval estimation for electricity price and demand using support vector machines

Uncertainty is known to be a concomitant factor of almost all the real world commodities such as oil prices, stock prices, sales and demand of products. As a consequence, forecasting problems are becoming more and more challenging and ridden with uncertainty. Such uncertainties are generally quantified by statistical tools such as prediction intervals (Pis). Pis quantify the uncertainty related to forecasts by estimating the ranges of the targeted quantities. Pis generated by traditional neural network based approaches are limited by high computational burden and impractical assumptions about the distribution of the data. A novel technique for constructing high quality Pis using support vector machines (SVMs) is being proposed in this paper. The proposed technique directly estimates the upper and lower bounds of the PI in a short time and without any assumptions about the data distribution. The SVM parameters are tuned using particle swarm optimization technique by minimization of a modified Pi-based objective function. Electricity price and demand data of the Ontario electricity market is used to validate the performance of the proposed technique. Several case studies for different months indicate the superior performance of the proposed method in terms of high quality PI generation and shorter computational times.