Energy Loss Impact in Electrical Smart Grid Systems in Australia

Abstract

This research draws attention to the potential and contextual influences on energy loss in Australia’s electricity market and smart grid systems. It further examines barriers in the transition toward optimising the benefit opportunities between electricity demand and electricity supply. The main contribution of this study highlights the impact of individual end-users by controlling and automating individual home electricity profiles within the objective function set (AV) of optimum demand ranges. Three stages of analysis were accomplished to achieve this goal. Firstly, we focused on feasibility analysis using ‘weight of evidence’ (WOE) and ‘information value’ (IV) techniques to check sample data segmentation and possible variable reduction. Stage two of sensitivity analysis (SA) used a generalised reduced gradient algorithm (GRG) to detect and compare a nonlinear optimisation issue caused by end-user demand. Stage three of analysis used two methods adopted from the machine learning toolbox, piecewise linear distribution (PLD) and the empirical cumulative distribution function (ECDF), to test the normality of time series data and measure the discrepancy between them. It used PLD and ECDF to derive a nonparametric representation of the overall cumulative distribution function (CDF). These analytical methods were all found to be relevant and provided a clue to the sustainability approach. This study provides insights into the design of sustainable homes, which must go beyond the concept of increasing the capacity of renewable energy. In addition to this, this study examines the interplay between the variance estimation of the problematic levels and the perception of energy loss to introduce a novel realistic model of cost–benefit incentives. This optimisation goal contrasted with uncertainties that remain as to what constitutes the demand impact and individual house effects in diverse clustering patterns in a specific grid system. While ongoing effort is still needed to look for strategic solutions for this class of complex problems, this research shows significant contextual opportunities to manage the complexity of the problem according to the nature of the case, representing dense and significant changes in the situational complexity.

Power Grid Intelligent Energy Dispatching Interactive System Based on Virtual Reality Technology

“…e prototype system of AO is developed, the hardware design and software structure based on cluster computers are given; and the software functions and algorithms are introduced. e AO prototype system is tested and analyzed for a provincial power system [3]. Sang and others extended the concept of energy dispatching center, put forward the concept of modern energy control center, and focused on the transformation of control centers in informatization, automation, integration, and intelligence, including applying information theory to analyze the information flow of power systems, rebuilding the original appearance of real power systems, and improving the operating conditions of power systems.…”

Monitoring Energy-Loss-Driven-Cost by Using Earned Value Simulation in Complex Systems

“…In this study, methods were employed to analyse electricity demand data sourced from the Australian Energy Market Operator (AEMO). The process adhered to the guidelines outlined in [1] and [2], utilising Python programming language to establish a data frame for subsequent analysis. Confidence levels of 99% and 1%, along with confidence intervals, were employed, forming a robust foundation for further exploration [1,2].…”

“…The process adhered to the guidelines outlined in [1] and [2], utilising Python programming language to establish a data frame for subsequent analysis. Confidence levels of 99% and 1%, along with confidence intervals, were employed, forming a robust foundation for further exploration [1,2]. Pearson's correlation coefficient (PCC) played a pivotal role in unveiling the relationships among variables.…”

“…In Australia, territories are seamlessly interconnected through regional networks, fostering the economic sharing of generation. The functional boundaries of transmission and distribution networks are delineated within and outside National Electricity Market (NEM) jurisdictions [1]. Subsequently, the production and demand of electricity are intricately synchronised to instant changes, maintaining real-time system balance.…”

Integrated diagnosis and time-series sensitivity evaluation of nutrient deficiencies in medicinal plant (Ligusticum chuanxiong Hort.) based on UAV multispectral sensors

“…Mask images were made using the support vector machine (SVM) algorithm ( Figure 3 ), and vegetation indices were calculated ( Table 1 ). Then the image was segmented, and mask extracted the sample mean reflectance and vegetation index ( Hassanzadeh et al., 2020 ), then removed redundant variables through the information value (IV) and correlation between variables ( Zaghwan and Gunawan, 2021 ). Correlation coefficients between variables were calculated by person correlation analysis, and 90% was used as the correlation threshold to remove redundant variables ( Hassanzadeh et al., 2020 ).…”