Energy Losses Analysis for Electrical Grid Systems

Gunawan, Indra; Zaghwan, Ashraf

doi:10.1109/ieem55944.2022.9989861

Cited by 1 publication

(3 citation statements)

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“…Peak demand, representing the maximum electricity volume required at any point, establishes a rational connection between peak/off-peak demands and the reliability standards of network prices. Aging assets struggle to cover higher input and meet elevated reliability standards, contributing to rising network charges driven by electricity prices [8]. End-users, with a primary focus on residential houses, are expected to contribute to the smooth functioning of the net national product, control resource depreciation, and reduce environmental damage.…”

Section: Investment In Electricitymentioning

confidence: 99%

“…Consumer demand behaviors, beyond the grid's control, constitute a controversial research topic, introducing uncertainties in valuing externalities related to human lifestyle, health, and climate change for various electricity generation technologies [6]. Recent Australian government projects target peak time control, aiming to reduce customers' payable electricity bills and extend benefits to the broader community, recognising the dynamic nature of residential consumers' habits [8]. An electricity grid system, functioning as a complex adaptive system (CAS), encompasses end-users, economic markets, physical networks, and diverse integrated agents [9].…”

Section: Investment In Electricitymentioning

confidence: 99%

“…Historical data reveals a significant increase in electricity prices in Australia from 2008 to 2014, exceeding inflation by over 80%, as depicted in Figure 6. The primary driver for these increases is attributed to the costs associated with upgrading and maintaining the electricity network to meet end-users' demand, as shown in Figure 7 [8]. The cost breakdown in Australia and New South Wales (NSW) encompasses various factors impacting both generators and consumers, such as Base load coal technologies, Base load gas technologies, Lowest capital cost solar, and Lowest capital cost wind [16].…”

Section: Learning Curves Of Costs Vs Pricesmentioning

confidence: 99%

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

Zaghwan,

Amer,

Efatmaneshnik

et al. 2024

J Energ Power Technol

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The economic impact of energy loss stemming from end-user electricity consumption is a significant concern, with historical trends revealing escalating costs. Effectively managing both peak and off-peak demands remains a formidable challenge due to the unpredictable nature of consumer behaviors, leading to energy wastage. This study delves into the nexus of demand uncertainty, financial repercussions, and potential strategies to mitigate energy losses in the evolving landscape of electricity consumption.that causes financial loss. This simulation measure of time series data serves the purpose of determining what possibly contributes to policy and regulatory reforms and its notion as an economic growth pathway in Australia. The objective of this study is to build a relationship between social factors and financial aspects and discuss the issue of energy loss that emerges from the lack of leverage between end-users, providers and suppliers of electricity. Recognising the financial burdens associated with energy loss as electricity demand continues to rise, the investigation aims to elucidate the complexities underlying the difficulties in controlling these losses. The distinctiveness of the electricity industry, characterised by its prototypical nature, introduces dynamics that contribute to energy losses, thereby impacting electricity prices. Employing quantitative analysis, this research employs the Earned Value Method (EVM) tool to scrutinise the influential role of consumer behavior in precipitating financial losses. The study provides a comprehensive examination of the interplay between electricity demand and the adverse effects of energy loss during peak and off-peak consumption periods. Utilising time series data through simulation measures, the research identifies key metrics influencing the formation of electricity costs and prices. The findings not only contribute to a deeper understanding of the energy loss parameter but also offer insights into potential policy and regulatory reforms. With a focus on Australia, the research aims to establish a relationship between social factors and financial considerations, emphasising the issue of energy loss arising from the lack of alignment between end-users, providers, and suppliers of electricity. The study concludes by proposing pathways for economic growth through strategic interventions and collaborative efforts within the electricity ecosystem.

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Section: Investment In Electricitymentioning

confidence: 99%

Section: Investment In Electricitymentioning

confidence: 99%

Section: Learning Curves Of Costs Vs Pricesmentioning

confidence: 99%

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