发表机构
UniSA STEM, The University of South Australia; School of Computer, Data and Mathematical Sciences Western Sydney University; Department of Electrical and Computer Systems Engineering Monash University; School of Mathematics, Monash University; Australian Energy Market Commission; Department of Mathematical and Physical Sciences, La Trobe University（南澳大学 UniSA STEM; 西悉尼大学计算机、数据与数学科学学院; 蒙纳士大学电气与计算机系统工程系; 蒙纳士大学数学学院; 澳大利亚能源市场委员会; 拉筹伯大学数学与物理科学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对澳大利亚能源部门提出一套可靠性风险度量指标，以平衡经济效益与风险管理，处理尾部风险并直接解释停电严重性，通过模拟研究验证其属性，为提高能源部门效率提供新工具。
AI 中文摘要
本文确定了澳大利亚能源部门可靠性风险度量应具备的理想属性。文章提出了一套全面的度量指标，旨在衡量当发电量中很大一部分来自可变可再生能源（VRE）时可靠性风险的各个方面。所建议的方法旨在平衡经济效益与风险管理之间的权衡，有效处理尾部风险，并以直接的方式解释停电的严重程度。通过使用预期未供电能量值时间序列的模拟研究，对所考虑的可靠性度量的属性进行了调查。研究了样本分布、依赖结构以及这些度量的其他统计属性。结果表明，新的工具和方法可用于提高澳大利亚能源部门的效率。
英文摘要
The article identifies the desired properties of the reliability risk metric for the Australian Energy Sector. It proposes a comprehensive set of metrics designed to measure various aspects of the reliability risk when a large portion of power generation is composed of variable renewable energy (VRE). The suggested methods aim to balance the tradeoff between economic benefit and risk management, effectively address the tail risk, and interpret the severity of the outage in a direct way. Properties of the considered reliability metrics are investigated by using simulation studies that use time series of expected unserved energy values. Sample distributions, dependency structures and other statistical properties of the metrics are studied. The results suggest new tools and approaches that can be used to increase the efficiency of the Australian Energy Sector.
Comments33 pages, 15 figures
Journal refANZIAM Journal, (2023), 65:4-41
DOI：10.21914/anziamproc.v65.19124
