Fuzzy Markov model for the reliability analysis of hybrid microgrids

IF 2.4 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Frontiers in Computer Science Pub Date : 2024-06-10 DOI:10.3389/fcomp.2024.1406086
Kunjabihari Swain, Murthy Cherukuri, Indu Sekhar Samanta, Abhilash Pati, Jayant Giri, Amrutanshu Panigrahi, Hong Qin, Saurav Mallik
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引用次数: 0

Abstract

This research presents a process for analyzing a hybrid microgrid's dependability using a fuzzy Markov model. The research initiated an analysis of the various microgrid components, such as wind power systems, solar photovoltaic (PV) systems, and battery storage systems. The states that are induced by component failures are represented using a state-space model. The research continues by suggesting a hybrid microgrid reliability model that analyzes data using a Markov process. Problems arise when trying to estimate reliability metrics for the microgrid using data that is both restricted and imprecise. This is why the study takes uncertainties into account to make microgrid reliability estimations more realistic. The importance of microgrid components concerning their overall availability is evaluated using fuzzy sets and reliability assessments. The study uses numerical analysis and then carefully considers the outcomes. The overall availability of hybrid microgrids is 0.99999.
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用于混合微电网可靠性分析的模糊马尔科夫模型
本研究提出了一种利用模糊马尔可夫模型分析混合微电网可靠性的方法。研究首先对风力发电系统、太阳能光伏(PV)系统和电池存储系统等各种微电网组件进行分析。使用状态空间模型表示组件故障引起的状态。研究还提出了一种混合微电网可靠性模型,该模型使用马尔可夫过程分析数据。在使用受限和不精确的数据估算微电网可靠性指标时会出现问题。因此,本研究考虑了不确定性因素,以使微电网可靠性估算更切合实际。研究使用模糊集和可靠性评估来评估微电网组件对其整体可用性的重要性。研究采用数值分析,然后仔细考虑结果。混合微电网的总体可用性为 0.99999。
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来源期刊
Frontiers in Computer Science
Frontiers in Computer Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.30
自引率
0.00%
发文量
152
审稿时长
13 weeks
期刊最新文献
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