Probabilistic in power engineering

被引：1

作者：

Pijarski, Pawel ^{[1
]}

Miller, Piotr ^{[1
]}

Sidor, Karol ^{[1
]}

机构：

[1] Lublin Univ Technol, Fac Elect Engn & Comp Sci, Dept Elect & Secur Networks, Nadbystrzycka 38 A, Lublin, Poland

来源：

PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS 2018 | 2018年 / 10808卷

关键词：

electric power quantities; probabilistic; probability distribution; SYSTEMS;

D O I：

10.1117/12.2501391

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Some quantities in the power industry, are subject to random changes, depending on the current state of the network, atmospheric conditions, or unforeseen, in normal conditions, events. It is difficult to describe them with classical dependencies, therefore a probabilistic approach seems to be appropriate. While analyzing the measurements of these quantities, for a certain period of time, an appropriate probability distributions can be assigned to them. The article presents the results of such considerations, for selected variables based on their real values. It should be noted that some quantities result from others (due to the connection), they are a kind of compilation.

引用

收藏

页数：9

相关论文

共 50 条

[41] Applications of computational electromagnetism in electric power engineering [J].

Melgoza, Enrique ;

Escarela-Perez, Rafael ;

Corona-Sanchez, Manuel A. .

2016 IEEE PES TRANSMISSION & DISTRIBUTION CONFERENCE AND EXPOSITION-LATIN AMERICA (PES T&D-LA), 2016,

[42] Combined Gaussian Mixture Model and cumulants for probabilistic power flow calculation of integrated wind power network [J].

Ye, Lin ;

Zhang, Yali ;

Zhang, Cihang ;

Lu, Peng ;

Zhao, Yongning ;

He, Boyu .

COMPUTERS & ELECTRICAL ENGINEERING, 2019, 74 :117-129

[43] Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties [J].

Shargh, S. ;

Ghazani, B. Khorshid ;

Mohammadi-Ivatloo, B. ;

Seyedi, H. ;

Abapour, M. .

RENEWABLE ENERGY, 2016, 94 :10-21

[44] Probabilistic Power Flow Analysis With Generation Dispatch Including Photovoltaic Resources [J].

Fan, Miao ;

Vittal, Vijay ;

Heydt, Gerald T. ;

Ayyanar, Raja .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (02) :1797-1805

[45] A Fuzzy Probabilistic Power Flow Method Based on Fuzzy Copula Model [J].

Lin, Chaofan ;

Chen, Yonglin ;

Bie, Zhaohong .

2018 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC), 2018,

[46] Robust Optimization with Probabilistic Constraints for Power-Efficient and Secure SWIPT [J].

Tuan Anh Le ;

Quoc-Tuan Vien ;

Huan Xuan Nguyen ;

Ng, Derrick Wing Kwan ;

Schober, Robert .

2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2016,

[47] Modelling Correlated Forecast Error for Wind Power in Probabilistic Load Flow [J].

Huang, Yu ;

Xu, Qingshan ;

Jiang, Xianqiang ;

Zhang, Tong ;

Yang, Yang .

ELEKTRONIKA IR ELEKTROTECHNIKA, 2017, 23 (05) :61-66

[48] Deep learning based ensemble approach for probabilistic wind power forecasting [J].

Wang, Huai-zhi ;

Li, Gang-qiang ;

Wang, Gui-bin ;

Peng, Jian-chun ;

Jiang, Hui ;

Liu, Yi-tao .

APPLIED ENERGY, 2017, 188 :56-70

[49] OpenCL-Accelerated Probabilistic Power Flow for Active Distribution Networks [J].

Abdelaziz, Morad Mohamed Abdelmageed .

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2018, 9 (03) :1255-1264

[50] Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather [J].

Karangelos, Efthymios ;

Perkin, Samuel ;

Wehenkel, Louis .

APPLIED SCIENCES-BASEL, 2020, 10 (15)

← 1 2 3 4 5 →