| 000 | 04186nlm1a2200433 4500 | ||
|---|---|---|---|
| 001 | 667926 | ||
| 005 | 20231030042131.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\39137 | ||
| 090 | _a667926 | ||
| 100 | _a20220516a2021 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aA Statistical Analysis of Wind Speed Probabilistic Distributions for the Wind Power Assessment in Different Regions _fYu. D. Bay, N. Yu. Ruban, A. S. Gusev, M. V. Andreev |
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| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References.: 20 tit.] | ||
| 330 | _aThe penetration of renewable energy sources (RES) into the electricity supply is gaining popularity all over the world, including countries that have large oil and gas reserves, since only the development of alternative energy will help avoid regression and take a green path development, reducing the damage to the environment. According to estimates of the International Energy Agency (IEA), the capacity of RES units built in China in 2016 was 34 GW, and Australia is one of the world leaders in the photovoltaic power plants installation, the share of which in the Australian electricity production exceeds 3%. It should be noted, that the final power generation capacity and stability are stochastic (probabilistic) in nature. Unlike the classical type generator, the output RES characteristics depend on the geographical features of the installation area, the season, and prevailing winds. Risks associated with inaccurate knowledge of the cumulative distribution function (CDF) describing these sources, as well as environmental uncertainties, are the reasons why it is more difficult for distribution network operators (DNO) to take RES into account in the power balance calculations. The wind speed CDF clarification can provide significant assistance in predicting the RES power production. | ||
| 333 | _aРежим доступа: по договору с организацией-держателем ресурса | ||
| 461 | _tPrzeglad Elektrotechniczny | ||
| 463 |
_tVol. 97, iss. 12 _v[P. 82-85] _d2021 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _apower system | |
| 610 | 1 | _awind speed time series | |
| 610 | 1 | _aprobability density function | |
| 610 | 1 | _acumulative distribution function | |
| 610 | 1 | _aэнергосистемы | |
| 610 | 1 | _aскорость ветра | |
| 701 | 1 |
_aBay _bYu. D. _cSpecialist in the field of electric power engineering _cAssistant of the Department of Tomsk Polytechnic University _f1991- _gYuly Dmitrievich _2stltpush _3(RuTPU)RU\TPU\pers\40030 |
|
| 701 | 1 |
_aRuban _bN. Yu. _cspecialist in the field of electric power engineering _cAssociate Professor of Tomsk Polytechnic University, Candidate of Sciences _f1988- _gNikolay Yurievich _2stltpush _3(RuTPU)RU\TPU\pers\34749 |
|
| 701 | 1 |
_aGusev _bA. S. _cspecialist in the field of electric power engineering _cProfessor of Tomsk Polytechnic University, Doctor of technical sciences _f1947- _gAlexander Sergeevich _2stltpush _3(RuTPU)RU\TPU\pers\32885 |
|
| 701 | 1 |
_aAndreev _bM. V. _cspecialist in the field of electric power engineering _cAssociate Professor of Tomsk Polytechnic University, Candidate of technical sciences _f1987- _gMikhail Vladimirovich _2stltpush _3(RuTPU)RU\TPU\pers\35035 |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа энергетики _bНаучно-исследовательская лаборатория "Моделирование электроэнергетических систем" _h192 _2stltpush _3(RuTPU)RU\TPU\col\23567 |
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа энергетики _bОтделение электроэнергетики и электротехники _h8022 _2stltpush _3(RuTPU)RU\TPU\col\23505 |
| 801 | 2 |
_aRU _b63413507 _c20220516 _gRCR |
|
| 856 | 4 | _uhttps://doi.org/10.15199/48.2021.12.14 | |
| 942 | _cCF | ||