Transmission adaptability planning considering cluster correlation of wind farms
Abstract Wind farm cluster penetration and its long‐distance delivery have become the important form of wind power accommodation of power network in China. For the adaptability of power network planning to the output volatility of clustering wind farms, three steps are studied as follows. Initially,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-03-01
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| Series: | IET Generation, Transmission & Distribution |
| Online Access: | https://doi.org/10.1049/gtd2.12342 |
| _version_ | 1818307941569134592 |
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| author | Shuxin Tian Jinhua Shen Libo Zhang Xijun Yang Yang Fu Yang Mi |
| author_facet | Shuxin Tian Jinhua Shen Libo Zhang Xijun Yang Yang Fu Yang Mi |
| author_sort | Shuxin Tian |
| collection | DOAJ |
| description | Abstract Wind farm cluster penetration and its long‐distance delivery have become the important form of wind power accommodation of power network in China. For the adaptability of power network planning to the output volatility of clustering wind farms, three steps are studied as follows. Initially, the output uncertainty model of clustering wind farms based on Auto Regression Integrated Moving Average (ARIMA)‐Generalized Autoregression Conditional Heteroscedasticity (GARCH)‐Pair Copula is put forward to analyze the intermittency, fluctuation and clustering wind power correlation. Secondly, Full Cost (FC) theory is introduced to account social expense brought by grid‐connected clustering wind farms from four aspects of static cost, dynamic cost, environmental cost and inter‐generational cost. Meanwhile, available wind power transmission capacity is defined to reflect wind power accommodation based on transmission margin. Finally, the adaptive efficiency index is proposed by the ratio of available wind power transmission capacity to FC. The transmission adaptability planning model considering cluster correlation of wind farms is built with the objective function of the adaptive efficiency index. Taking the actual regional power grid as an example, the results show that the planning scheme considering the optimal adaptive efficiency index of clustering wind farms can be better adapted to the future power network environment. |
| first_indexed | 2024-12-13T07:06:23Z |
| format | Article |
| id | doaj.art-1048a016f6f940eb8505aefa2c5e273e |
| institution | Directory Open Access Journal |
| issn | 1751-8687 1751-8695 |
| language | English |
| last_indexed | 2024-12-13T07:06:23Z |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj.art-1048a016f6f940eb8505aefa2c5e273e2022-12-21T23:55:47ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952022-03-0116596298310.1049/gtd2.12342Transmission adaptability planning considering cluster correlation of wind farmsShuxin Tian0Jinhua Shen1Libo Zhang2Xijun Yang3Yang Fu4Yang Mi5Electric Engineering College Shanghai University of Electric Power Shanghai 200090 ChinaElectric Engineering College Shanghai University of Electric Power Shanghai 200090 ChinaChina Electric Power Research Institute Beijing 100192 ChinaKey Laboratory of Control of Power Transmission and Conversion (SJTU) Ministry of Education Shanghai 200240 ChinaElectric Engineering College Shanghai University of Electric Power Shanghai 200090 ChinaElectric Engineering College Shanghai University of Electric Power Shanghai 200090 ChinaAbstract Wind farm cluster penetration and its long‐distance delivery have become the important form of wind power accommodation of power network in China. For the adaptability of power network planning to the output volatility of clustering wind farms, three steps are studied as follows. Initially, the output uncertainty model of clustering wind farms based on Auto Regression Integrated Moving Average (ARIMA)‐Generalized Autoregression Conditional Heteroscedasticity (GARCH)‐Pair Copula is put forward to analyze the intermittency, fluctuation and clustering wind power correlation. Secondly, Full Cost (FC) theory is introduced to account social expense brought by grid‐connected clustering wind farms from four aspects of static cost, dynamic cost, environmental cost and inter‐generational cost. Meanwhile, available wind power transmission capacity is defined to reflect wind power accommodation based on transmission margin. Finally, the adaptive efficiency index is proposed by the ratio of available wind power transmission capacity to FC. The transmission adaptability planning model considering cluster correlation of wind farms is built with the objective function of the adaptive efficiency index. Taking the actual regional power grid as an example, the results show that the planning scheme considering the optimal adaptive efficiency index of clustering wind farms can be better adapted to the future power network environment.https://doi.org/10.1049/gtd2.12342 |
| spellingShingle | Shuxin Tian Jinhua Shen Libo Zhang Xijun Yang Yang Fu Yang Mi Transmission adaptability planning considering cluster correlation of wind farms IET Generation, Transmission & Distribution |
| title | Transmission adaptability planning considering cluster correlation of wind farms |
| title_full | Transmission adaptability planning considering cluster correlation of wind farms |
| title_fullStr | Transmission adaptability planning considering cluster correlation of wind farms |
| title_full_unstemmed | Transmission adaptability planning considering cluster correlation of wind farms |
| title_short | Transmission adaptability planning considering cluster correlation of wind farms |
| title_sort | transmission adaptability planning considering cluster correlation of wind farms |
| url | https://doi.org/10.1049/gtd2.12342 |
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