Vol. 74

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues
2018-10-04

The Influence of Spatial and Temporal Distribution of Meteorology on Power System Operation

By Fan Song, Yanling Wang, Guangling Gao, Xianghua Pan, Mingjun Zhang, Likai Liang, and Zhijun Yin
Progress In Electromagnetics Research M, Vol. 74, 41-50, 2018
doi:10.2528/PIERM18072202

Abstract

Due to the spatial and temporal distribution of meteorological conditions along the transmission lines, the equivalent model with lumped parameters cannot accurately represent the line model with the actual parameters. In the paper, the nonuniform parameter model based on the dynamic thermal rating (DTR) technology of transmission lines is adopted to establish the power flow analysis model based on the conductor temperature. The algorithm presented in the paper is adopted to analyze the power flow of power networks with known load and meteorological parameters. And then cases with parameters of di erent seasons and spatial distribution in practical conditions are used to verify the feasibility of the algorithm. It is shown that the power flow analysis model established in this paper can realize the accurate analysis of the thermal load capacity of the transmission line in the power grid, which has great practical significance.

Citation


Fan Song, Yanling Wang, Guangling Gao, Xianghua Pan, Mingjun Zhang, Likai Liang, and Zhijun Yin, "The Influence of Spatial and Temporal Distribution of Meteorology on Power System Operation," Progress In Electromagnetics Research M, Vol. 74, 41-50, 2018.
doi:10.2528/PIERM18072202
http://www.jpier.org/PIERM/pier.php?paper=18072202

References


    1. Jiang, X. L., "Analysis of the situation of power development and reform in China (2018)," China Electrical Equipment Industry, No. 5, 15-29, 2018.

    2. Yuan, J. H., Q. Lei, and M. P. Xiong, "The prospective of coal power in China: Will it reach a plateau in the coming decade?," Energy Policy, Vol. 98, 495-504, 2016.
    doi:10.1016/j.enpol.2016.09.025

    3. Gao, H., J. C. Liu, and J. Y. Liu, "Analysis and research of transmission corridor planning under the global energy network," Sichuan Electric Power Technology, Vol. 40, No. 3, 15-20, 2017.

    4. Wang, M. X., X. S. Han, and H. B. Sun, "Analysis of enhancing power grid's capacity to absorb intermittent power generation based on electric heating coordination theory," Sichuan Electric Power Technology, Vol. 33, No. 9, 7-12, 2013.

    5. Zhan, J., C. Y. Chung, and E. Demeter, "Time series modeling for dynamic thermal rating of overhead lines," IEEE Transactions on Power Systems, Vol. 32, No. 3, 2172-2182, 2017.
    doi:10.1109/TPWRS.2016.2596285

    6. Ying, Z. F., Y. S. Chen, and K. Feng, "New DTR estimation method without measured solar and wind data," Journal of Electrical Engineering and Technology, Vol. 12, No. 2, 576-585, 2017.
    doi:10.5370/JEET.2017.12.2.576

    7. Ringelband, T., P. Schafer, and A. Moser, "Probabilistic ampacity forecasting for overhead lines using weather forecast ensembles," Electrical Engineering, Vol. 95, No. 2, 99-107, 2013.
    doi:10.1007/s00202-012-0244-8

    8. Babs, A., "Weather-based and conductor state measurement methods applied for dynamic line rating forecasting," Proceedings of the International Conference on Advanced Power System Automation and Protection, 2011.

    9. Zhou, H. S., Z. Chen, and J. Zhang, "Application of meteorological numerical forecast technology for improving transmission line capability," Power System Technology, Vol. 40, No. 7, 2175-2180, 2016.

    10. Troccoli, A., L. Dubus, and S. E. Haupt, Weather Matters for Energy, Springer, New York, 2014.
    doi:10.1007/978-1-4614-9221-4

    11. Michiorri, A., H. M. Nguyen, and S. Alessandrini, "Forecasting for dynamic line rating," Renewable and Sustainable Energy Reviews, Vol. 52, 1713-1730, 2015.
    doi:10.1016/j.rser.2015.07.134

    12. Banakar, H., N. Alguacil, and F. D. Galiana, "Electrothermal coordination Part I: Theory and implementation schemes," IEEE Transactions on Power Systems, Vol. 20, No. 2, 798-805, 2005.
    doi:10.1109/TPWRS.2005.846196

    13. Alguacil, N., M. H. Banakar, and F. D. Galiana, "Electrothermal coordination Part II: Case studies," IEEE Transactions on Power Systems, Vol. 20, No. 4, 1738-1745, 2005.
    doi:10.1109/TPWRS.2005.857836

    14. Cecchi, V., M. Knudson, and K. Miu, "System impacts of temperature-dependent transmission line models," IEEE Transactions on Power Delivery, Vol. 28, No. 4, 2300-2308, 2013.
    doi:10.1109/TPWRD.2013.2276757

    15. Cecchi, V., A. S. Leger, and K. Miu, "Incorporating temperature variations into transmission-line models," IEEE Transactions on Power Delivery, Vol. 26, No. 4, 2189-2196, 2011.
    doi:10.1109/TPWRD.2011.2159520

    16. Aaron, S. L. and N. Chika, "OTA-based transmission line model with variable parameters for analog power ow computation," International Journal of Circuit Theory and Applications, Vol. 38, 199-220, 2008.

    17. Teh, J. and I. Cotton, "Critical span identi cation model for dynamic thermal rating system placement," IET Generation, Transmission and Distribution, Vol. 9, No. 16, 2644-2652, 2015.
    doi:10.1049/iet-gtd.2015.0601