Abstract
Traditionally, transmission lines have been operated based on static thermal rating, which is determined by fixed and conservative meteorological data. It causes underutilization of potential transmission capacity. To overcome this limitation, this paper presents seasonal time scale, which can provide flexible ratings. Seasonal meteorological parameters are uncertain. The uncertainty can directly impact the conductor temperature, and eventually impact transmission capacity of the lines. In order to account for the uncertainty, this paper presents an uncertainty analysis model. This model consists of three parts: establishment of probability distribution models, Monte Carlo simulation, and operation risk assessment. In the case study, the actual meteorological data for 7 years in the Weihai is utilized, and is divided into four subsets by spring, summer, autumn and winter. The uncertainty analysis model is tested on an actual 47 km Wei-Kun line and a 4-bus power system. Results show that potential transmission capacity can be extracted if seasonal meteorological parameters are taken into account.
Funding statement: This paper is supported by the National Natural Science Foundation of China (No. 51607107, 51641702), and the Science & Technology Development Project of Shandong Province (No. ZR2015ZX045).
References
[1] Douglass DA. Weather-dependent versus static thermal line ratings. IEEE Trans Power Deliv. 1998;3:742–53.10.1109/61.4313Suche in Google Scholar
[2] Hu XL, Cotton I. “Impact of climate change on static ratings of overhead line in edinburgh.” InProceedings of the International Universities' Power Engineering Conference (UPEC). 2013: 1–6.Suche in Google Scholar
[3] Heckenbergerova J, Musilek P, Filimonenkov K. “Assessment of seasonal static thermal ratings of overhead transmission conductors.” InProceedings of the IEEE Power and Energy Society General Meeting. 2011: 1–8.10.1109/PES.2011.6039393Suche in Google Scholar
[4] Wang YL, Mo Y, Wang MQ, Zhou XF, Liang LK, Zhang P. Impact of conductor temperature time-space variation on the power system operational state. Energies. 2018;11:1–15.10.3390/en11040760Suche in Google Scholar
[5] Karimi S, Knight AM, Musilek P, Heckenbergerova J. “A probabilistic estimation for dynamic thermal rating of transmission lines.” InProceedings of the IEEE International Coference on Environment and Electrical Engineering. 2016: 1–6.10.1109/EEEIC.2016.7555851Suche in Google Scholar
[6] Rahman M, Kiesau M, Cecchi V, Watkins B. “Investigating effects of weather parameter uncertainty on transmission line power handling capabilities using affine arithmetic.” InProceedings of the IEEE Power & Energy Society General Meeting. 2017: 1–5.10.1109/PESGM.2017.8274733Suche in Google Scholar
[7] Kim DM, Cho JM, Lee HS, Jung HS, Kim JO. “Prediction of dynamic line rating based on assessment risk by time series weather model.” InProceedings of the International Coference on Probabilistic Methods Applied to Power Systems. 2006: 1–7.10.1109/PMAPS.2006.360329Suche in Google Scholar
[8] Tang L, Shu HC, Yu JL. “Operation risk on-line pre-evaluation for wind power integrated system.” InProceedings of the IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). 2010: 481–5.Suche in Google Scholar
[9] Ntuli M, Mbuli N, Motsoeneng L, Xezile R, Pretorius J. “Increasing the capacity of transmission lines via current uprating: An updated review of benefits, considerations and developments.” InProceedings of the Australasian Universities Power Engineering Conference (AUPEC). 2016: 1–6.10.1109/AUPEC.2016.7749338Suche in Google Scholar
[10] Elyas SH, Wang ZF. “Statistical analysis of transmission line capacities in electric power grids.” InProceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). 2016: 1–5.10.1109/ISGT.2016.7781263Suche in Google Scholar
[11] Yang YF, Lei XJ, Zhai QZ, Wu J, Guan XH. “Transmission capacity margin assessment in power systems with uncertain wind integration.” InProceedings of the IEEE Conference on Automation Science and Engineering (CASE). 2017: 1386–91.10.1109/COASE.2017.8256296Suche in Google Scholar
[12] Liang LK, Han XS, Wang YL, Kong LY. Online valuation of transmission line loadability. Trans China Electrotechnical Soc. 2013;28:279–84.Suche in Google Scholar
[13] Miura M, Satoh T, Iwamoto S, Kurihara I. “Application of dynamic rating to evaluation of ATC with thermal constraints considering weather conditions.” InProceedings of the IEEE Power Engineering Society General Meeting. 2006: 1–6.10.1109/PES.2006.1709107Suche in Google Scholar
[14] Gutman R, Marchenko PP, Dunlop RD. Analytical development of loadability characteristics for EHV and UHV transmission lines. IEEE Trans Power Apparatus Syst. 1979;PAS-98:606–17.10.1109/TPAS.1979.319410Suche in Google Scholar
[15] Lisityn K. Conductor temperature uncertainty. Geodigital Company. 2012;2:1–19Suche in Google Scholar
[16] Zhang J, Pu J, McCalley JD, Stern H, Gallus WA. A bayesian approach for short-term transmission line thermal overload risk assessment. IEEE Trans Power Deliv. 2002;17:770–8.10.1109/TPWRD.2002.1022802Suche in Google Scholar
[17] Kumaraswamy BG, Keshavan BK, Ravikiran YT. Analysis of seasonal wind speed and wind power density distribution in Aimangala wind form at Chitradurga Karnataka using two parameter Weibull distribution function. IEEE Power an Energy Society General Meeting.1–4. 2011.10.1109/PES.2011.6039587Suche in Google Scholar
[18] Han J, Chen HY, Cao Y. “Uncertainty evaluation using Monte Carlo method with MATLAB.” InProceedings of the Tenth International Conference on Electronic Measurement & Instruments. 2011: 282–6.10.1109/ICEMI.2011.6037817Suche in Google Scholar
[19] IEEE Std 738. InIEEE standard for calculating the current-temperature relationship of bare overhead conductors.Suche in Google Scholar
© 2018 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Research Article
- Modelling a Disconnect Switch
- New Numerical Integration Methods for Simulation of Electromagnetic Transients
- Protection Systems and Earthing Schemes for Microgrids: Main Aspects and Fault Analysis
- Maxmize the House Roof PV Solar Output by Using Maximum Power Point Box (MPPB)
- Implementation of Single-Phase Two-Switch Midpoint Unidirectional Multilevel Converter System
- LIM Control Strategy Supported by Genetic Algorithm with Unbalanced AC Source
- Economical Feasibility of Photovoltaic Array Power Increase by Alternative Structures Inclusion
- Multi-Stage Optimal Placement of Branch PMU in Active Distribution Network
- Study on the Impacts of Uncertain Meteorological Parameters on Line Transmission Capacity
- A Buck-Boost DC/DC Converter with High Efficiency Suitable for Renewable Energies
- Smart Battery Charging Station for ElectricVehicle Using Half Bridge Power Converter
- Study on a Motor Bearing Fault Diagnosis Method Using Improved EWT Based on Scale Space Threshold Method
Artikel in diesem Heft
- Research Article
- Modelling a Disconnect Switch
- New Numerical Integration Methods for Simulation of Electromagnetic Transients
- Protection Systems and Earthing Schemes for Microgrids: Main Aspects and Fault Analysis
- Maxmize the House Roof PV Solar Output by Using Maximum Power Point Box (MPPB)
- Implementation of Single-Phase Two-Switch Midpoint Unidirectional Multilevel Converter System
- LIM Control Strategy Supported by Genetic Algorithm with Unbalanced AC Source
- Economical Feasibility of Photovoltaic Array Power Increase by Alternative Structures Inclusion
- Multi-Stage Optimal Placement of Branch PMU in Active Distribution Network
- Study on the Impacts of Uncertain Meteorological Parameters on Line Transmission Capacity
- A Buck-Boost DC/DC Converter with High Efficiency Suitable for Renewable Energies
- Smart Battery Charging Station for ElectricVehicle Using Half Bridge Power Converter
- Study on a Motor Bearing Fault Diagnosis Method Using Improved EWT Based on Scale Space Threshold Method