## Fan Song* , Yanling Wang* , Lei Zhao** , Kun Qin** , Likai Liang* , Zhijun Yin*** and Weihua Tao****## |

Parameter | Value |
---|---|

Ambient temperature (℃) | 40 |

Wind speed (m/s) | 0.5 |

Wind direction (°) | 90 |

Radiation coefficient | 0.9 |

Absorption coefficient | 0.9 |

Sunshine intensity (W/m2) | 1,000 |

Maximum operating temperature (℃) | 70 |

It is worth mentioning that the conductor temperature in thermal balance state is calculated under known line current and ambient weather conditions, and it cannot be expressed as an explicit function by IEEE thermal equivalent equation. It can only be expressed as an implicit function, and solved by iterative method.

Now choose the steel core aluminum wire LGJ-400/50. The conductor diameter is 27.63 mm. The resistance temperature coefficient is 0.0039/ºC (20ºC). Select the geographical location of Weihai. Average altitude is 250 m. Latitude is 37.15°. The STR is 592 A. Then, according to the variation of meteorological conditions, the carrying capacity is analyzed.

Wind speed is the main factor influencing the convection cooling. Under the condition that the other parameters keep the boundary environmental condition, the range of the wind speed change is supposed to be 0–20 m/s, and the influence of the wind speed on the carrying capacity is shown in Fig. 1.

As seen in Fig. 1, in the wind speed of 0–5 m/s section, as the wind speed increases, the ampacity increases significantly from 368 A up to 1,252 A. Relative to the wind speed of 0 m/s, the carrying capacity increased by 240%. While in the wind of 5–20 m/s section, carrying capacity increases from 1,252 A to 1,926 A. Compared with the wind speed of 5 m/s, the ampacity increased by 53.8%. The influence is declining when compared with the wind speed of 0–5 m/s. In summary, the wind speed has a great influence on the current carrying capacity.

Wind direction is the influence factor on the convective cooling of the overhead transmission line. Under the condition that the other parameters keep the boundary environmental condition, the wind incidence angle along the line direction is 0°–90°, and the influence of the wind direction on the current carrying capacity is shown in Fig. 2.

By analysis of Fig. 2, it can be drawn that the transmission line capacity is fixed to a constant 368.4 A in the wind direction angle of 0°–7.8° section. The reason is that when the wind speed is 0.5 m/s, the wind incidence angle is too small, so that the effective value of wind speed is approximately 0. So only the natural convection is considered. In the wind angle of 7.8°–45°, with the increase of the angle, the carrying capacity increases obviously, from 368.4 A to 547.6 A. Compared with the wind angle of 7.8°, the carrying capacity increased by 48.64%. In the wind angle of 45°–90° section, with the angle increases, the load increases from 547.6 A up to 604.2 A. The carrying capacity increased by 10.34% with respect to the wind angle of 45°. In summary, the wind incidence angle has a great influence on the current carrying capacity.

Sunshine intensity is the influence factor on solar absorption of overhead transmission line. Under the

condition that the other parameters keep the boundary environmental condition, select the sunshine intensity change range of 0–1,000 W/m2 and the influence of sunshine intensity on current carrying capacity is shown in Fig. 3.

Fig. 3 shows that the effect of sunshine intensity on current carrying capacity is approximately linear. With the increase of the sunshine intensity, the solar absorption of the transmission line increases and the carrying capacity decreases from 825.4 A to 611.4 A. Relative to the sunshine intensity of 0 W/m^{2}, the carrying capacity decreased by 25.9%. In summary, the change of sunshine intensity has relatively small effect on current carrying capacity.

The ambient temperature is the influence factor on the radiation dissipation. Under the condition that the other parameters keep the boundary environmental condition, the variation range of the ambient temperature is 0ºC–40ºC, and the effect of the ambient temperature is analyzed in Fig. 4.

Fig. 4 shows that the influence of ambient temperature on the line ampacity is approximately linearly reduced. As the ambient temperature rises from 0°C to 40°C, the difference between the conductor temperature and the ambient temperature decreases. The radiation cooling is reduced, so that the current carrying value is reduced from 1,021 A to 604.2 A. The carrying capacity is reduced by 40.8% relative to the temperature of 0°C. In summary, the ambient temperature also has a great influence on current carrying capacity.

The effects of wind speed, wind direction, sunshine intensity and ambient temperature on ampacity of transmission line are compared and quantified. Table 2 shows the difference in the carrying capacity of different environmental parameters in descending order.

Table 2.

Meteorological parameters | Parameter range of change | Current carrying difference (A) |
---|---|---|

Wind speed (m/s) | 0–20 | 1,557.5 |

Ambient temperature (℃) | 0–40 | 406.5 |

Wind direction (°) | 0–90 | 235.8 |

Sunshine intensity (W/m2) | 0–1,000 | 213.9 |

When one meteorological parameter is studied, other parameters are maintained as the values under the boundary conditions in Table 1. The influence of wind speed on the current carrying capacity is the greatest, followed by ambient temperature, wind direction and sunshine intensity, respectively. The randomness of the wind speed is relatively large, and the distribution of the ambient temperature is relatively regular. All in all, wind speed and ambient temperature are the key parameters that affect the line ampacity.

Through above analysis, it can be concluded that wind speed and ambient temperature are the key meteorological parameters. The real-time key meteorological parameters are from Shandong University (Weihai) observatory, from January 1, 2009 to December 31, 2015, with the interval of 10 minutes and 363,737 sets of continuous data. Moreover, the wind incidence angle is fixed at 45° and the sunshine intensity is calculated by the IEEE standard formula. The type of transmission line is ACSR-400/50 in Weihai city. Regardless of the transient temperature change process of lines, the ampacity and the conductor temperature are analyzed in the steady state.

According to the calculation and analysis of the above method, corresponding to 10 minutes interval for the 7 years meteorological data, using the IEEE standard thermal equivalent equation, current carrying value of 363,737 groups can calculate. The scatter diagram is shown in Fig. 5.

Fig. 5 shows that the distribution of dynamic current carrying value of overhead transmission lines has obvious seasonal characteristics. Especially the current carrying value is high in winter and is low in summer, which is consistent with the ambient temperature distribution of meteorological elements, low temperature in winter, and high temperature in summer. As can be seen from Fig. 5, the ampacity of 363,737 groups is negatively correlated with the temperature, and the lower the temperature, the higher the current carrying value. The maximum value of transmission line current carrying capacity appears in winter, and the maximum value is 2,758 A. The minimum value appears in summer, and the minimum value is 534 A. The average current carrying capacity is 1,721 A and the standard deviation is 307.56. The data points in the scatter plot have very few points below the static load rating of 592 A. The data of the 363,737 groups’ DTR is only a few arrays below the STR, which verifies that DTR can effectively improve the utilization of transmission capacity. Fig. 6 is the frequency distribution of 363,737 groups’ DTR. The distribution range and operational risk of DTR values are analyzed deeply.

As shown in Fig. 6, 99% (984 A) represents the frequency sum of data greater than 984 A is 99%, and 95% (1,254 A) represents the frequency sum of data greater than 1,254 A is 95%. In addition, the confidence interval for the transmission line current carrying capacity at 99% is [985, 2426], and the minimum value under the confidence interval is 985 A with the maximum being 2,426 A. The confidence interval for line carrying capacity at 95% is [1254, 2249]. The minimum value under the confidence interval is 1,254 A and the maximum is 2,249 A. Therefore, when the current value is 984 A and 1,254 A, the operation risk is 1% and 5%, respectively. Compared with STR, the dynamic carrying capacity increased by 66.2% and 111.8%, respectively. The results show that STR is a relatively conservative method, while DTR can effectively improve the utilization of transmission capacity.

It can be seen from the above analysis that the dynamic carrying value has obvious seasonal distribution characteristics. The typical weather conditions of the summer solstice and the winter solstice will be selected. Then, the ampacity and conductor temperature will be analyzed. Static weather conditions of the boundary environment meteorological conditions occur in the summer. Fig. 7 shows the dynamic ampacity for three consecutive days by using the actual meteorological data in Weihai on June 21, 2014 and the days before and after the summer solstice.

In theory, the winter weather conditions are more suitable for improving the ampacity than other seasons. Fig. 8 shows the dynamic ampacity for three consecutive days by using the actual meteorological data in Weihai on December 22, 2014 and the days before and after the winter solstice

As can be seen from Figs. 7 and 8, the dynamic ampacity is greater than the STR of 592 A. In summer solstice, the maximum carrying capacity is 1,965 A of the 72 sets data, and the minimum value is 994 A. The average value is 1,472 A and the standard deviation is 138.85. In winter solstice, the maximum carrying capacity of 72 sets data is 2,577 A, and the minimum value is 1,628 A. The average value is 2,029 A and the standard deviation is 202.84. The whole winter dynamic current carrying value is significantly higher than that in summer. Parts of Weihai have wind farms and the application of DTR technology can provide transmission lines with higher ampacity, increase the utilization of wind power in the electricity market as well as improve the utilization of clean energy.

The conductor temperature under steady-state conditions is analyzed using the actual weather data of Weihai on June 21, 2014, along with the summer solstice before and after 2 days, a total of 3 consecutive days. In addition, the relationship among the conductor temperature, ambient temperature and wind speed is analyzed. The results are shown in Fig. 9. Similarly, the conductor temperature and their relationship are analyzed using the actual weather data on December 22, 2014, along with the winter solstice before and after 2 days, a total of 3 consecutive days. The results are shown in Fig. 10.

It can be drawn from Figs. 9 and 10 that when the ampacity is 592 A, the conductor temperature is much smaller than the maximum allowed temperature of 70ºC. The conductor temperature is about 15ºC in winter, while it is about 40ºC in summer. Overall, the winter and summer transmission line conductor operating temperature trend is basically consistent with the ambient temperature trend. The environment temperature is relatively high in summer, and the summer wind speed is relatively lower than winter. Come to the conclusion that if the wind speed is small the conductor temperature is relatively high. The winter environment temperature is lower, but the wind speed is mostly more than 5m/s. Therefore, the conductor operating temperature relative to the summer, there are not many isolated conductor high temperature points. The above results well validate that transmission line conductor operating temperature and ambient temperature is a positive correlation, but with the size of the wind speed is negatively correlated, which is consistent with the principle of heat absorption and heat dissipation of the transmission line. In summary, the conductor operating temperature for overhead transmission lines has a great safety margin and the use of dynamic current carrying value will be able to effectively tap the thermal load potential of transmission lines.

This paper is supported by the National Natural Science Foundation of China (No. 51407111, 51407106, 51641702), the Science & Technology Development Project of Shandong Province (No. ZR2015ZX045), and the Science and Technology Development Project of Weihai City (No. 2014DXGJ23).

In this paper, first, we introduce the IEEE standard steady-state thermal equivalent equation of transmission lines, and analyze the main factors influencing the transmission line conductor. We study the method of calculating the current carrying value by using the IEEE thermal equivalent equation and the transmission line conductor operating temperature under the given meteorological parameters. Secondly, we analyze separately the ambient temperature, wind speed, wind incidence angle, and sunshine intensity which effect the line ampacity. The key meteorological factors are found as wind speed and ambient temperature. Then this paper analyzes the actual ampacity of 220 kV overhead transmission lines in Weihai area, and analyzes the thermal load capacity of DTR relative to STR under given confidence interval. Finally, the actual ampacity on summer solstice day and winter solstice day in 2014 as well as the transmission line conductor operating temperature are analyzed correspondingly. The results show that the carrying current capacity of overhead transmission line in Weihai area is too conservative under STR, and DTR can effectively excavated the thermal load potential of transmission lines. Dynamic current carrying capacity can better reflect the transmission capacity. The DTR is affected by many uncertain factors. In future work, it will be devoted to studying the uncertainty of conductor temperature, the uncertainty of system power flow and the operation risk of grid capacity increase. By combining the analysis method of this paper, dispatchers are provided with operational risk information of transmission line, and combined with load forecasting technology, intelligent load dispatching can be carried out better.

She received her Bachelor in School of Computer and Information Engineering from Central South University of Forestry and Technology in 2017. Now, she is a postgraduate student in School of Mechanical, Electrical and Information Engineering in Shandong University at Weihai, China. Her main research interests include power system operation and control.

He graduated from mechanical electronic engineering of Nanjing University of Science and Technology in 1999. Now he works as engineer in Beaulieu Yarns Weihai Company Limited, Weihai, China. His main field of research is new energy generation (including grid inverter) and large power electronic circuit.

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