高压架空输电线路动态增容风险评估研究

发布时间：2018-07-17 08:48

【摘要】：高压架空输电线路动态增容技术是在不新建输电线路的情况下,提高现有输电线路送容量的有效途径。遗憾的是,动态增容技术虽然能够提高线路送容量,但是却在一定程度上存在风险,这主要由于对气象参数的测量误差和模型本身的计算误差导致的。值得注意的是,工程上使用较多的动态增容模型都强烈依赖于气象参数,这就增加了动态增容的风险。基于上述情况,本文对高压架空线路动态增容的风险评估进行研究,提出一种基于暂态等效风速系数的高压架空线路动态增容风险评估模型,以降低动态增容系统对气象参数的依赖,较为准确的评估增容风险,为动态增容的安全实施提供依据。首先,本文研究了国内外学者提出的架空输电线路动态增容模型,主要针对IEEE模型、热路模型以及等效风速系数模型开展深入研究。其中,IEEE标准模型在气象条件变化较快的时候,对载流量计算的精度不高;同时,IEEE模型在计算载流量时忽略了自然对流散热的影响。热路模型忽略了导线温度分布不均匀的情况,用导线上一点的温度代替整个导线的温度,存在计算误差。等效风速系数模型虽然降低了对气象参数的依赖,但是在导线温度和风速系数处于波动状态时计算误差较大。其次,由于风险评估模型所得结果应具有一定的预见性,故在实际工程中,所提动态增容风险评估模型应配合电流短期预测算法来使用。为了提高短期电流预测精度,本文提出一种基于小波包变换和峰式马尔科夫链的预测模型来估计未来线路短期电流,并且通过江苏某市2013年6月的电流、气象、温度数据,进行实验验证。同时,将所提预测模型与基于模糊聚类的相似日模型、基于模糊聚类相似日的BP神经网络模型进行对比。实验结果显示,基于小波包变换和峰式马尔科夫链的预测模型通过对历史数据进行分解和重构,能够充分提取有效信息,进行预测,具有较高的精度。本文选取该预测模型进行线路短期电流预测,为后续动态增容风险评估模型提供电流误差。最后,本文提出一种基于暂态等效风速系数的高压架空输电线路动态增容模型,该模型能够降低对气象参数的依赖,简化动态增容系统,提高线路载流量计算精度,更为准确、可靠的对线路动态增容风险进行评估。另外,通过在实验中加入预测电流误差,可以证明所提动态增容风险评估模型在实际应用中,会受到线路电流预测方法精度的影响。当电流预测结果精度不高时,通过降低线路最高允许运行温度可避免增容风险漏判情况发生。随着未来线路电流预测方法精度的改善,本文所提动态增容风险评估模型精度也将随之改善,线路运行的经济性能够充分得以发挥。
[Abstract]:High voltage overhead transmission line dynamic capacity enhancement technology is an effective way to improve the transmission capacity of existing transmission lines without building new transmission lines. Unfortunately, although dynamic capacity-increasing technology can improve the transmission capacity of the line, there is a certain degree of risk, which is mainly caused by the measurement error of meteorological parameters and the calculation error of the model itself. It is worth noting that more dynamic compatibilization models are strongly dependent on meteorological parameters which increases the risk of dynamic compatibilization. Based on the above situation, this paper studies the risk assessment of dynamic capacity increase of high voltage overhead lines, and puts forward a risk assessment model for dynamic capacity increase of high voltage overhead lines based on transient equivalent wind speed coefficient. In order to reduce the dependence of dynamic compatibilization system on meteorological parameters and evaluate the risk of increasing capacity more accurately, it can provide the basis for the safe implementation of dynamic capacity increase. Firstly, the dynamic capacitive model of overhead transmission lines proposed by domestic and foreign scholars is studied in this paper. The IEEE model, the thermal path model and the equivalent wind speed coefficient model are studied deeply. When the meteorological conditions change rapidly, the IEEE standard model is not accurate enough to calculate the carrier flow, and the IEEE model neglects the influence of natural convection heat dissipation in the calculation of the carrier flow. The thermal path model neglects the uneven temperature distribution of the conductor and replaces the temperature of the whole wire with the temperature of a point on the wire. There is a calculation error. The equivalent wind speed coefficient model reduces the dependence on meteorological parameters, but the calculation error is large when the conductor temperature and wind speed coefficient are fluctuating. Secondly, because the results of the risk assessment model should be predictable, the proposed dynamic capacitive risk assessment model should be used in combination with the short-term current prediction algorithm in practical engineering. In order to improve the accuracy of short-term current prediction, this paper presents a prediction model based on wavelet packet transform and peak-type Markov chain to estimate the short-term current of future lines, and through the current, weather and temperature data of a certain city in Jiangsu province in June 2013. Experimental verification was carried out. At the same time, the proposed prediction model is compared with the similar day model based on fuzzy clustering and the BP neural network model based on fuzzy clustering similarity day. The experimental results show that the prediction model based on wavelet packet transform and peak-type Markov chain can fully extract effective information and predict it with high accuracy by decomposing and reconstructing historical data. In this paper, the model is selected to predict the short term current of the line, which provides the current error for the risk assessment model of dynamic capacity increase. Finally, this paper presents a dynamic capacitive model for HV overhead transmission lines based on the transient equivalent wind speed coefficient. The model can reduce the dependence on meteorological parameters, simplify the dynamic capacitive system, and improve the accuracy and accuracy of the line load calculation. Reliable risk assessment of line dynamic capacity increase. In addition, by adding predictive current error into the experiment, it can be proved that the proposed dynamic capacitive risk assessment model will be affected by the accuracy of the line current prediction method in practical application. When the precision of current prediction is not high, the risk of capacitive leakage can be avoided by reducing the maximum allowable operating temperature of the line. With the improvement of the accuracy of the future line current prediction method, the accuracy of the dynamic capacity increase risk assessment model proposed in this paper will also be improved, and the economic efficiency of the line operation can be brought into full play.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM75

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