基于大数据的考虑谐波影响的配电网 经济损失评估方法研究

谐波对配电网的危害较大，带来了巨大的经济损失。目前，关于配电网谐波经济损失评估方面，缺乏统一、科学的评估体系。针对以上问题，以电力大数据平台为基础支撑，建立了包含数据层、指标层和应用层的配电网谐波经济损失评估体系总体架构，构建了谐波经济损失评估指标体系。对常规PSO算法进行改进，并和RBF神经网络结合，利用CAPSO-RBF神经网络进行谐波网损评估。将Simoni模型和XLPE电缆谐波线芯温升模型结合，得到了谐波影响下的XLPE电缆绝缘老化寿命评估模型。最后，案例分析证明了本文方法的可行性，验证了评估体系的合理性和电力大数据的优势，对配电网谐波经济损失评估具有一定的指导和参考意义。

Study on Economic Loss Evaluation Method of Distribution Network Considering Harmonic Influence on Large Date

Harmonics have great harm to the distribution network, which brings huge economic losses. At present, it is lack of unified, scientific evaluation system. In view of the above problems, based on the power large data technology, the overall framework of harmonic economy loss evaluation system of distribution network which contaions data layer, index layer and application layer is constructed and the harmonic economy loss evaluation index system is established. The conventional particle swarm optimization algorithm is improved, combing with the RBF neural network, using the CAPSO-RBF neural network to assessment the harmonic loss. The simoni model and the XLPE cable harmonic line core temperature rise model are combined together, obtaining the evaluation model of insulation aging life of XLPE cable. Finally, the feasibility of this method is proved by the case analysis, and the rationality of the evaluation system and the advantages of large power data is also verified, hasing certain guidance and reference significance for the harmonic economy evaluation of distribution network.