含风电场的输电网运营效率评估
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TM721

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国家自然科学基金资助项目(51767017)


Efficiency evaluation of transmission grids with wind farms
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National Natural Science Foundation of China (Grant No.51767017).

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    摘要:

    针对传统含风电场的输电网运营效率评估体系中存在的指标冗余和评估结果准确性较差的问题,首先引用相关性分析法去除相关性较强的指标,随后运用组合权重法合理赋权突出主导因素,从而筛选精简出含有11个代表性极强的指标的合理的评估指标体系,由此构建出模糊神经网络综合评价体系。然而模糊神经网络在训练参数时收敛速度较慢且容易陷入局部最优解,因此文中在对比分析了梯度下降法、粒子群算法及小生境粒子群(NPSO)算法的收敛速度和精度后,选择具有最优收敛性能的NPSO算法求解最优参数并更新到神经网络中。测试数据表明,实际输出和预测输出的契合度很高,最终针对甘肃省L市、T市和B市2011—2016年的输电网运营效率进行评估与分析。

    Abstract:

    In view of the problem of the redundancy of indicators and the poor accuracy of the evaluation results in the traditional transmission efficiency evaluation system of wind farms, the correlation analysis method is first cited to remove the more relevant indicators, and then the combined weight method is applied. Reasonable empowerment highlights the dominant factors, so as to screen and streamline a reasonable evaluation index system with 10 representative indicators, and construct a fuzzy neural network comprehensive evaluation system. The fuzzy neural network uses the GD method to train parameters with slow convergence rate and easy to fall into the local optimal solution. Therefore, the convergence speed and accuracy of GD, PSO and NPSO algorithms are compared and analyzed, so that the NPSO algorithm with optimal convergence performance is selected to solve the most. The parameters are updated and updated into the neural network. The test data shows that the actual output and the predicted output have a high degree of fit. Finally, the efficiency of transmission grid operation in city L, city T and city B of Gansu Province from 2011 to 2016 is evaluated and analyzed.

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党存禄,李永强,杨海兰,党媛.含风电场的输电网运营效率评估[J].电力工程技术,2020,39(4):77-86

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  • 收稿日期:2020-02-19
  • 最后修改日期:2020-03-27
  • 录用日期:2020-02-15
  • 在线发布日期: 2020-08-03
  • 出版日期: 2020-07-28
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