[1]徐利美,贺卫华,李 远,等.基于 ISSA-BP 的 500kV 高压线损预测模型[J].计算机技术与发展,2023,33(05):214-220.[doi:10. 3969 / j. issn. 1673-629X. 2023. 05. 032]
　XU Li-mei,HE Wei-hua,LI Yuan,et al.Prediction Model of 500kV High Voltage Line Loss Based on ISSA-BP[J].,2023,33(05):214-220.[doi:10. 3969 / j. issn. 1673-629X. 2023. 05. 032]

点击复制

基于 ISSA-BP 的 500kV 高压线损预测模型()

分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:

33

期数:

2023年05期

页码:

214-220

栏目:

新型计算应用系统

出版日期:

2023-05-10

文章信息/Info

Title:

Prediction Model of 500kV High Voltage Line Loss Based on ISSA-BP

文章编号:

1673-629X(2023)05-0214-07

作者:

徐利美1 ; 贺卫华¹ ; 李 远¹ ; 杨 射² ; 刘展鹏³ ; 续欣莹³

1. 国网山西省电力公司,山西 太原 030021;

2. 国网山西超高压变电公司,山西 太原 030021;

3. 太原理工大学 电气与动力工程学院,山西 太原 030024

Author(s):

XU Li-mei1 ; HE Wei-hua1 ; LI Yuan1 ; YANG She2 ; LIU Zhan-peng3 ; XU Xin-ying3

1. State Grid Shanxi Electric Power Company,Taiyuan 030021,China;

2. State Grid Shanxi Extra High Voltage Substation Company,Taiyuan 030021,China;

3. School of Electrical and Power Engineering,Taiyuan University of Technology,Taiyuan 030024,China

关键词:

500 kV 高压; 线损预测; BP 神经网络; 麻雀搜索算法; Levy 变异策略; 旋转策略; 基准函数

Keywords:

500 kV high voltage;  line loss prediction;  BP neural network;  sparrow search algorithm;  Levy mutation strategy;  rotationstrategy; benchmark function

分类号:

TP183;TM744

DOI:

10. 3969 / j. issn. 1673-629X. 2023. 05. 032

摘要:

线损对评估电力系统的经济运行有着重要作用。 针对高压线损与多种特征参数之间关系复杂的问题,综合考虑关口电压、关口电流及温湿度对高压线损的影响,提出一种基于改进麻雀搜索算法

( ISSA) 优化 BP 神经网络( ISSA-BP) 的高压线损预测模型。 首先,通过 Levy 变异策略及旋转策略分别对麻雀搜索算法( SSA) 的发现者及加入者的位置更新方式进行改进,并在 6 个基准函数上进行测试,结果表明 ISSA 的寻优能力得到提升。 其次,通过 ISSA 将最优初始权值和最优初始阈值赋予 BP 神经网络,进而拟合出特征参数与线损率的关系。 最后,以山西省某条 500 kV 高压输电线路数据为研究对象,对比分析 BP、GWO-BP、WOA-BP、SSA-BP 与 ISSA-BP 这五种预测模型的预测效果,结果表明 ISSA-BP 模型的预测值最接近实际值,其 RMSE、MAPE、MAE 和 R2 分别为 4. 29% 、3. 67% 、3. 57% 和 99. 01% ,均为各种预测模型中最优。 相较于 SSA-BP,ISSA-BP 的 RMSE 下降了 33. 4% ,MAPE 下降了 36. 7% ,MAE 下降了 37. 1% ,R2 提高了 1. 24% , 表明 ISSA-BP 模型能对高压线损进行准确预测。

Abstract:

Line loss plays an important role in evaluating the economic operation of a power system. Aiming at the complex relationshipbetween high voltage line loss and various characteristic parameters,considering the influence of gate voltage,gate current and temperatureand humidity on high voltage line loss,we propose a high voltage line loss prediction model based on improved sparrow search algorithm(ISSA) optimized BP neural network ( ISSA-BP) . Firstly,the position update methods of the discoverers and joiners of the sparrow　search algorithm

?( SSA) are improved through the Levy mutation strategy and the rotation strategy, respectively, and tested on sixbenchmark functions. The results show that the optimization ability of ISSA has been improved. Secondly,the optimal initial weights andoptimal initial thresholds are given to the BP neural network through ISSA,and then the relationship between the characteristic parameters and the line loss rate is fitted. Finally,taking the data of a 500kV high voltage transmission line in Shanxi Province as the researchobject,the prediction effects of five prediction models of BP,GWO-BP,WOA-BP,SSA-BP and ISSA-BP are compared and analyzed.The predicted value is the closest to the actual value,and its RMSE,MAPE,MAE and R2 are 4. 29% ,

3. 67% ,3. 57% and 99. 01% ,respectively,which are the best among various prediction models. Compared with SSA-BP,the RMSE of ISSA-BP decreased by 33. 4% ,MAPE decreased by?

36. 7% ,MAE decreased by 37. 1% ,and R2 increased by 1. 24% . It is showed that ISSA-BP model can accuratelypredict high voltage line loss.

常用功能