These are the PMU datasets I generated as 9 topologies.
For 33-PMU on each node expect node 800:
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/PMU_PUresults.rar
I suggest deleting "folder 3" inside for them all, because the data in folder 3 is too close to folder 2. If you use these data training a CNN topology identification neural network, they would lower the accuracy in the result, and also same for all the dataset below.
For the interfered PMU data (with niose or missing or both):
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_10dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_20dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_20dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_10dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_MissingOneData.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_MissingOneData_add10dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_MissingOneData_add20dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_MissingTwoData.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_MissingTwoData_add10dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_22PMU_MissingTwoData_add20dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_30dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_40dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_50dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingOneData.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingOneData_BasedOn_40dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingOneData_add10dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingOneData_add20dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingOnePMU.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingThreePMU.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoData.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoData_BasedOn_40dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoData_BasedOn_random_dB.rar (random means the SNR from 20dB ~ 50dB)
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoData_add10dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoData_add20dB.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoPMU.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_random_dB.rar
For Manual Data that 100 data in each folder (/topology/label):
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_40dB_900Mannual.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingOneData_BasedOn_40dB_900Mannual.rar
https://storage.googleapis.com/yifu-ieee-34-node-test-feeder/CNN_MissingTwoData_BasedOn_40dB_900Mannual.rar
So till now, after you delete "folder 3" in all datasets, the mapping relationship between folder numbers to topologies would be:
Folder 1 → Topology 1
Folder 2 → Topology 2
Folder 4 → Topology 3
Folder 5 → Topology 4
Folder 6 → Topology 5
Folder 7 → Topology 6
Folder 8 → Topology 7
Folder 9 → Topology 8
(Also, you can rename the rest folders)
![image](https://raw.githubusercontent.com/liyifu93/IEEE_34_Node_Test_Feeder/master/All_8_Topologies.jpg)
没有合适的资源?快使用搜索试试~ 我知道了~
毕业设计&课设-基于MATLAB的IEEE配电系统仿真.zip
共39个文件
m:14个
xls:8个
slx:5个
需积分: 1 1 下载量 100 浏览量
2024-01-08
22:58:51
上传
评论
收藏 2.79MB ZIP 举报
温馨提示
matlab算法,工具源码,适合毕业设计、课程设计作业,所有源码均经过严格测试,可以直接运行,可以放心下载使用。有任何使用问题欢迎随时与博主沟通,第一时间进行解答! matlab算法,工具源码,适合毕业设计、课程设计作业,所有源码均经过严格测试,可以直接运行,可以放心下载使用。有任何使用问题欢迎随时与博主沟通,第一时间进行解答! matlab算法,工具源码,适合毕业设计、课程设计作业,所有源码均经过严格测试,可以直接运行,可以放心下载使用。有任何使用问题欢迎随时与博主沟通,第一时间进行解答! matlab算法,工具源码,适合毕业设计、课程设计作业,所有源码均经过严格测试,可以直接运行,可以放心下载使用。有任何使用问题欢迎随时与博主沟通,第一时间进行解答! matlab算法,工具源码,适合毕业设计、课程设计作业,所有源码均经过严格测试,可以直接运行,可以放心下载使用。有任何使用问题欢迎随时与博主沟通,第一时间进行解答! matlab算法,工具源码,适合毕业设计、课程设计作业,所有源码均经过严格测试,可以直接运行,可以放心下载使用。有任何使用问题欢迎随
资源推荐
资源详情
资源评论
收起资源包目录
毕业设计&课设-基于MATLAB的IEEE配电系统仿真.zip (39个子文件)
matlab_code
Yifu_SUMMARY_34.xlsx 87KB
MATLAB
power_34NodeTestFeeder_loads_init.m 4KB
power_34NodeTestFeeder_init.m 2KB
IEEE_34_node_2018a.slx 127KB
Dataset
README.md 4KB
IEEE_34_node_2019b.slx 131KB
IEEE_34_node_2020a_scenarios.slx 139KB
IEEE_34_node_2020a_scenarios_fold.slx 148KB
README.md 314B
scripts
save_results.m 3KB
Load_Data_Generator.m 9KB
convert_mat_data.m 5KB
PMU_Niose_Generator.m 45KB
save_data.m 454B
revalue_data.m 1KB
PMU_PU_Generator.m 2KB
PMU_PU.m 2KB
PMU_MissingData_Generator.m 66KB
ReadData.m 383B
PMU_ScenarioData_Generator.m 35KB
PMU_Data_Generator.m 20KB
README.md 454B
IEEE_34_node_2019b_scenarios_v4.slx 148KB
analysis.pdf 643KB
Results_34.pdf 410KB
All_8_Topologies.jpg 1.09MB
IEEE_files
config.xls 28KB
IEEE 34 Node Test Feeder.doc 186KB
distributed load data.xls 30KB
spot load data.xls 28KB
cap data.xls 27KB
line data.xls 29KB
feeder34.zip 79KB
IEEE 34 Node Test Feeder.pdf 176KB
Regulator Data.xls 29KB
Transformer Data.xls 28KB
IEEE Test Feeder.pdf 66KB
Line Configuration.xls 29KB
README.md 729B
共 39 条
- 1
资源评论
白话机器学习
- 粉丝: 9306
- 资源: 7681
上传资源 快速赚钱
- 我的内容管理 展开
- 我的资源 快来上传第一个资源
- 我的收益 登录查看自己的收益
- 我的积分 登录查看自己的积分
- 我的C币 登录后查看C币余额
- 我的收藏
- 我的下载
- 下载帮助
安全验证
文档复制为VIP权益,开通VIP直接复制
信息提交成功