Pinned Repositories
PyPSCAD
ANN-MPC
A Feed-Forward ANN based on MPC for a Three-Phase Inverter With an Output LC Filter
AutoInput_SEU
自动填写东南大学每日健康状况，建议设置成每日定期执行任务，免除导员，班长连环夺命call
hello-world
just
ipss-odm
InterPSS ODM development
Mooc_Downloader
学无止下载器，慕课下载器，Mooc下载，慕课网下载，中国大学下载，爱课程下载，网易云课堂下载，学堂在线下载；支持视频，课件同时下载
OpenGlass
Turn any glasses into AI-powered smart glasses
OPTIMIZATION-of-the-APFs-Placement-Based-on-Instantaneous-Reactive-Power-Theory-by-GENETIC-ALGORITHM
In electrical distribution systems, a great amount of power are wasting across the lines, also nowadays power factors, voltage profiles and total harmonic distortions (THDs) of most loads are not as would be desired. So these important parameters of a system play highly important role in wasting money and energy, and besides both consumers and sources are suffering from a high rate of distortions and even instabilities. Active power filters (APFs) are innovative ideas for solving of this adversity which have recently used instantaneous reactive power theory. In this paper, a novel method is proposed to optimize the allocation of APFs. The introduced method is based on the instantaneous reactive power theory in vectorial representation. By use of this representation, it is possible to asses different compensation strategies. Also, APFs proper placement in the system plays a crucial role in either reducing the losses costs and power quality improvement. To optimize the APFs placement, a new objective function has been defined on the basis of five terms: total losses, power factor, voltage profile, THD and cost. Genetic algorithm has been used to solve the optimization problem. The results of applying this method to a distribution network illustrate the method advantages.
PIoT-Oriented-Multi-Target-Recognition-of-Substation-Infrared-Images-Driven-by-Deep-Learning
This repository hosts the code and resources for a deep learning-driven multi-target recognition system for substation infrared images, aimed at enhancing Power Internet of Things (PIoT) fault diagnosis and equipment monitoring.
PLIID-Dataset
Dataset created for the Power Line Insulators Inspection Detections
shichen164429350's Repositories
shichen164429350/PIoT-Oriented-Multi-Target-Recognition-of-Substation-Infrared-Images-Driven-by-Deep-Learning
This repository hosts the code and resources for a deep learning-driven multi-target recognition system for substation infrared images, aimed at enhancing Power Internet of Things (PIoT) fault diagnosis and equipment monitoring.
shichen164429350/OpenGlass
Turn any glasses into AI-powered smart glasses
shichen164429350/PyPSCAD
shichen164429350/v2ray-core
A platform for building proxies to bypass network restrictions.
shichen164429350/Mooc_Downloader
学无止下载器，慕课下载器，Mooc下载，慕课网下载，**大学下载，爱课程下载，网易云课堂下载，学堂在线下载；支持视频，课件同时下载
shichen164429350/PLIID-Dataset
Dataset created for the Power Line Insulators Inspection Detections
shichen164429350/v2rayN
shichen164429350/simupy
A framework for modeling and simulating dynamical systems
shichen164429350/public-insulator-datasets
Unifying Public Datasets for Insulator Detectionand Fault Classification in Electrical Power Lines
shichen164429350/TAPAS
Community drives inverter project
shichen164429350/AutoInput_SEU
自动填写东南大学每日健康状况，建议设置成每日定期执行任务，免除导员，班长连环夺命call
shichen164429350/TeamViewer-5min
Mac/Windows TeamViewer 破解版，解除被检测出商业用途限制(5 min)
shichen164429350/ANN-MPC
A Feed-Forward ANN based on MPC for a Three-Phase Inverter With an Output LC Filter
shichen164429350/seuthesis
LaTeX Thesis Template for Southeast University
shichen164429350/seuthesix
seuthesix: A LaTeX document class for typesetting thesis/dissertation of Southeast University.
shichen164429350/Training-a-network-on-insulator-datasets
首先将绝缘子数据转换成TFRecords格式，然后运用预训练模型来fine tuning
shichen164429350/OPTIMIZATION-of-the-APFs-Placement-Based-on-Instantaneous-Reactive-Power-Theory-by-GENETIC-ALGORITHM
In electrical distribution systems, a great amount of power are wasting across the lines, also nowadays power factors, voltage profiles and total harmonic distortions (THDs) of most loads are not as would be desired. So these important parameters of a system play highly important role in wasting money and energy, and besides both consumers and sources are suffering from a high rate of distortions and even instabilities. Active power filters (APFs) are innovative ideas for solving of this adversity which have recently used instantaneous reactive power theory. In this paper, a novel method is proposed to optimize the allocation of APFs. The introduced method is based on the instantaneous reactive power theory in vectorial representation. By use of this representation, it is possible to asses different compensation strategies. Also, APFs proper placement in the system plays a crucial role in either reducing the losses costs and power quality improvement. To optimize the APFs placement, a new objective function has been defined on the basis of five terms: total losses, power factor, voltage profile, THD and cost. Genetic algorithm has been used to solve the optimization problem. The results of applying this method to a distribution network illustrate the method advantages.
shichen164429350/ipss-odm
InterPSS ODM development
shichen164429350/shichen164429350.github.io
shichen164429350/test
shichen164429350/hello-world
just