yuktabutala

Kickstart-2020

Solutions of Google Kickstart 2020.

Depression-Chatbot

Feeling Depressed? Feeling Suicidal? Want to give up? Try Depression-Chatbot!

Fault-Detection-in-Power-Microgrid

This project presents the concept of fault detection and location in a Power Microgrid making use of the machine learning concepts like Artificial Neural Network. The electronic equipment used in microgrids is in essential need of more secure protection against short circuit faults. Due to the high current at the time of fault occurrence, the whole system might be de-energized which would have a severely negative impact on the entire system. A fault occurs when two or more conductors come in contact with each other or ground. Ground faults are considered as one of the main problems in power systems and account for more than 80% of all faults. An effective method to detect, isolate, and protect the power microgrid system against the effects of short circuit faults is extremely important. In this project we worked on a highly effective new method to protect the microgrid system using an Artificial Neural Network (ANN) that will detect and find the location of the fault before it affects other parts of the system. It would, therefore, be more dependable for microgrid protection. This protection network is distributed all along the power microgrid system protecting the entire microgrid network and is connected to the other protective devices in the system. This project focuses on detecting faults and identifying the location of the faults on electric power transmission lines in the power microgrid network.

hacktoberfest

Kickstart-2020

Solutions of Google Kickstart 2020.

kickstart_2020

mlda_project

PV_fault_Python

ML models trained to predict faults for Photo Voltaic systems

smile-detection

Smile detection on GENKI4K dataset.

yuktabutala/Depression-Chatbot

Feeling Depressed? Feeling Suicidal? Want to give up? Try Depression-Chatbot!

yuktabutala/Fault-Detection-in-Power-Microgrid

This project presents the concept of fault detection and location in a Power Microgrid making use of the machine learning concepts like Artificial Neural Network. The electronic equipment used in microgrids is in essential need of more secure protection against short circuit faults. Due to the high current at the time of fault occurrence, the whole system might be de-energized which would have a severely negative impact on the entire system. A fault occurs when two or more conductors come in contact with each other or ground. Ground faults are considered as one of the main problems in power systems and account for more than 80% of all faults. An effective method to detect, isolate, and protect the power microgrid system against the effects of short circuit faults is extremely important. In this project we worked on a highly effective new method to protect the microgrid system using an Artificial Neural Network (ANN) that will detect and find the location of the fault before it affects other parts of the system. It would, therefore, be more dependable for microgrid protection. This protection network is distributed all along the power microgrid system protecting the entire microgrid network and is connected to the other protective devices in the system. This project focuses on detecting faults and identifying the location of the faults on electric power transmission lines in the power microgrid network.

yuktabutala/hacktoberfest

yuktabutala/Kickstart-2020

Solutions of Google Kickstart 2020.

yuktabutala/kickstart_2020

yuktabutala/mlda_project

yuktabutala/PV_fault_Python

ML models trained to predict faults for Photo Voltaic systems

yuktabutala/smile-detection

Smile detection on GENKI4K dataset.