6 papers
A Multi-Head Convolutional Neural Network Based Non-Intrusive Load Monitoring Algorithm Under Dynamic Grid Voltage Conditions
Himanshu Grover, Lokesh Panwar, Ashu Verma +2
In recent times, non-intrusive load monitoring (NILM) has emerged as an important tool for distribution-level energy management systems owing to its potential for energy conservati…
Estimating State of Charge for xEV batteries using 1D Convolutional Neural Networks and Transfer Learning
Arnab Bhattacharjee, Ashu Verma, Sukumar Mishra +1
In this paper we propose a one-dimensional convolutional neural network (CNN)-based state of charge estimation algorithm for electric vehicles. The CNN is trained using two publicl…
Efficient Multi-Year Security Constrained AC Transmission Network Expansion Planning
Soumya Das, Ashu Verma, P. R. Bijwe
Solution of multi-year, dynamic AC Transmission network expansion planning (TNEP) problem is gradually taking center stage of planning research owing to its potential accuracy. How…
A New Efficient Methodology for AC Transmission Network Expansion Planning in The Presence of Uncertainties
Soumya Das, Ashu Verma, P. R. Bijwe
Consideration of generation, load and network uncertainties in modern transmission network expansion planning (TNEP) is gaining interest due to large-scale integration of renewable…
Security Constrained AC Transmission Network Expansion Planning
Soumya Das, Ashu Verma, P. R. Bijwe
Modern transmission network expansion planning (TNEP) is carried out with AC network model, which is able to handle voltage and voltage stability constraints. However, such a model…
Computationally Efficient Day-Ahead OPF using Post-Optimal Analysis with Renewable and Load Uncertainties
Parikshit Pareek, Ashu Verma
This paper presents a method to handle renewable source and load uncertainties in Dynamic Day-ahead Optimal Power Flow (DA-OPF) using post-optimal analysis of linear programming pr…