abodh Goto Github PK
Name: Abodh Poudyal
Type: User
Company: National Renewable Energy Laboratory
Bio: Power Systems Researcher @NREL
Location: Golden, CO
Abodh Poudyal's Projects
abodh.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
continuation-power-flow
Conducts continuation power flow in the IEEE-14 bus system
d-net
Network data structure of distribution feeders from OpenDSS.
d-opf
A toolbox for Distribution Optimal Power Flow (D-OPF) Algorithms
dcopf
A generalized DCOPF formulation for standard IEEE test cases
electricity-cost-forecasting-using-machine-learning-and-deep-learning-models
Comparative study of ANN, CNN, LSTM, and ARIMA for time-series forecasting
hurricane_flood_wsu
Compound effect of Hurricane and Flood on Electric Power Systems
inertia-estimation-using-federated-learning
Multi-area Inertia Estimation Using Federated Learning
lindistrestoration
A linearized 3-phase unbalanced distribution power flow-based restoration for multi-fault conditions using mixed-integer linear programming.
mpi-sppy
MPI-based Stochastic Programming in PYthon
neural-network-autoencoder
This is a simple example of using a neural network as an autoencoder without using any machine learning libraries in Python.
neural_network_inertia_estimation
Estimating power system inertia using convolutional neural network
newton-rhapson-power-flow
Implementation of Newton Rhapson Power Flow algorithm on IEEE-14 bus system with transformer taps.
parallel_matrix_mutiplication
Parallel matrix multiplication using OpenMP in C and South Dakota State University's roaring thunder cluster.
power-flow-with-sparse-matrix-reordering
Three reordering schemes of Sparse Matrix for better computation. Scheme 0, Scheme I, and Scheme II
powergrid-models
CIM interfaces for GridLAB-D and OpenDSS; data and test scripts for the PNNL taxonomy feeders, EPRI large-circuit and DPV test feeders, and some IEEE test feeders.
proactive_resilience_planning
Two-stage stochastic planning model for proactive generation dispatch and line hardening investment to enhance the resilience of power system
pysp
PySP: Stochastic Programming in Python
q-learning_maze_navigator
Maze navigator (grid world) using value function approximation and Q-learning
samplegridappsd
A modification on the sample app provided by PNNL on GridAPPS-D.
scenred2003
Scenario reduction algorithms for stochastic programming
summerinternship2021wsu
We will share relevant literature and update source codes via this repository.
wsu-restoration
GridAPPS-D Restoration Application
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