Abodh Poudyal (abodh)

abodh

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Company:National Renewable Energy Laboratory

Location:Golden, CO

Twitter:@abodh_ltd

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Abodh Poudyal's repositories

Electricity-cost-forecasting-using-machine-learning-and-deep-learning-models

Comparative study of ANN, CNN, LSTM, and ARIMA for time-series forecasting

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LinDistRestoration

A linearized 3-phase unbalanced distribution power flow-based restoration for multi-fault conditions using mixed-integer linear programming.

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proactive_resilience_planning

Two-stage stochastic planning model for proactive generation dispatch and line hardening investment to enhance the resilience of power system

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Neural_Network_Inertia_Estimation

Estimating power system inertia using convolutional neural network

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Continuation-Power-Flow

Conducts continuation power flow in the IEEE-14 bus system

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Inertia-Estimation-using-Federated-Learning

Multi-area Inertia Estimation Using Federated Learning

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DCOPF

A generalized DCOPF formulation for standard IEEE test cases

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Hurricane_Flood_WSU

Compound effect of Hurricane and Flood on Electric Power Systems

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Newton-Rhapson-Power-Flow

Implementation of Newton Rhapson Power Flow algorithm on IEEE-14 bus system with transformer taps.

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WSU-Restoration

GridAPPS-D Restoration Application

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abodh.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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D-Net

Network data structure of distribution feeders from OpenDSS.

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D-OPF

A toolbox for Distribution Optimal Power Flow (D-OPF) Algorithms

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mpi-sppy

MPI-based Stochastic Programming in PYthon

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Neural-Network-Autoencoder

This is a simple example of using a neural network as an autoencoder without using any machine learning libraries in Python.

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Parallel_matrix_mutiplication

Parallel matrix multiplication using OpenMP in C and South Dakota State University's roaring thunder cluster.

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Power-Flow-with-Sparse-Matrix-Reordering

Three reordering schemes of Sparse Matrix for better computation. Scheme 0, Scheme I, and Scheme II

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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.

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pysp

PySP: Stochastic Programming in Python

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Q-learning_maze_navigator

Maze navigator (grid world) using value function approximation and Q-learning

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sampleGridAPPSD

A modification on the sample app provided by PNNL on GridAPPS-D.

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scenred2003

Scenario reduction algorithms for stochastic programming

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SummerInternship2021WSU

We will share relevant literature and update source codes via this repository.

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