Neda Vahabzad

Neda Vahabzad

@neda-vahabzad

PhD Candidate at TU Delft

Netherlands
4
Followers
3
Following
8
Public Repos
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Private Repos

Language Breakdown

Lines of code distribution across 5 owned repositories

1.7M Total LOC
Python
1,479,927 lines
87.3%
N/A
Jupyter Notebook
202,771 lines
12.0%
N/A
PureBasic
12,276 lines
0.7%
N/A
I

I-Shaped Developer

I-shaped

Specialist — deep expertise in Python

Python
Jupyter Notebook
PureBasic

Collaboration Network

Global Impact visualization

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Neda Vahabzad
0 active collaborators

Repos

10

PRs

0

Growth

+18%

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Coding Streak

Contribution activity over the past year

2 days
193
Contributions
2
Commits
0
Pull Requests
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Top Repositories

Imitation-Learning-Surrogate-Model-for-Stochastic-Three-Phase-Distribution-OPF

This repository presents a stochastic imitation learning–based surrogate model (IL-SOM) for three-phase distribution system operation, combining scenario-based uncertainty modeling with a stochastic optimal power flow (OPF) framework for networks with distributed generation and renewable energy sources.

1 0
Python
OMLT-based-surrogate-models-for-optimization

Using OMLT to develop ML based surrogate models that can eliminate the need for long optimization models with lots of variables and parametres.

1 0
Python
OMLT

Represent trained machine learning models as Pyomo optimization formulations

0 0
Python
stochastic-investment-planning

Solution of a two-stage stochastic model useful for investment planning using pyomo and mpi-sppy.

0 0
Jupyter Notebook
Imitation-learning-surrogate-model-for-deterministic-OPF-model-of-a-three-phase-distribution-system

Deterministic version of the imitation learning based surrogate model used for three phase OPF analysis

0 0
Python
Open-DSOPF

An Open-Source Optimal Power Flow Formulation: Integrating Pyomo & OpenDSS in Python

0 0
Python
Optimization-based-data-generation-for-energy-system-models

This repository provides utilities for scenario generation and data preparation for optimization-based energy system models and machine learning applications. It generates stochastic scenarios for load, solar, wind, and electricity price profiles, solves a deterministic optimization model for each scenario, and structures the resulting outputs into

0 0
Python
Distribution-system-operation-mockup_model

Deterministic and stochastic modeling of operation for a mockup distribution network.

0 0
Jupyter Notebook

Open Source Impact

Contributions to external projects

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