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I-Shaped Developer
I-shapedSpecialist — deep expertise in Python
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Nanda Kishor Panda
@nkpanda97
Shuyi Gao
@ShuyiGao
Energy Quant Research Institution
@EnergyQuantResearch
Top Repositories
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.
Using OMLT to develop ML based surrogate models that can eliminate the need for long optimization models with lots of variables and parametres.
Represent trained machine learning models as Pyomo optimization formulations
Solution of a two-stage stochastic model useful for investment planning using pyomo and mpi-sppy.
Deterministic version of the imitation learning based surrogate model used for three phase OPF analysis
An Open-Source Optimal Power Flow Formulation: Integrating Pyomo & OpenDSS in Python
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
Deterministic and stochastic modeling of operation for a mockup distribution network.
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