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Peter Palensky

An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of Domains

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Aug 15, 2024
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RL-ADN: A High-Performance Deep Reinforcement Learning Environment for Optimal Energy Storage Systems Dispatch in Active Distribution Networks

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Aug 07, 2024
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EnergyDiff: Universal Time-Series Energy Data Generation using Diffusion Models

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Jul 18, 2024
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A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and Prediction

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May 06, 2024
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EV2Gym: A Flexible V2G Simulator for EV Smart Charging Research and Benchmarking

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Apr 02, 2024
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Quantum Neural Networks for Power Flow Analysis

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Nov 04, 2023
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Stable Training of Probabilistic Models Using the Leave-One-Out Maximum Log-Likelihood Objective

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Oct 05, 2023
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A Constraint Enforcement Deep Reinforcement Learning Framework for Optimal Energy Storage Systems Dispatch

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Jul 26, 2023
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Targeted Analysis of High-Risk States Using an Oriented Variational Autoencoder

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Mar 20, 2023
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Generating Contextual Load Profiles Using a Conditional Variational Autoencoder

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Sep 08, 2022
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