Process Systems Engineering Tools for Optimization of Trained Machine Learning Models: Comparative and Perspective
FJ López-Flores, C Ramírez-Márquez… - Industrial & …, 2024 - ACS Publications
This article studies the relevance of innovative Process Systems Engineering (PSE) tools
that can reformulate trained machine learning models that are driven by advances in …
that can reformulate trained machine learning models that are driven by advances in …
[HTML][HTML] RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks
Abstract Deep Reinforcement Learning (DRL) presents a promising avenue for optimizing
Energy Storage Systems (ESSs) dispatch in distribution networks. This paper introduces RL …
Energy Storage Systems (ESSs) dispatch in distribution networks. This paper introduces RL …
DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks
The integration of distributed energy resources (DER) has escalated the challenge of
voltage magnitude regulation in distribution networks. Model-based approaches, which rely …
voltage magnitude regulation in distribution networks. Model-based approaches, which rely …
CommonPower: Supercharging Machine Learning for Smart Grids
The growing complexity of power system management has led to an increased interest in
the use of reinforcement learning (RL). However, no tool for comprehensive and realistic …
the use of reinforcement learning (RL). However, no tool for comprehensive and realistic …
Safe Imitation Learning-based Optimal Energy Storage Systems Dispatch in Distribution Networks
The integration of distributed energy resources (DER) has escalated the challenge of
voltage magnitude regulation in distribution networks. Traditional model-based approaches …
voltage magnitude regulation in distribution networks. Traditional model-based approaches …