Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission
A supervisory control system using Model Predictive Control (MPC) has been designed to
evaluate the efficiency of wind and solar power and is consistent with the cost function in the …
evaluate the efficiency of wind and solar power and is consistent with the cost function in the …
[PDF][PDF] Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning
A Romero, E Aljalbout, Y Song… - arXiv preprint arXiv …, 2024 - researchgate.net
An open research question in robotics is how to combine the benefits of model-free
reinforcement learning (RL)—known for its strong task performance and flexibility in …
reinforcement learning (RL)—known for its strong task performance and flexibility in …
A learning-based model predictive control method for unlocking the potential of building energy flexibility
Buildings are regarded as promising energy flexibility resources due to their significant
energy consumption and better integration into the electricity grid. To fully exploit the …
energy consumption and better integration into the electricity grid. To fully exploit the …
Enhanced reinforcement learning-model predictive control for distributed energy systems: Overcoming local and global optimization limitations
H Meng, H Bin, F Qian, T Xu, C Wang, W Liu, Y Yao… - Building …, 2025 - Springer
The complex structures of distributed energy systems (DES) and uncertainties arising from
renewable energy sources and user load variations pose significant operational challenges …
renewable energy sources and user load variations pose significant operational challenges …
Distill2Explain: Differentiable decision trees for explainable reinforcement learning in energy application controllers
Demand-side flexibility is gaining importance as a crucial element in the energy transition
process. Accounting for about 25% of final energy consumption globally, the residential …
process. Accounting for about 25% of final energy consumption globally, the residential …
Learning-based Nonlinear Model Predictive Control Using Deterministic Actor-Critic with Gradient Q-learning Critic
A Salaje, T Chevet, N Langlois - 2024 18th International …, 2024 - ieeexplore.ieee.org
In this paper, we present an off-policy reinforcement learning (RL) method used to tune the
optimal weights of a nonlinear model predictive control (NMPC) scheme. The objective is to …
optimal weights of a nonlinear model predictive control (NMPC) scheme. The objective is to …
An Attention-Based Deep Learning Approach for Forecasting Electricity Prices in Real-Time Electricity Markets
JE do Carmo Junior - 2025 - prism.ucalgary.ca
Real-time electricity markets are characterized by irregular and sudden price swings,
leading to high price volatility and significant uncertainties for market participants. Accurate …
leading to high price volatility and significant uncertainties for market participants. Accurate …
Modelo de controlo preditivo para comunidades de energia
BS Rosário - 2024 - recipp.ipp.pt
Nos objetivos da união europeia para 2050 está consagrado que a união deve de ser
neutra em carbono, para tal a utilização de energias renováveis será praticamente …
neutra em carbono, para tal a utilização de energias renováveis será praticamente …
Data-Driven Model Predictive Control with Reinforcement Learning Algorithms
H Moradimaryamnegari - bia.unibz.it
In this dissertation, we aim to combine model-based (Model Predictive Control) and model-
free (Neural Network) action value functions for the control of robotic systems and their path …
free (Neural Network) action value functions for the control of robotic systems and their path …