The goal is to efficiently coordinate the energy production and energy distribution from different sources in order to minimize the overall energy consumption.

Optimal control of building energy systems with multiple energy sources using predictive model based control and reinforcement learning. Chenzi Huang ...

A reinforcement learning based approach is developed and compared to the MPC controller in detail and both methods are able to decrease energy consumption ...

Reinforcement learning (RL) approaches allow agents to implicitly learn the physics or detector dynamics and the behavior policy that maximizes a designated ...

In this paper the control of building energy systems with multiple energy sources and storages are analysed. The goal is to efficiently coordinate the ...

In this paper, we proposed an MPC framework based on a long-term hybrid deep learning prediction model for operational optimization of a PVB system.

Model predictive control (MPC) offers an optimal control technique to establish and ensure that the total operation cost of multi-energy systems remains at ...

In this contribution we develop and analyse intelligent control methods in order to optimise the energy efficiency of a modern residential building.

Dec 1, 2021 · Model predictive control (MPC) offers an optimal control technique to establish and ensure that the total operation cost of multi-energy ...

Apr 30, 2021 · I have been reading a lot about MPC used in control theory, but I don't understand the difference with Model-based RL approaches.