Neural Moving Horizon Estimation: A Systematic Literature Review
The neural moving horizon estimator (NMHE) is a relatively new and powerful state
estimator that combines the strengths of neural networks (NNs) and model-based state …
estimator that combines the strengths of neural networks (NNs) and model-based state …
激励条件下的大规模空调负荷聚合集群优化策略
汤卓凡， 赵建立， 郑庆荣， 赵希超， 石杰 - 电力需求侧管理, 2024 - dsm.ijournals.cn
为提高大规模空调负荷聚合精度, 提升空调集群可调节潜力, 提出了激励条件下的大规模空调
负荷聚合集群优化策略. 首先建立了大规模空调负荷聚合架构, 然后建立单体的二阶空调等值 …
负荷聚合集群优化策略. 首先建立了大规模空调负荷聚合架构, 然后建立单体的二阶空调等值 …
A Data-Driven Modeling and Control Framework for Physics-Based Building Emulators
We present a data-driven modeling and control framework for physics-based building
emulators. Our approach comprises:(a) Offline training of differentiable surrogate models …
emulators. Our approach comprises:(a) Offline training of differentiable surrogate models …
Discovering Symbolic Policy for Building Control using Reinforcement Learning
We propose a learning framework for interpretable HVAC control in buildings using deep
reinforcement learning (DRL). Our framework includes a data-driven surrogate environment …
reinforcement learning (DRL). Our framework includes a data-driven surrogate environment …
Ensemble Learning Method for Forecasting HVAC System Demand
The efficiency of buildings' energy use is one of the energy transition's three fundamental
pillars. It is a current issue that many countries are actively promoting as a means of …
pillars. It is a current issue that many countries are actively promoting as a means of …