87 Citations
Energy Optimal Control of a Multivalent Building Energy System using Machine Learning
- EngineeringSMARTGREENS
- 2021
Reinforcement learning can achieve better results with less computational resources than model predictive controller approach in order to optimise the energy efficiency of a modern residential building with multiple renewable energy sources.
Coordinated energy management for a cluster of buildings through deep reinforcement learning
- Engineering
- 2021
A Review of Recent Advances on Reinforcement Learning for Smart Home Energy Management
- Engineering2020 IEEE Electric Power and Energy Conference (EPEC)
- 2020
Smart home energy management is one of the core problems in modern power grids. With the increasing adoption of different types of electric appliances and on-site intermittent renewable energy…
Monitoring data-driven Reinforcement Learning controller training: A comparative study of different training strategies for a real-world energy system
- Engineering, Computer Science
- 2021
Towards an intelligent HVAC system automation using Reinforcement Learning
- EngineeringJournal of Physics: Conference Series
- 2021
HVAC systems are among the biggest energy consumers in buildings and therefore in the focus of optimal control research. In practice, rule-based control and PID controllers are typically used and…
Energy-Efficient Control of a Building HVAC System using Reinforcement Learning
- Engineering
- 2020
Advanced climate control algorithms provide a cost-effective approach to reduce the large energy footprint of heating, ventilation, and air conditioning (HVAC) systems in buildings. Although model…
Reinforcement Learning Techniques for Optimal Power Control in Grid-Connected Microgrids: A Comprehensive Review
- EngineeringIEEE Access
- 2020
The need to improve and scale multi-agent RL methods to enable seamless distributed power dispatch among interconnected microgrids is identified.
Study on the application of reinforcement learning in the operation optimization of HVAC system
- Engineering
- 2020
An innovative RL-based model-free control strategy combining rule-based and RL- based control algorithm as well as complete application process is proposed and shown to be more suitable for small-scale operation optimization problems.
References
SHOWING 1-10 OF 105 REFERENCES
Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings
- EngineeringEnergies
- 2018
A smart grid facilitates more effective energy management of an electrical grid system. Because both energy consumption and associated building operation costs are increasing rapidly around the…
On-Line Building Energy Optimization Using Deep Reinforcement Learning
- EngineeringIEEE Transactions on Smart Grid
- 2019
The benefits of using deep reinforcement learning, a hybrid type of methods that combines reinforcement learning with deep learning, to perform on-line optimization of schedules for building energy management systems, are explored for the first time in the smart grid context.
Optimising operational cost of a smart energy hub, the reinforcement learning approach
- EngineeringInt. J. Parallel Emergent Distributed Syst.
- 2015
A new solution which is entitled ‘smart energy hub’ (SEH) that models a multi-carrier energy system in a SG and shows that running costs are reduced up to 40% while keeping the household owner's desired comfort levels.
A DEEP REINFORCEMENT LEARNING APPROACH TO USINGWHOLE BUILDING ENERGYMODEL FOR HVAC OPTIMAL CONTROL
- Engineering
- 2018
Whole building energy model (BEM) is difficult to be used in the classical model-based optimal control (MOC) because of its high-dimension nature and intensive computational speed. This study…
Battery Energy Management in a Microgrid Using Batch Reinforcement Learning
- Engineering
- 2017
Motivated by recent developments in batch Reinforcement Learning (RL), this paper contributes to the application of batch RL in energy management in microgrids. We tackle the challenge of finding a…
Autonomous HVAC Control, A Reinforcement Learning Approach
- EngineeringECML/PKDD
- 2015
The architecture comprises a number of different learning methods each of which contributes to create a complete autonomous thermostat capable of controlling a HVAC system to enable a Reinforcement Learning agent to successfully control the HV AC system by optimising both occupant comfort and energy costs.
Online tuning of a supervisory fuzzy controller for low-energy building system using reinforcement learning
- Computer Science
- 2010
Energy management in solar microgrid via reinforcement learning using fuzzy reward
- Engineering
- 2018
ABSTRACT This paper proposes a single-agent system towards solving energy management issues in solar microgrids. The proposed system consists of a photovoltaic (PV) source, a battery bank, a…
Residential Energy Management with Deep Reinforcement Learning
- Engineering2018 International Joint Conference on Neural Networks (IJCNN)
- 2018
A deep reinforcement learning based approach has been proposed to solve this residential energy management problem and can directly learn the optimal energy management strategy based on reinforcement learning.