mlsanityData to 14 Oct 2026

Optimal Management of Grid-Interactive Efficient Buildings via Safe Reinforcement Learning

arXiv 2409.08132 ↗First posted 12 Sep 2024eess.SY cs.SYcited by 1

On the map: Deep reinforcement learning methods → RL for energy, networks and operations

Abstract (arXiv)

Reinforcement learning (RL)-based methods have achieved significant success in managing grid-interactive efficient buildings (GEBs). However, RL does not carry intrinsic guarantees of constraint satisfaction, which may lead to severe safety consequences. Besides, in GEB control applications, most existing safe RL approaches rely only on the regularisation parameters in neural networks or penalty of rewards, which often encounter challenges with parameter tuning and lead to catastrophic constraint violations. To provide enforced safety guarantees in controlling GEBs, this paper designs a physics-inspired safe RL method whose decision-making is enhanced through safe interaction with the environment. Different energy resources in GEBs are optimally managed to minimize energy costs and maximize customer comfort. The proposed approach can achieve strict constraint guarantees based on prior knowledge of a set of developed hard steady-state rules. Simulations on the optimal management of GEBs, including heating, ventilation, and air conditioning (HVAC), solar photovoltaics, and energy storage systems, demonstrate the effectiveness of the proposed approach.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 7 of its 18 references that are in the map. First posted on arXiv 12 Sep 2024.

Builds on

7 of 18 references.

References · 7

  1. 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
  2. 2020Conservative Safety Critics for Explorationcited by 113
  3. 2021Reinforcement Learning for Selective Key Applications in Power Systems: Recent Advances and Future Challengescited by 50
  4. 2017Decentralized and Distributed Temperature Control via HVAC Systems in Energy Efficient Buildingscited by 4
  5. 2017Distributed Temperature Control via Geothermal Heat Pump Systems in Energy Efficient Buildingscited by 1
  6. 2020Two-Facet Scalable Cooperative Optimization of Multi-Agent Systems in The Networked Environmentcited by 1
  7. 2022Two-Level Decentralized-Centralized Control of Distributed Energy Resources in Grid-Interactive Efficient Buildingscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Safe Deep Reinforcement Learning for Building Heating Control and Demand-side Flexibilitycited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Data-Driven Policy Mapping for Safe RL-based Energy Management Systems
  2. 2026Safe Deep Reinforcement Learning for Energy-Efficient HVAC Control in Multi-Zone Residential Buildings
  3. 2024Safe Reinforcement Learning for Power System Control: A Review
  4. 2024A Review of Safe Reinforcement Learning Methods for Modern Power Systems
  5. 2025Optimizing Energy Management of Smart Grid using Reinforcement Learning aided by Surrogate models built using Physics-informed Neural Networks
  6. 2024A Critical Review of Safe Reinforcement Learning Techniques in Smart Grid Applications
  7. 2026LLM-Guided Safe Reinforcement Learning for Energy System Topology Reconfiguration ↗
  8. 2025A Receding Horizon Reinforcement Learning Framework for Campus Chiller Energy Management - A case study from an Australian University