# A Hierarchical Approach to Multi-Energy Demand Response: From Electricity to Multi-Energy Applications

arXiv: https://arxiv.org/abs/2005.02339 · HTML: https://mlsanity.com/paper/2005.02339/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 May 2020.

## Built on by (most cited first, 2 of 2)

- [End-to-End Demand Response Model Identification and Baseline Estimation with Deep Learning](https://mlsanity.com/paper/2109.00741/) (2021)
- [Causative Cyberattacks on Online Learning-based Automated Demand Response Systems](https://mlsanity.com/paper/2307.15175/) (2023)

## Abstract (arXiv)

Due to proliferation of energy efficiency measures and availability of the renewable energy resources, traditional energy infrastructure systems (electricity, heat, gas) can no longer be operated in a centralized manner under the assumption that consumer behavior is inflexible, i.e. cannot be adjusted in return for an adequate incentive. To allow for a less centralized operating paradigm, consumer-end perspective and abilities should be integrated in current dispatch practices and accounted for in switching between different energy sources not only at the system but also at the individual consumer level. Since consumers are confined within different built environments, this paper looks into an opportunity to control energy consumption of an aggregation of many residential, commercial and industrial consumers, into an ensemble. This ensemble control becomes a modern demand response contributor to the set of modeling tools for multi-energy infrastructure systems.