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A Multi-Agent Framework for Smart Grid Simulations: Strategies for power-to-heat flexibility management in residential context
Open accessAbstract
The complexity of a system, such as the Smart Grid, comes from the interaction of different fields of expertise and actors cooperating together. As a result, co-simulation frameworks are emerging to meet the need for analysis from a broader perspective. The feature to better understand the Smart Grid environment is the ability to simulate its different components simultaneously. Therefore, we propose a multi-agent co-simulation framework that can serve as a test-bed for multiple Smart Grid strategies. In particular, we focus on Demand Response programs that exploit the thermal behaviour of residential buildings. The proposed framework is modular to test Plug&Play models. Moreover, it is highly flexible and configurable to evaluate realistic scenarios. We tested the platform on a case study of 1,000 buildings, performing an analysis of the effects of micro temperature deviations in buildings on the primary grid substation balancing problem. The results show the flexibility of the platform in testing different strategies. Moreover, power imbalances could be mitigated simply by acting on the indoor temperature set-points with smaller deviations.
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“In networked microgrids or regional integrated energy systems (RIES), aggregator agents typically serve as intermediaries between local controllers (e.g., building agents) and higher-order coordination actors such as distribution system operators (DSOs).”
From Explainable AI and Multi-Agent Systems for Energy Management in IoT-Edge Environments: A State of the Art Review (2026) · cites this paper as [61]
In the citing paper
“At the asset tier, building agents control HVAC, lighting, onsite generation, and storage.They sense power demand profiles directly and reconcile internal needs with external directives from aggregators or supervisors [61].”
From Explainable AI and Multi-Agent Systems for Energy Management in IoT-Edge Environments: A State of the Art Review (2026) · cites this paper as [61]
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Research works printed but not linked: 16
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Cited by
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Álvarez-López, C., González-Briones, A., & Li, T. (2026) · Electronics · doi:10.3390/electronics15020385 · Cited by 23
Metadata
- Authors
- Rando Mazzarino, P., Macii, A., Bottaccioli, L., & Patti, E.
- Affiliations
- Politecnico di Torino (IT)
- Venue
- Sustainable Energy, Grids and Networks
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 34
- Pages
- 101072
- ISSN
- 2352-4677 (ISSN-L)
- OpenAlex
- W4377101000
- Cited by
- 12
- References
- 0
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 5 · 2023: 1
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Sustainable Energy Grids and Networks (publishedVersion, cc-by)
- PORTO@Iris (submittedVersion, cc-by-nc-nd)
- Funders
- Ministero dell’Istruzione, dell’Università e della Ricerca (ECS00000036)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Keywords
- multi-agent systems, smart grid simulation, power-to-heat, demand response, residential buildings, building thermal behavior, testbed
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