Coordination of Electrical and Heating Resources by Self-Interested Agents

Fuente: arXiv
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Autori principali: Schrage, Rico, Radler, Jari, Nieße, Astrid
Natura: Preprint
Pubblicazione: 2025
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author Schrage, Rico
Radler, Jari
Nieße, Astrid
author_facet Schrage, Rico
Radler, Jari
Nieße, Astrid
contents With the rise of distributed energy resources and sector coupling, distributed optimization can be a sensible approach to coordinate decentralized energy resources. Further, district heating, heat pumps, cogeneration, and sharing concepts like local energy communities introduce the potential to optimize heating and electricity output simultaneously. To solve this issue, we tackle the distributed multi-energy scheduling optimization problem, which describes the optimization of distributed energy generators over multiple time steps to reach a specific target schedule. This work describes a novel distributed hybrid algorithm as a solution approach. This approach is based on the heuristics of gossiping and local search and can simultaneously optimize the private objective of the participants and the collective objective, considering multiple energy sectors. We show that the algorithm finds globally near-optimal solutions while protecting the stakeholders' economic goals and the plants' technical properties. Two test cases representing pure electrical and gas-based technologies are evaluated.
format Preprint
id arxiv_https___arxiv_org_abs_2506_16277
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Coordination of Electrical and Heating Resources by Self-Interested Agents
Schrage, Rico
Radler, Jari
Nieße, Astrid
Multiagent Systems
With the rise of distributed energy resources and sector coupling, distributed optimization can be a sensible approach to coordinate decentralized energy resources. Further, district heating, heat pumps, cogeneration, and sharing concepts like local energy communities introduce the potential to optimize heating and electricity output simultaneously. To solve this issue, we tackle the distributed multi-energy scheduling optimization problem, which describes the optimization of distributed energy generators over multiple time steps to reach a specific target schedule. This work describes a novel distributed hybrid algorithm as a solution approach. This approach is based on the heuristics of gossiping and local search and can simultaneously optimize the private objective of the participants and the collective objective, considering multiple energy sectors. We show that the algorithm finds globally near-optimal solutions while protecting the stakeholders' economic goals and the plants' technical properties. Two test cases representing pure electrical and gas-based technologies are evaluated.
title Coordination of Electrical and Heating Resources by Self-Interested Agents
topic Multiagent Systems
url https://arxiv.org/abs/2506.16277