Coordination of Electrical and Heating Resources by Self-Interested Agents

TL;DR

This paper introduces a novel distributed hybrid algorithm for multi-energy resource scheduling that optimizes both individual and collective objectives in decentralized energy systems, ensuring near-optimal solutions while respecting stakeholders' goals.

Contribution

It presents a new hybrid distributed algorithm combining gossiping and local search for multi-energy scheduling, addressing both electrical and heating resources.

Findings

Algorithm finds globally near-optimal solutions.

Protects stakeholders' economic interests and technical properties.

Effective in pure electrical and gas-based technology scenarios.

Abstract

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.