A Distributed Algorithm for Demand Response with Mixed-Integer Variables

TL;DR

This paper introduces a fast distributed gradient algorithm for demand response management involving households with mixed-integer variables, demonstrating scalable convergence properties across system sizes.

Contribution

It proposes a novel fast distributed gradient algorithm applied to the dual function of a demand response model with mixed-integer variables, ensuring scalable convergence.

Findings

Convergence behavior is consistent across different system sizes.

The algorithm efficiently handles mixed-integer variables in demand response.

Minimal parameter tuning suffices for reliable convergence.

Abstract

This letter presents a fast distributed algorithm for aggregating a large number of households with mixed-integer variables and intricate couplings between devices. The proposed fast distributed gradient algorithm is applied to the double smoothed dual function of the adopted DR model. The results also show that, with minimal parameter adjustments, the convergence of the dual objective exhibits the same behavior irrespective of the system size.