Dynamic Power Allocation for Smart Grids via ADMM

TL;DR

This paper introduces two semi-distributed algorithms based on ADMM for dynamic power allocation in smart grids, addressing supply fluctuations from renewable sources with theoretical bounds and experimental validation.

Contribution

It presents novel ADMM-based algorithms for real-time power allocation in smart grids, including feasibility guarantees and bounds on solution accuracy.

Findings

Algorithms effectively adapt to supply variability

Bounded the distance to optimal solutions

Validated results through experiments

Abstract

Electric power distribution systems will encounter fluctuations in supply due to the introduction of renewable sources with high variability in generation capacity. It is therefore necessary to provide algorithms that are capable of dynamically finding approximate solutions. We propose two semi-distributed algorithms based on ADMM and discuss their advantages and disadvantages. One of the algorithms computes a feasible approximate of the optimal power allocation at each instance. We require coordination between the nodes to guarantee feasibility of each of the iterates. We bound the distance from the approximate solutions to the optimal solution as a function of the variation in optimal power allocation. Finally, we verify our results via experiments.