Distributed Dual Gradient Tracking for Priority-Considered Load Shedding

TL;DR

This paper introduces a distributed dual gradient tracking approach to optimize economic dispatch with transmission loss considerations and priority-based load shedding in power systems, enhancing efficiency and reliability.

Contribution

It proposes a novel distributed algorithm for solving a convex relaxation of the EDP with transmission losses and integrates priority-aware load shedding into a unified framework.

Findings

Effective distributed algorithm for EDP with transmission losses.

Priority-based load shedding scheduling improves system reliability.

Simulation results confirm the method's effectiveness.

Abstract

This paper studies two fundamental problems in power systems: the economic dispatch problem (EDP) and load shedding. For the EDP, an extension of the problem considering the transmission losses is presented. Because the optimization problem is non-convex owing to quadratic equality constraints modeling the transmission losses, a convex relaxation method is presented. Under a particular assumption, it is shown that a distributed algorithm can be designed to solve the considered EDP. Furthermore, this work aims to handle an overloading problem by employing an optimal load shedding method. Emphasis is placed on scheduling the load shedding when there exist some priorities on the loads. First, a novel optimization problem is proposed to obtain the load shedding according to the predefined priority order. Then, a distributed algorithm solving the optimization problem is presented. Finally, this paper presents how to integrate the proposed algorithms, i.e., the EDP and the load shedding, in a distributed manner. Simulation results are presented to demonstrate the effectiveness of the proposed method.