Distributionally Robust Decentralized Volt-Var Control with Network Reconfiguration

TL;DR

This paper introduces a decentralized, distributionally robust volt-var control and network reconfiguration method for active distribution networks with high PV integration, enhancing local decision-making under uncertainty.

Contribution

It proposes a novel two-stage distributionally robust optimization approach combined with a decomposition algorithm for efficient, localized control in active distribution networks.

Findings

Demonstrates superior out-of-sample performance on IEEE 123 bus system.

Achieves computational efficiency suitable for real-time applications.

Effectively manages PV output uncertainty through risk-informed decisions.

Abstract

This paper presents a decentralized volt-var optimization (VVO) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization; decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions.