A Linear Branch Flow Model for Radial Distribution Networks and its Application to Reactive Power Optimization and Network Reconfiguration

TL;DR

This paper introduces a new linear branch flow model for radial distribution networks that improves accuracy and computational efficiency in reactive power optimization and network reconfiguration tasks.

Contribution

The paper proposes the modified DistFlow model, which reduces errors of conventional linear models and enables explicit, non-iterative calculation of power flows and voltages.

Findings

Modified DistFlow has higher accuracy than existing models.

The MIQP formulation is more computationally efficient.

Simulations validate improved performance in distribution network optimization.

Abstract

This paper presents a cold-start linear branch flow model named modified DistFlow. In modified DistFlow, the active and reactive power are replaced by their ratios to voltage magnitude as state variables, so that errors introduced by conventional branch flow linearization approaches due to their complete ignoring of the quadratic term are reduced. Based on the path-branch incidence matrix, branch power flows and nodal voltage magnitudes can be obtained in a non-iterative and explicit manner. Subsequently, the proposed modified DistFlow model is applied to the problem of reactive power optimization and network reconfiguration, transforming it into a mixed-integer quadratic programming (MIQP). Simulations show that the proposed modified DistFlow has a better accuracy than existing cold-start linear branch flow models for distribution networks, and the resulting MIQP model for reactive power optimization and network reconfiguration is much more computationally efficient than existing benchmarks.