A Graph Computation based Sequential Power Flow Calculation for Large-Scale ACDC Systems

TL;DR

This paper introduces a graph computation-based sequential power flow method for large-scale AC/DC systems, enabling parallel analysis and significantly improving computational efficiency.

Contribution

It develops a novel graph-theoretic approach that partitions large AC/DC systems for parallel power flow analysis, enhancing speed and scalability.

Findings

Achieves high computational performance in large-scale systems.

Demonstrates accuracy and efficiency through extensive case studies.

Supports parallel processing for faster power flow calculations.

Abstract

This paper proposes a graph computation based sequential power flow calculation method for Line Commutated Converter (LCC) based large-scale AC/DC systems to achieve a high computing performance. Based on the graph theory, the complex AC/DC system is first converted to a graph model and stored in a graph database. Then, the hybrid system is divided into several isolated areas with graph partition algorithm by decoupling AC and DC networks. Thus, the power flow analysis can be executed in parallel for each independent area with the new selected slack buses. Furthermore, for each area, the node-based parallel computing (NPC) and hierarchical parallel computing (HPC) used in graph computation are employed to speed up fast decoupled power flow (FDPF). Comprehensive case studies on the IEEE 300-bus, polished South Carolina 12,000-bus system and a China 11,119-bus system are performed to demonstrate the accuracy and efficiency of the proposed method