Graph Computing based Distributed Fast Decoupled Power Flow Analysis

TL;DR

This paper introduces a graph computing based distributed approach for fast and accurate power flow analysis in large-scale power systems, enabling parallel processing and improved computational efficiency.

Contribution

It proposes a novel distributed power flow analysis method using graph computing, dividing the system into areas for parallel analysis without sacrificing accuracy.

Findings

Achieves accurate power flow results on IEEE 118-bus and MP 10790-bus systems.

Demonstrates significant computational performance improvements.

Ensures system state consistency across distributed areas.

Abstract

Power flow analysis plays a fundamental and critical role in the energy management system (EMS). It is required to well accommodate large and complex power system. To achieve a high performance and accurate power flow analysis, a graph computing based distributed power flow analysis approach is proposed in this paper. Firstly, a power system network is divided into multiple areas. Slack buses are selected for each area and, at each SCADA sampling period, the inter-area transmission line power flows are equivalently allocated as extra load injections to corresponding buses. Then, the system network is converted into multiple independent areas. In this way, the power flow analysis could be conducted in parallel for each area and the solved system states could be guaranteed without compromise of accuracy. Besides, for each area, graph computing based fast decoupled power flow (FDPF) is employed to quickly analyze system states. IEEE 118-bus system and MP 10790-bus system are employed to verify the results accuracy and present the promising computation performance of the proposed approach.