A High-Performance Energy Management System based on Evolving Graph

TL;DR

This paper introduces a high-performance energy management system framework that models power grids as evolving graphs, significantly improving computational efficiency for real-time analysis in complex modern power systems.

Contribution

It develops an EMS analysis framework based on evolving graphs, enabling faster dynamic analysis applications like state estimation and power flow for large-scale power systems.

Findings

Speeds up computation performance in power system analysis

Achieves real-time analysis capability for large-scale systems

Validated on a 2749-bus system in Sichuan, China

Abstract

As the fast growth and large integration of distributed generation, renewable energy resource, energy storage system and load response, the modern power system operation becomes much more complicated with increasing uncertainties and frequent changes. Increased operation risks are introduced to the existing commercial Energy Management System (EMS), due to its limited computational capability. In this paper, a high-performance EMS analysis framework based on the evolving graph is developed. A power grid is first modeled as an evolving graph and then the power system dynamic analysis applications, like network topology processing (NTP), state estimation (SE), power flow (PF), and contingency analysis (CA), are efficiently implemented on the system evolving graph to build a high-performance EMS analysis framework. Its computation performance is field tested using a 2749-bus power system in Sichuan, China. The results illustrate that the proposed EMS remarkably speeds up the computation performance and reaches the goal of real-time power system analysis.