Hierarchical Graph Modeling for Multi-Scale Optimization of Power Systems

TL;DR

This paper introduces a graph modeling framework for multi-scale hierarchical optimization in power systems, implemented in Julia, to improve the management of complex, multi-level operational problems.

Contribution

It presents a novel graph abstraction and implementation for hierarchical power system optimization, enabling better problem construction, visualization, and solution.

Findings

Facilitates modeling of multi-scale power system problems.

Enables visualization of complex hierarchical structures.

Supports efficient solution of tri-level optimization frameworks.

Abstract

Hierarchical optimization architectures are used in power systems to manage disturbances and phenomena that arise at multiple spatial and temporal scales. We present a graph modeling abstraction for representing such architectures and an implementation in the ${\tt Julia}$ package ${\tt Plasmo.jl}$. We apply this framework to a tri-level hierarchical framework arising in wholesale market operations that involves day-ahead unit commitment, short-term unit commitment, and economic dispatch. We show that graph abstractions facilitate the construction, visualization, and solution of these complex problems.