Application of Stochastic Optimization Techniques to the Unit Commitment Problem -- A Review

TL;DR

This review paper surveys recent developments in stochastic optimization techniques for the unit commitment problem, emphasizing their role in integrating renewable energy sources into power grids to address climate change.

Contribution

It provides a comprehensive overview of different problem formulations and stochastic methods, comparing recent research contributions and case studies in the field.

Findings

Various stochastic optimization methods are applied to unit commitment.

Renewable energy integration challenges are addressed through these techniques.

Comparative analysis highlights effective approaches for grid stability.

Abstract

Due to the established energy production methods contribution to the climate crisis, renewable energy is to replace a substantial part of coal or nuclear plants to prevent greenhouse gases or toxic waste entering the atmosphere. This relatively quick shift in energy production, primarily pushed by increasing political and economical pressure, requires enormous effort on the part of the energy providers to balance out production fluctuations. Consequently, a lot of research is conducted in the key area of stochastic unit commitment (UC) on electrical grids and microgrids. The term unit commitment includes a large variety of optimization techniques, and in this paper we will review recent developments in this area. We start by giving an overview over different problem definitions and stochastic optimization procedures, to then assess recent contributions to this topic. We therefore compare the proposals and case studies of several papers.