Valuing Uncertainties in Wind Generation: An Agent-Based Optimization Approach

TL;DR

This paper introduces an agent-based optimization method that values wind generation uncertainties in the price domain, enabling more flexible market offers and improved system-level management of renewable variability.

Contribution

It proposes a novel approach to uncertainty management by valuing wind uncertainties in the price domain, contrasting with traditional quantity-based methods.

Findings

System-level impacts show improved market efficiency.

Wind offers based on uncertainty valuation outperform fixed-price strategies.

The approach enhances integration of variable renewable energy sources.

Abstract

The increasing integration of variable renewable energy sources such as wind and solar will require new methods of managing generation uncertainty. Existing practices of uncertainty management for these resources largely focuses around modifying the energy offers of such resources in the quantity domain and from a centralized system operator consideration of these uncertainties. This paper proposes an approach to instead consider these uncertainties in the price domain, where more uncertain power is offered at a higher price instead of restricting the quantity offered. We demonstrate system-level impacts on a modified version of the RTS-GMLC system where wind generators create market offers valuing their uncertainties over scenario set of day-ahead production forecasts. The results are compared with a dispatch method in which wind energy is offered at zero marginal price and restricted based on the forecast percentile.