Robust Unit Commitment Considering Strategic Wind Generation Curtailment

TL;DR

This paper introduces a robust unit commitment model that incorporates strategic wind generation curtailment to enhance wind dispatchability, reduce operational costs, and maintain system reliability, supported by an efficient solution algorithm and simulation results.

Contribution

It proposes a novel RUC model with strategic wind curtailment to improve wind integration and reduce costs, along with a C&CG algorithm for efficient solution.

Findings

Reduced operational costs in simulations.

Improved wind dispatchability and ramping capabilities.

Validated effectiveness on IEEE test systems.

Abstract

Wind generation is traditionally treated as a non-dispatchable resource and is fully absorbed unless there are security issues. To tackle the operational reliability issues caused by the volatile and non-dispatchable wind generation, many dispatch frameworks have been proposed, including robust unit commitment (RUC) considering wind variation. One of the drawbacks that commonly exist in those dispatch frameworks is increased demand on flexibility resources and associated costs. To improve wind dispatchability and reduce flexibility resource costs, in this paper, we propose a novel RUC model considering strategic wind generation curtailment (WGC). Strategic WGC can reduce wind uncertainty and variability and increase the visibility of wind generation capacity. As a result, the ramping requirement for wind generation will be reduced and ramp-up capability of wind generation can be increased, leading to reduced day-ahead operational cost with guaranteed operational reliability requirement of power systems. The economic benefits also include profits gained by wind farm by providing ramping-up capacities other auxiliary services. We also propose a solution algorithm based on the column and constraint generation (C&CG). Simulations on the IEEE 39-bus system and two larger test systems demonstrate the effectiveness of the proposed RUC model and efficiency of the proposed computational methodology.