Stochastic Real-time Power Dispatch with Large-scale Wind Power Integration and its Analytical solution

TL;DR

This paper introduces an analytical chance-constrained real-time power dispatch model that effectively manages wind power forecast errors using a Cauchy distribution, ensuring system security and operational efficiency.

Contribution

It proposes a novel CCRTD model with an analytical solution based on Cauchy distribution, incorporating dependence among wind farms and an affine control strategy for real-time dispatch.

Findings

Model effectively handles wind forecast errors.

Analytical convex optimization solution derived.

Demonstrates reliability and efficiency in numerical tests.

Abstract

Real-time power dispatch (RTD) can coordinate wind farms, automatic generation control (AGC) units and non AGC units. In RTD, the probable wind power forecast errors (WPFE) should be appropriately formulated to ensure system security with high probability and minimize operational cost. Previous studies and our onsite tests show that Cauchy distribution (CD) effectively fits the leptokurtic feature of small timescale WPFE distributions. In this paper, we propose a chance-constrained real time dispatch (CCRTD) model with the WPFE represented by CD. Since the CD is stable and has promising mathematical characteristics, the proposed CCRTD model can be analytically transformed to a convex optimization problem considering the dependence among wind farms outputs. Moreover, the proposed model incorporates an affine control strategy compatible with AGC systems. This strategy makes the CCRTD adaptively take into account both the additional power ramping requirement and power variation on transmission lines caused by WPFE in RTD stage. Numerical test results show that the proposed method is reliable and effective. Meanwhile it is very efficient and suitable for real-time application.