Short-Term Reliability Evaluation of Generating Systems Using Fixed-Effort Generalized Splitting

TL;DR

This paper introduces a computationally efficient method using fixed-effort generalized splitting and MCMC to evaluate short-term reliability of wind-integrated power systems, accounting for uncertainties.

Contribution

It presents a novel, low-burden approach for short-term reliability assessment that incorporates wind and load uncertainties using FEGS and MCMC techniques.

Findings

Outperforms crude Monte-Carlo in efficiency

Effectively evaluates reliability indices with lower computational cost

Shows impact of wind/load uncertainties on reliability

Abstract

The short-term reliability evaluation techniques provide a rational approach for risk-informed decision making during power system operation. The existing reliability assessment techniques involve large computational burden and therefore are not directly applicable for short-term reliability evaluation during system operation. To this end, this paper presents a computationally-efficient approach for short-term reliability evaluation of wind-integrated generating systems. The proposed approach makes use of the fixed-effort generalized splitting (FEGS) technique, which is a variant of importance splitting. To realize the implementation of FEGS, a discrete version of component-wise Metropolis-Hastings (MH) algorithm for Markov Chain Monte-Carlo (MCMC) is also presented. Besides, the proposed FEGS approach is extended to take the uncertainties of wind generation and load demand into account. The simulation results indicate that, in comparison to crude Monte-Carlo simulation (CMCS), the proposed approach is able to evaluate short-term reliability indices with a low computational burden. Moreover, further simulation results indicate the impacts of uncertainties of wind generation and load demand on short-term reliability indices.