Tolerable random interruption duration based reliability estimation of stand alone hybrid renewable energy system by network reduction and sequential Monte Carlo simulation

  • Atul S. Koshti
  • , Aanchal Verma
  • , Rajesh Arya
  • , Chandrima Roy
  • , Liladhar Arya
  • , Sharat Chandra Choube
  • , Baseem Khan

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This paper presents a novel tolerable random interruption duration (TRID) concept for estimation of reliability indices of stand-alone hybrid renewable energy system (SAHRES) during down time. This concept utilizes the ignorance of interruption duration if it is tolerable in event of failure. It uses a framework using network reduction technique and sequential Monte Carlo simulation (SMCS) suitable for present research whereas the solution in such cases is not feasible with analytical method. Thus reliability indices such as mean up time, mean down time, failure frequency, system failure rate, interruption duration and system unavailability are estimated using SMCS. Modelling aspects are considered for load, capacity, renewable energy system and TRID due to network outage. The impact of considering random tolerable interruption duration has been demonstrated on the reliability indices and case study is presented to show the effect of change of TRID on reliability indices. A sample SAHRES has been considered for the study.

Original languageEnglish
Pages (from-to)4168-4179
Number of pages12
JournalIET Generation, Transmission and Distribution
Volume18
Issue number24
DOIs
Publication statusPublished - Dec 2024
Externally publishedYes

Keywords

  • power system reliability
  • reliability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Tolerable random interruption duration based reliability estimation of stand alone hybrid renewable energy system by network reduction and sequential Monte Carlo simulation'. Together they form a unique fingerprint.

Cite this