A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F22%3A10250917" target="_blank" >RIV/61989100:27230/22:10250917 - isvavai.cz</a>

Výsledek na webu

<a href="https://mdpi-res.com/d_attachment/electronics/electronics-11-03825/article_deploy/electronics-11-03825.pdf?version=1669022174" target="_blank" >https://mdpi-res.com/d_attachment/electronics/electronics-11-03825/article_deploy/electronics-11-03825.pdf?version=1669022174</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/electronics11223825" target="_blank" >10.3390/electronics11223825</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems

Popis výsledku v původním jazyce

The current research investigates a new and unique Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) algorithm for solving large-scale Optimal Power Flow (OPF) problems of complex power systems, including renewable energy sources and Flexible AC Transmission Systems (FACTS). A recently reported single-objective generalized normal distribution optimization algorithm is transformed into the MOGNDO algorithm using the nondominated sorting and crowding distancing mechanisms. The OPF problem gets even more challenging when sources of renewable energy are integrated into the grid system, which are unreliable and fluctuating. FACTS devices are also being used more frequently in contemporary power networks to assist in reducing network demand and congestion. In this study, a stochastic wind power source was used with different FACTS devices, including a static VAR compensator, a thyristor- driven series compensator, and a thyristor-driven phase shifter, together with an IEEE-30 bus system. Positions and ratings of the FACTS devices can be intended to reduce the system&apos;s overall fuel cost. Weibull probability density curves were used to highlight the stochastic character of the wind energy source. The best compromise solutions were obtained using a fuzzy decision-making approach. The results obtained on a modified IEEE-30 bus system were compared with other well-known optimization algorithms, and the obtained results proved that MOGNDO has improved convergence, diversity, and spread behavior across PFs. (C) 2022 by the authors.

Název v anglickém jazyce

A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems

Popis výsledku anglicky

The current research investigates a new and unique Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) algorithm for solving large-scale Optimal Power Flow (OPF) problems of complex power systems, including renewable energy sources and Flexible AC Transmission Systems (FACTS). A recently reported single-objective generalized normal distribution optimization algorithm is transformed into the MOGNDO algorithm using the nondominated sorting and crowding distancing mechanisms. The OPF problem gets even more challenging when sources of renewable energy are integrated into the grid system, which are unreliable and fluctuating. FACTS devices are also being used more frequently in contemporary power networks to assist in reducing network demand and congestion. In this study, a stochastic wind power source was used with different FACTS devices, including a static VAR compensator, a thyristor- driven series compensator, and a thyristor-driven phase shifter, together with an IEEE-30 bus system. Positions and ratings of the FACTS devices can be intended to reduce the system&apos;s overall fuel cost. Weibull probability density curves were used to highlight the stochastic character of the wind energy source. The best compromise solutions were obtained using a fuzzy decision-making approach. The results obtained on a modified IEEE-30 bus system were compared with other well-known optimization algorithms, and the obtained results proved that MOGNDO has improved convergence, diversity, and spread behavior across PFs. (C) 2022 by the authors.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Electronics

ISSN

2079-9292

e-ISSN

—

Svazek periodika

11

Číslo periodika v rámci svazku

22

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

34

Strana od-do

nestrankovano

Kód UT WoS článku

000887102300001

EID výsledku v databázi Scopus

2-s2.0-85142418821