A novel weight-improved particle swarm optimization algorithm for optimal power flow and economic load dispatch problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00176043" target="_blank" >RIV/68407700:21230/10:00176043 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

A novel weight-improved particle swarm optimization algorithm for optimal power flow and economic load dispatch problems

Popis výsledku v původním jazyce

The optimization problems of optimal power flow (OPF) and the economic load dispatch (ELD) with valve-point effects in power systems are recently solved by some types of artificial intelligent (AI) algorithms. In this paper, based on improving the function of weight parameters, we present a novel weight-improved particle swarm optimization (WIPSO) method for computing two above problems. To evaluate the accuracy, convergence speed and applicability of the proposed method, we first compare the OPF results of proposed method to those of traditional particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), ant colony optimization (ACO) methods on the standard IEEE 30-bus system. We second compare our results of ELD problem tothose of classical evolutionary programming (CEP), improved fast evolutionary programming (IFEP), and various improved particle swarm optimization methods on the IEEE 13-unit and 40-unit systems.

Název v anglickém jazyce

A novel weight-improved particle swarm optimization algorithm for optimal power flow and economic load dispatch problems

Popis výsledku anglicky

The optimization problems of optimal power flow (OPF) and the economic load dispatch (ELD) with valve-point effects in power systems are recently solved by some types of artificial intelligent (AI) algorithms. In this paper, based on improving the function of weight parameters, we present a novel weight-improved particle swarm optimization (WIPSO) method for computing two above problems. To evaluate the accuracy, convergence speed and applicability of the proposed method, we first compare the OPF results of proposed method to those of traditional particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), ant colony optimization (ACO) methods on the standard IEEE 30-bus system. We second compare our results of ELD problem tothose of classical evolutionary programming (CEP), improved fast evolutionary programming (IFEP), and various improved particle swarm optimization methods on the IEEE 13-unit and 40-unit systems.

Druh

D - Stať ve sborníku

CEP obor

JE - Nejaderná energetika, spotřeba a užití energie

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název statě ve sborníku

Transmission and Distribution Conference and Exposition, 2010 IEEE PES

ISBN

978-1-4244-6546-0

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

—

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

New Orleans

Datum konání akce

19. 4. 2010

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—