Economic dispatch using particle swarm optimization: A review

Mahor, Amita; Prasad, Vishnu; Rangnekar, Saroj

doi:10.1016/j.rser.2009.03.007

Cited by 199 publications

(96 citation statements)

References 40 publications

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“…There are several methods to solve ED, and more recent methods, such as GA, PSO, evolutionary programming, tabu search, NN, and ant colony optimization have been increasingly explored and show better results than traditional methods, such as LR, nonlinear programming, or dynamic programming. The aforementioned methodologies have their advantages and disadvantages, but PSO has been the method that has attracted the most attention as the best tool to solve these problems [29].…”

Section: Literature Reviewmentioning

confidence: 99%

Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

et al. 2018

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Insular power systems represent an asset and an excellent starting point for the development and analysis of innovative tools and technologies. The integration of renewable energy resources that has taken place in several islands in the south of Europe, particularly in Portugal, has brought more uncertainty to production management. In this work, an innovative scheduling model is proposed, which considers the integration of wind and solar resources in an insular power system in Portugal, with a strong conventional generation basis. This study aims to show the benefits of increasing the integration of renewable energy resources in this insular power system, and the objectives are related to minimizing the time for which conventional generation is in operation, maximizing profits, reducing production costs, and consequently, reducing greenhouse gas emissions.

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Section: Literature Reviewmentioning

confidence: 99%

Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

et al. 2018

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“…Em 1995, inspirado no comportamento social constatado em variadas espécies de pássaros, cardumes de peixes e enxames de insetos, a heurística Otimização por Enxame de Partículas (PSO) foi apresentada por James Kennedy e Russell Elberhart [4].…”

Section: Otimização Por Enxame De Partículasunclassified

“…Quando o sistema analisado possui muitas unidades geradoras, geralmente se torna muito trabalhoso resolvê-lo utilizando o método tradicional dos multiplicadores de Lagrange (MML) [7]. Nestes casos, estão sendo muito utilizados heurísticas bioinspiradas, que apresentam como diferencial sua fácil implementação e eficiência [4,6]. Heurísticas bastante utilizadas ná area de Engenharia são a otimização por enxame de partículas (PSO) [4] e otimização por enxame de vaga-lumes (AF) [8].…”

Section: Introductionunclassified

Resolução de um Problema de Despacho Econômico de Carga utilizando Enxames de Partículas e Vaga-lumes

Santos¹,

Kapelinski²,

Santos³

et al. 2018

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Resumo. O objetivo deste trabalhoé resolver um problema de despacho econômico de carga considerando quinze unidades geradoras termoelétricas, perdas nas linhas de transmissão e limites máximos e mínimos de geração para cada geradora. Para tanto, serão utilizadas as heurísticas otimização por enxame de partículas (PSO) e de vaga-lumes (FA), e os resultados comparados com a solução obtida via método dos multiplicadores de Lagrange (MML). Como principal resultado, obteve-se que a melhor solução obtida pelo FA foi muito mais precisa do que a obtida pelo PSO, quando comparados com o MML, embora a um custo computacional consideravelmente maior.Palavras-chave. Despacho Econômico de Carga, Otimização por Enxame de Partículas, Otimização por Enxame de Vaga-lumes, Multiplicadores de Lagrange. IntroduçãoO despacho econômico de carga (DE) consiste em um problema de otimização restrito não-linear onde se deseja alocar a carga demandada pelo sistema elétrico de potência nas unidades geradoras, de modo a alcançar o menor custo total de geração [3]. Quando o sistema analisado possui muitas unidades geradoras, geralmente se torna muito trabalhoso resolvê-lo utilizando o método tradicional dos multiplicadores de Lagrange (MML) [7]. Nestes casos, estão sendo muito utilizados heurísticas bioinspiradas, que apresentam como diferencial sua fácil implementação e eficiência [4,6]. Heurísticas bastante utilizadas ná area de Engenharia são a otimização por enxame de partículas (PSO) [4] e otimização por enxame de vaga-lumes (AF) [8].

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“…In the tertiary control level, economic dispatch (ED) [12,13] is responsible for minimize the total operation cost of the MG. In general, according to the predicted generation and load information, the ED algorithm can update the schedules every 5 min or longer [14].…”

Section: Introductionmentioning

confidence: 99%

Fully distributed optimal automatic generation control for an islanded microgrids

Zang

Zeng

et al. 2016

2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

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Abstract-Microgrids (MGs) have been receiving more and more attention, as it can environmentally and reliably integrate intermittent renewable energy sources (RES). Conventionally, an islanded MG is controlled and optimized in a hierarchical strategy, i.e., primary droop control, second automatic generation control (AGC), and tertiary economic dispatch (ED). ED has large time-scale while AGC has small time-scale. Thus the gap between ED and AGC may decrease the economic efficiency of a MG. In this paper, a distributed optimal automatic generation control (OAGC) algorithm is proposed to integrate the gap between ED and AGC, i.e., the MG can realize AGC and ED at the same time. In order to implement the OAGC algorithm, each DG is assigned with an agent and the agents only require the local measurements and communicate with its neighbors. The proposed OAGC algorithm is fully distributed, which involves low costs related to modify the architecture of a MG and robust against single point failure. Simulation results demonstrate the effectiveness of the proposed algorithm.Index Terms--distributed algorithm, droop control, Microgrid, multi-agent system (MAS), optimal automatic generation control (OAGC).

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Economic dispatch using particle swarm optimization: A review

Cited by 199 publications

References 40 publications

Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

Resolução de um Problema de Despacho Econômico de Carga utilizando Enxames de Partículas e Vaga-lumes

Fully distributed optimal automatic generation control for an islanded microgrids

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