MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H2 system incorporating demand response

César Y. Acevedo-Arenas; Antonio Correcher; Carlos Sánchez-Díaz; Eduardo Ariza; David Alfonso-Solar; Carlos Vargas-Salgado; Johann F. Petit-Suárez

doi:10.1016/j.enconman.2019.02.044

MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H₂ system incorporating demand response

César Y. Acevedo-Arenas, Antonio Correcher, Carlos Sánchez-Díaz, Eduardo Ariza, David Alfonso-Solar, Carlos Vargas-Salgado, Johann F. Petit-Suárez

Ingeniería en Energía

Resultado de la investigación: Artículos / Notas › Artículo Científico › revisión exhaustiva

38 Citas (Scopus)

Resumen

A Model Predictive Control (MPC) strategy based on the Evolutionary Algorithms (EA) is proposed for the optimal dispatch of renewable generation units and demand response in a grid-tied hybrid system. The generating system is based on the experimental setup installed in a Distributed Energy Resources Laboratory (LabDER), which includes an AC micro-grid with small scale PV/Wind/Biomass systems. Energy storage is by lead-acid batteries and an H2 system (electrolyzer, H2 cylinders and Fuel Cell). The energy demand is residential in nature, consisting of a base load plus others that can be disconnected or moved to other times of the day within a demand response program. Based on the experimental data from each of the LabDER renewable generation and storage systems, a micro-grid operating model was developed in MATLAB

Idioma original	Inglés
Páginas (desde-hasta)	241-257
Número de páginas	17
Publicación	Energy Conversion and Management
Volumen	186
DOI	https://doi.org/10.1016/j.enconman.2019.02.044
Estado	Publicada - 15 abr. 2019

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1016/j.enconman.2019.02.044

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title = "MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H2 system incorporating demand response",

abstract = "A Model Predictive Control (MPC) strategy based on the Evolutionary Algorithms (EA) is proposed for the optimal dispatch of renewable generation units and demand response in a grid-tied hybrid system. The generating system is based on the experimental setup installed in a Distributed Energy Resources Laboratory (LabDER), which includes an AC micro-grid with small scale PV/Wind/Biomass systems. Energy storage is by lead-acid batteries and an H2 system (electrolyzer, H2 cylinders and Fuel Cell). The energy demand is residential in nature, consisting of a base load plus others that can be disconnected or moved to other times of the day within a demand response program. Based on the experimental data from each of the LabDER renewable generation and storage systems, a micro-grid operating model was developed in MATLAB",

keywords = "Genetic algorithm, Hybrid energy systems, Micro-grids, Model predictive control",

author = "Acevedo-Arenas, {C{\'e}sar Y.} and Antonio Correcher and Carlos S{\'a}nchez-D{\'i}az and Eduardo Ariza and David Alfonso-Solar and Carlos Vargas-Salgado and Petit-Su{\'a}rez, {Johann F.}",

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AU - Acevedo-Arenas, César Y.

AU - Correcher, Antonio

AU - Sánchez-Díaz, Carlos

AU - Ariza, Eduardo

AU - Alfonso-Solar, David

AU - Vargas-Salgado, Carlos

AU - Petit-Suárez, Johann F.

PY - 2019/4/15

Y1 - 2019/4/15

N2 - A Model Predictive Control (MPC) strategy based on the Evolutionary Algorithms (EA) is proposed for the optimal dispatch of renewable generation units and demand response in a grid-tied hybrid system. The generating system is based on the experimental setup installed in a Distributed Energy Resources Laboratory (LabDER), which includes an AC micro-grid with small scale PV/Wind/Biomass systems. Energy storage is by lead-acid batteries and an H2 system (electrolyzer, H2 cylinders and Fuel Cell). The energy demand is residential in nature, consisting of a base load plus others that can be disconnected or moved to other times of the day within a demand response program. Based on the experimental data from each of the LabDER renewable generation and storage systems, a micro-grid operating model was developed in MATLAB

AB - A Model Predictive Control (MPC) strategy based on the Evolutionary Algorithms (EA) is proposed for the optimal dispatch of renewable generation units and demand response in a grid-tied hybrid system. The generating system is based on the experimental setup installed in a Distributed Energy Resources Laboratory (LabDER), which includes an AC micro-grid with small scale PV/Wind/Biomass systems. Energy storage is by lead-acid batteries and an H2 system (electrolyzer, H2 cylinders and Fuel Cell). The energy demand is residential in nature, consisting of a base load plus others that can be disconnected or moved to other times of the day within a demand response program. Based on the experimental data from each of the LabDER renewable generation and storage systems, a micro-grid operating model was developed in MATLAB

KW - Genetic algorithm

KW - Hybrid energy systems

KW - Micro-grids

KW - Model predictive control

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DO - 10.1016/j.enconman.2019.02.044

M3 - Artículo Científico

AN - SCOPUS:85062266439

SN - 0196-8904

VL - 186

SP - 241

EP - 257

JO - Energy Conversion and Management

JF - Energy Conversion and Management

ER -