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

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

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

Original languageEnglish
Pages (from-to)241-257
Number of pages17
JournalEnergy Conversion and Management
Volume186
DOIs
StatePublished - 15 Apr 2019

Keywords

  • Genetic algorithm
  • Hybrid energy systems
  • Micro-grids
  • Model predictive control

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