HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems

This paper presents the Hybrid Renewable Energy System (HYRES), a powerful tool to contribute to the viability analysis of energy systems involving renewable generators. HYRES considers various input parameters related to climatic conditions, statistical reliability, and economic views; in addition...

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Published inEnergies (Basel) Vol. 13; no. 1; p. 26
Main Authors Donado, Katheryn, Navarro, Loraine, Quintero M., Christian G., Pardo, Mauricio
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2020
Subjects
Alternative energy sources
Climatic conditions
Configurations
Design optimization
Distributed generation
Energy
Energy storage
Feasibility studies
Generators
Genetic algorithms
Linear programming
Multiple objective analysis
Net present value
Optimization
Optimization techniques
Power supply
Random variables
Renewable resources
Software
Solar energy
Statistical analysis
Storage units
Systems design
User needs
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Abstract This paper presents the Hybrid Renewable Energy System (HYRES), a powerful tool to contribute to the viability analysis of energy systems involving renewable generators. HYRES considers various input parameters related to climatic conditions, statistical reliability, and economic views; in addition to offering multi-objective optimizations using Genetic Algorithms (GAs) that have a better cost-benefit ratio than mono-objective optimization, which is the technique used in several commercial systems like HOMER, a worldwide leader in microgrid modeling. The use of intelligent techniques in HYRES allows optimal sizing of hybrid renewable systems with wind and solar energy generators adapted to different conditions and case studies. The elements that affect the system design like buying and selling energy from/to the grid and the use of storage units can be included in system configuration according to the need. Optimization approaches are selectable and include Initial Cost, Life Cycle Cost, Loss of Power Probability, and Loss of Power Supply Probability.
AbstractList This paper presents the Hybrid Renewable Energy System (HYRES), a powerful tool to contribute to the viability analysis of energy systems involving renewable generators. HYRES considers various input parameters related to climatic conditions, statistical reliability, and economic views; in addition to offering multi-objective optimizations using Genetic Algorithms (GAs) that have a better cost-benefit ratio than mono-objective optimization, which is the technique used in several commercial systems like HOMER, a worldwide leader in microgrid modeling. The use of intelligent techniques in HYRES allows optimal sizing of hybrid renewable systems with wind and solar energy generators adapted to different conditions and case studies. The elements that affect the system design like buying and selling energy from/to the grid and the use of storage units can be included in system configuration according to the need. Optimization approaches are selectable and include Initial Cost, Life Cycle Cost, Loss of Power Probability, and Loss of Power Supply Probability.
Author Navarro, Loraine
Pardo, Mauricio
Donado, Katheryn
Quintero M., Christian G.
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  surname: Quintero M.
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  givenname: Mauricio
  orcidid: 0000-0002-7608-3290
  surname: Pardo
  fullname: Pardo, Mauricio
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StartPage 26
SubjectTerms Alternative energy sources
Climatic conditions
Configurations
Design optimization
Distributed generation
Energy
Energy storage
Feasibility studies
Generators
Genetic algorithms
Linear programming
Multiple objective analysis
Net present value
Optimization
Optimization techniques
Power supply
Random variables
Renewable resources
Software
Solar energy
Statistical analysis
Storage units
Systems design
User needs
Title HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems
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