2019
DOI: 10.3390/en13010026
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HYRES: A Multi-Objective Optimization Tool for Proper Configuration of Renewable Hybrid Energy Systems

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, … Show more

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Cited by 23 publications
(14 citation statements)
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“…The introduction of WT in the HRES located in Germany and the Czech Republic is favorable, especially for higher latitudes [15]. A multi-objective optimization tool, named HYRES (Hybrid Renewable Energy System) is presented in [16], showing better results than the HOMER software. A study in Taiwan demonstrates that the HRES is a more ecological solution, but the use of WT is not economically reasonable [17].…”
Section: Sizing Of Hybrid Systems For General Applicationmentioning
confidence: 99%
“…The introduction of WT in the HRES located in Germany and the Czech Republic is favorable, especially for higher latitudes [15]. A multi-objective optimization tool, named HYRES (Hybrid Renewable Energy System) is presented in [16], showing better results than the HOMER software. A study in Taiwan demonstrates that the HRES is a more ecological solution, but the use of WT is not economically reasonable [17].…”
Section: Sizing Of Hybrid Systems For General Applicationmentioning
confidence: 99%
“…Jia et al (2019)proposed a two-layer optimized configuration method that considers economy and efficiency in the distribution network, and based on this, realized short-term operation optimization layout, making the optimized configuration method more in line with actual operating conditions. Donado et al (2019) used genetic algorithms to optimize for multiple objectives such as climate and economy, taking into account factors such as initial cost, life cycle cost, and probability loss of power supply to achieve the optimal capacity allocation of renewable energy systems.…”
Section: Energy Storage Technology and Capacity Allocation Strategymentioning
confidence: 99%
“…The development of an approach that integrates a genetic algorithm (GA) and a dynamic programming (DP) algorithm was proposed. In addition, the authors of [41][42][43] were oriented towards the implementation of mathematical models for the optimal sizing of hybrid renewable energy systems that satisfy the energy needs in load sectors. The main objective of these studies was to minimize the total cost of generation and the cost of energy using different optimization approaches.…”
Section: Related Workmentioning
confidence: 99%