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.
Highlights
Power balance between sources and loads rules the behavior of any energy power system where equilibrium is essential for proper operation
This paper presents a system oriented to dimensioning hybrid renewable energy systems with solar photovoltaic and wind resources
The proposed system contributes with powerful tools to perform the optimization of renewable hybrid systems, through the use of genetic algorithms, which as shown, are algorithms highly used for this type of study due to their adaptive properties
Summary
Power balance between sources and loads rules the behavior of any energy power system where equilibrium is essential for proper operation. The system design procedure must be based on the prediction of the renewable energy resources data; the selection and sizing of the system components is optimized to trade-off system operation and investment costs. Sinha and Chandel [3] and Khare et al [4] present a review of hybrid solar grid-connected systems where depending on the optimization technique, different accuracy and system configuration/operation time are obtained. Faccio et al [11] present a review of recent works on optimal design of hybrid renewable energy systems. Recent reviews on optimization techniques applied in the design of hybrid renewable energy systems [13] present a general trend in analyzing, classifying, and developing novel algorithms according to their ability to handle high-dimension variable spaces [14,15]. All Tfuhtuusr,ethvaelfluoeswacrheatratkiesnustoedprtoesceanltcuvlaaltueet,haendyetahres yfoerartlhyeoruettpuurntsoanreintvakesetnmteonotb. tFaoinr tahNisPpVurepqousael, allofrulteusrsethvaanluzeesraor.e taken to present value, and the yearly outputs are taken to obtain a NPV equal or less than zero
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