Subtle Influence of the Weibull Shape Parameter on Homer Optimization Space of a Wind Diesel Hybrid Gen Set for Use in Southern Brazil

Abstract

Wind power is an increasingly important alternative for obtaining energy supplies, both in large interconnected power systems and in smaller hybrid systems and even in backup systems. The temporal and spatial variability of the winds represent an obstacle to be overcome so that wind energy can be increasingly used. The capacity factor of wind farms shows how this variability impacts the operation of the plants and its value is of the order of 30% to 35%. The variability of the wind speed is influenced if the point of interest is on land or on sea, the shape of the surface, the proximity of water bodies, among other factors. The availability of wind is best described by the Weibull probability distribution, which has as one of its defining parameters one which is termed as shape parameter. This parameter is much higher as higher is the variability of the wind speed. This paper studies the subtle influence of Weibull shape parameter on the optimal combination of components in a wind diesel hybrid system, by means of computer simulations with the well known software Homer. The results indicate a relatively small influence (as expected) in the studied system, which appears particularly when the cost of diesel is higher and the availability of wind is lower.

Review on probabilistic forecasting of wind power generation

“…De estas, la distribución Weibull se usa con gran frecuencia por adaptarse fácilmente a los datos al requerir dos parámetros numéricos denominados de forma y escala que representan la velocidad media del viento y la desviación estándar respectivamente (Benevit et al, 2016;Cherif & Belhadj, 2014). Henao et al (2019) en su estudio de optimización de la inserción de renovables en el sector eléctrico colombiano estimó la generación eólica partiendo de la dependencia que está tiene con las características de la ubicación y las técnicas de las turbinas instaladas.…”

Dataset after Seven Years Simulating Hybrid Energy Systems with Homer Legacy

“…Among the other case studies, the first three of them (Silva, Cardoso & Beluco, 2012;Beluco & Ponticelli, 2014;Beluco et al, 2013) deal with the insertion of PV modules and-or other components or new fuels into previously existing diesel hybrid systems and the fourth (Benevit et al, 2016) of them studies the subtle influence of different wind energy availability profiles on the performance of a wind diesel hybrid system.…”

“…80, 360 optimization values and 108 sensitivity values, results presented byBenevit et al (2016);  #07-benevit-et-al-2016-210.hmr -a wind diesel hybrid system with energy storage in batteries, simulated with Weibull shape parameter equal to 2.10, 360 optimization values and 108 sensitivity values, results presented by Benevit et al (2016);  #07-benevit-et-al-2016-240.hmr -a wind diesel hybrid system with energy storage in batteries, simulated with Weibull shape parameter equal to 2.40, 360 optimization values and 108 sensitivity values, results presented by Benevit et al (2016);  #07-benevit-et-al-2016-270.hmr -a wind diesel hybrid system with energy storage in batteries, simulated with Weibull shape parameter equal to 2.70, 360 optimization values and 108 sensitivity values, results presented by Benevit et al (2016);  #07-benevit-et-al-2016-300.hmr -a wind diesel hybrid system with energy storage in batteries, simulated with Weibull shape parameter equal to 3.00, 360 optimization values and 108 sensitivity values, results presented by Benevit et al (2016);  #08-canales-et-al-2017.hmr -a wind hydro hybrid system with energy storage in the reservoir of the hydropower plant, 224 optimization values and 72 sensitivity values, results presented by Canales, Beluco & Mendes (2017);  #09-silva-beluco-2018.hmr -a PV wind diesel hybrid system connected to the grid, includ-ing an ocean wave power plant, 512 optimization values and 450 sensitivity values, results presented by Silva & Beluco (2018);  #10-during-et-al-2018-d000.hmr -a PV hydro hybrid system with energy storage capacity in batteries, with time-complementarity index equal to 0.00, 1476 optimization values and 87 sensitivity values, results presented by During F o . et al (2018); #10-during-et-al-2018-d090.hmr -a PV hydro hybrid system with energy storage capacity…”