Exam (elaborations)
Prácticas de paneles solares y de machine learning
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El documento contiene las prácticas evaluadas relacionadas con los temas de paneles solares y de machine learning.
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X1 0X2 1
X3 9
X4 4
X5 8
X6 8
X7 9
X8 3
Ejercicio 1
TABLA SIN MODIFICACIONES
Objetos uds W h W Wh
lamparas 0 36 8 0 0
nevera 1 110 12 110 1320
televisor 1 900 9 900 8100
Pcs 2 145 1 290 290
microondas 1 480 0.9 480 432
otros 1 800 3.5 800 2800
Potencia real (W) 2580
Consumo real (Wh) 12942
Potencia sobredimensionada (W) 2257.5
Consumo sobredimensionado (Wh) 17212.86
Ejercicio 2: HSP
Irradiación Área cuadrado
Ángulo (kWh/m^2) mes dias Wh/(m^2*día) W/m^2 HSP/día
0 52.93 Diciembre 31 1707.4193548 1000 1.70741935
39 103.41 Enero 31 3335.8064516 1000 3.33580645
Ejercicio 3: Número Paneles
Número de paneles 8.5420773 9
E_panel(J) 779.744758 Consumo 6660.64
P_panel(W) 275
, HSP 3.33580645
ƞ 0.85
Ejercicio 4: Baterias y regulado
como la potencia real obtenida es de 2580W la tensión a la que tienen que trabajar las baterias es de 24 a 48
Días de autonomía 3
Profundidad de descarga 0.6
Ejercicio 5:Regulador
V_bat
V_panel
I_panel_out
I_reg_out
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