Wrapper function to run CRM calculations under option 3, i.e.:
Using the extended model, which takes into account the distribution of bird flight heights at risk height (above the minimum and below the maximum height of the rotor blade)
Using generic flight height distribution data
Usage
crm_opt3(
rotor_grids,
d_y_gen,
rotor_radius,
blade_width,
rotor_speed,
blade_pitch,
flight_type,
wing_span,
flight_speed,
body_lt,
n_blades,
prop_upwind,
avoidance_rate,
flux_factor,
mth_prop_oper,
lac_factor
)Arguments
- rotor_grids
A list object containing geometric attributes of the rotor at equidistant points within its unit circle. This object should be built via the function
generate_rotor_grids().- d_y_gen
a vector with the proportion of birds at height bands within the rotor disc, from a generic flight height distribution
- rotor_radius
Numeric value. The radius of the rotor (\(R\)), in metres.
- blade_width
Numeric value, giving the maximum blade width, in metres.
- rotor_speed
Numeric value. The operational rotation speed, in revolutions/min.
- blade_pitch
Numeric value. The average blade pitch angle, the angle between the blade surface and the rotor plane (\(\gamma\)), in radians.
- flight_type
A character string, either 'flapping' or 'gliding', indicating the species' characteristic flight type.
- wing_span
Numeric value. The wingspan of the bird (\(W\)), in metres.
- flight_speed
Numeric value. The bird flying speed (\(v\)), in metres/sec.
- body_lt
Numeric value. The length of the bird (\(L\)), in metres.
- n_blades
An integer, the number of blades in rotor (\(b\)).
- prop_upwind
Numeric value between 0-1 giving the proportion of flights upwind - defaults to 0.5.
- avoidance_rate
a numeric value within the interval \([0, 1]\). The avoidance rate, expressing the probability that a bird flying on a collision course with a turbine will take evading action to avoid collision.
- flux_factor
a vector containing the flux factor for each month
- mth_prop_oper
A numeric vector, the proportion of time during which turbines are operational per month.
- lac_factor
A numerical value, the large array correction factor. Defaults to 1, meaning large array correction is not applicable.
Examples
rotor_grids <- generate_rotor_grids(yinc = 0.05, xinc = 0.05, chord_prof_5MW)
gen_fhd_dat <- Johnston_Flight_heights_SOSS %>%
dplyr::filter(variable=="Gannet.est") %>%
dplyr::select(height,prop)
gen_fhd <- gen_fhd_dat$prop
gen_fhd_at_rotor <-
get_fhd_rotor(
hub_height = 150,
fhd = gen_fhd,
rotor_radius = 120,
tidal_offset = 2.5,
yinc = 0.05)
flux_fct <- get_flux_factor(
n_turbines = 100,
rotor_radius = 120,
flight_speed = 13.1,
bird_dens = c(1.19,0.85,1.05,1.45,1.41,1.45,1.12,1.45,0.93,0.902,1.06,1.23),
daynight_hrs = Day_Length(52),
noct_activity = 0.5
)
turb_oper <- data.frame(
month = month.abb,
prop_oper = runif(12,0.5,0.8)
)
turb_oper_month <- turb_oper$prop_oper
crm_opt3(
rotor_grids = rotor_grids,
d_y_gen = gen_fhd_at_rotor,
rotor_radius = 120,
blade_width = 5,
rotor_speed = 15,
blade_pitch = 15,
flight_type = "flapping",
wing_span = 1.01,
flight_speed = 13.1,
body_lt = 0.85,
n_blades = 3,
prop_upwind = 0.5,
avoidance_rate = 0.981,
flux_factor = flux_fct,
mth_prop_oper = turb_oper_month,
lac_factor = 0.9998299
)
#> [1] 8.370416 5.865827 9.260779 11.613477 9.729629 12.153394 8.421661
#> [8] 9.799154 8.207087 4.865321 5.302548 6.842424