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- # -*- coding: utf-8 -*-
- """
- Estimating the viability of a drone delivery business
- """
- import numpy as np
- pi = np.pi
- #City variables:
- pop = 750000 #number of inhabitants
- period = 4 #number of days between consecutive orders for household/medicine supplies
- area = 140 #number of square kilometers of the urban area of the city
- price_kwh = 0.2237 #price of 1 kWh in the city
- work_day = 12 #hours available for delivery
- k = 0.15 #fraction of people in the city that actually use the delivery service
- #Drone variables:
- autonomy = 30 #autonomy of the drone in minutes
- speed = 50 #average speed of the drone in km/h
- bat_charge = 6000 #batery charge in mAh
- bat_tension = 14.8 #voltage of the battery
- bat_time = 1 #hours to fully charge battery
- price_drone = 1000 #price of 1 drone
- #Consequences of city variables:
- radius = (area/pi)**0.5 #city approximated to a circle - radius in km
- mean_distance = (2/3) * radius #average distance from a point to the center of the city (km)
- dialy_demand = (pop*k)/period #number of deliveries needed in 1 day
- #Consequences of drone variables:
- bat_energy = bat_charge * bat_tension/1000000 #energy of 1 full charge in kWh
- max_distance = 0.5 * speed * (autonomy/60) #maximum distance the delivery site can be from the center (km)
- #Consequences of both drone and city:
- avg_delivery_time = 2*mean_distance/speed #average delivery time in hours
- del_p_opcy = max_distance/mean_distance #deliveries per operation cycle
- op_cycle = del_p_opcy*(avg_delivery_time)+bat_time #hours per operation cycle (between two charges)
- bat_price = bat_energy * price_kwh #price to charge 1 drone once
- del_per_day = (work_day/op_cycle) * del_p_opcy #deliveries a drone makes, on average, in one day
- energy_per_day = del_per_day * bat_energy #kwh spent per day per drone
- price_per_day = energy_per_day * price_kwh #money spent on charging the drone in one day
- drones_needed = dialy_demand/del_per_day
- energy_expense = price_per_day * drones_needed #total money spent on energy spent in 1 day
- drone_expense = price_drone * drones_needed
- time_to_break_even = 10 #days
- # drone_expense + time*energy_expense = price_charged * time * (pop * k/period)
- min_price_charged = (drone_expense + time_to_break_even*energy_expense)/(time_to_break_even * (pop * k/period))
- print("You need to charge at least", min_price_charged, "per delivery.")
- actual_price_charged = 7.9
- time_company = 150 #number of days of operation
- profit = (pop * k/period*time_company) - (drone_expense + time_company*energy_expense)
- average_profit = profit/time_company
- print("The total profit of the undertaking would be", profit, ", and the average profit would be", average_profit, "per day.")
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