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This is an exhaustive list of test ideas/suggestions that could be implemented prepared by @dhungelgd
Test rand_total_time_of_use:
Test when the randomised time is lesser than the sum of all the total spaces available in the windows
Test when the randomised time is greater than the sum of all the total spaces available in the windows (should return – randomised time = sum of the available time spaces within all the windows)
Test_switch_on:
Test for num_windows = 1, 2 and 3 windows separately
For num_windows = 1
Test if the switch on is within the random window 1
For num_windows = 2
Test if the switch on falls within the boundaries of randomised windows 1 & 2
For num_windows = 3
Test if the switch on falls within the boundaries of randomised windows 1 & 2 &3
Test calc_indexes_for_rand_switch_on:
Test for the upper limit value when
The difference between the switch ons is greater than the func_cycle value
The difference between the switch ons is lesser than the func_cycle value ( i.e there is an overlap between two switch ons)
There are no other switch-on events after the current one
Test for the indexes value when upper limit is greater than func_cycle
Test for index when the upper limit is less than the func_cycle value of the appliance
Test calc_coincident_switch_on:
Test when self.fixed = yes – i.e all the apps are switched on together (should return the total number of apps)
Test when self.fixed= no and the index value lies in peak_time_range (test whether the coincidence values are normally distributed or not)
Test when self.fixed = no and the index value lies in off peak time (test whether the coincidence values are uniformly distributed or not)
Test update_daily_use:
Test when evaluate (mean of the indexes) is within 1st duty cycle
Test when evaluate (mean of the indexes) is within 2nd duty cycle
Test when evaluate (mean of the indexes) is within 3rd duty cycle
Test for the case where no duty cycles are specified
Test calc_rand_window:
Check that the window boundaries are within the random_var
Test overflow
Check for window behaviour when the input time is greater than the sum of the time space available within the windows
Also for when func_time < sum of the available time spaces in all windows
Test for different values of r_w
Test assign_random_cycles:
Test when fixed_cycle = 1
Test for number of fixed_cycle = 2
Test for number of fixed_cycle = 3
Test that the new power values assigned to each cycles are within the range of the thermal_P_var
Test generate_load_profile:
Test for indexes is None
Test maximum_profile:
Test that maximum_profile == App.daily_use * np.mean (App.power) * App.number
Test generate_single_load_profile:
Test for different occassional use
Test for different weekend weekday behaviour
Test for different pref_index
Test for flat appliances – test that if an app is flat, the power is calculated without further stochasticity
Test for non-flat appliances
Test generate_aggregate_load_profile:
Test the value of aggregated load for all users
Test calc_peak_time_range:
Test user with single app with single window of one point (or more)
Then test for peak_enlarge = 0
And peak_enlarge = 0.15
The text was updated successfully, but these errors were encountered:
This is an exhaustive list of test ideas/suggestions that could be implemented prepared by @dhungelgd
Test rand_total_time_of_use:
Test_switch_on:
For num_windows = 1
For num_windows = 2
For num_windows = 3
Test calc_indexes_for_rand_switch_on:
The difference between the switch ons is greater than the func_cycle value
The difference between the switch ons is lesser than the func_cycle value ( i.e there is an overlap between two switch ons)
There are no other switch-on events after the current one
Test calc_coincident_switch_on:
Test update_daily_use:
Test calc_rand_window:
Check that the window boundaries are within the random_var
Check for window behaviour when the input time is greater than the sum of the time space available within the windows
Also for when func_time < sum of the available time spaces in all windows
Test for different values of r_w
Test assign_random_cycles:
Test that the new power values assigned to each cycles are within the range of the thermal_P_var
Test generate_load_profile:
Test maximum_profile:
Test generate_single_load_profile:
Test for flat appliances – test that if an app is flat, the power is calculated without further stochasticity
Test generate_aggregate_load_profile:
Test calc_peak_time_range:
Then test for peak_enlarge = 0
And peak_enlarge = 0.15
The text was updated successfully, but these errors were encountered: