Coverage for agentlib_flexquant/data_structures/globals.py: 100%

1"""Script containing global variables""" 

2 

3from typing import Literal 

4 

5# fixed string definitions 

6PREP_TIME = "prep_time" 

7MARKET_TIME = "market_time" 

8FLEX_EVENT_DURATION = "flex_event_duration" 

9PROFILE_DEVIATION_WEIGHT = "profile_deviation_weight" 

10PROFILE_COMFORT_WEIGHT = "profile_comfort_weight" 

11TIME_STEP = "time_step" 

12PREDICTION_HORIZON = "prediction_horizon" 

13FLEXIBILITY_OFFER = "FlexibilityOffer" 

14LINEAR = 'linear' 

15CONSTANT = 'constant' 

16COLLOCATION = 'collocation' 

17INTEGRATION_METHOD = Literal[LINEAR, CONSTANT] 

18FlexibilityDirections = Literal["positive", "negative"] 

19POWER_ALIAS_BASE = "_P_el_base" 

20POWER_ALIAS_NEG = "_P_el_neg" 

21POWER_ALIAS_POS = "_P_el_pos" 

22STORED_ENERGY_ALIAS_BASE = "_E_stored_base" 

23STORED_ENERGY_ALIAS_NEG = "_E_stored_neg" 

24STORED_ENERGY_ALIAS_POS = "_E_stored_pos" 

25full_trajectory_suffix: str = "_full" 

26full_trajectory_prefix: str = "_" 

27shadow_suffix: str = "_shadow" 

28COLLOCATION_TIME_GRID = 'collocation_time_grid' 

29 

30# cost function in the shadow mpc. obj_std and obj_flex are to be evaluated according 

31# to user definition 

32SHADOW_MPC_COST_FUNCTION = ( 

33 "return ca.if_else(self.time < self.prep_time.sym + " 

34 "self.market_time.sym, obj_std, ca.if_else(self.time < " 

35 "(self.prep_time.sym + self.flex_event_duration.sym + " 

36 "self.market_time.sym), obj_flex, obj_std))" 

37) 

38 

39 

40def return_baseline_cost_function(power_variable: str, comfort_variable: str) -> str: 

41 """Return baseline cost function 

42 

43 Args: 

44 power_variable: name of the power variable 

45 comfort_variable: name of the comfort variable 

46 

47 Returns: 

48 Cost function in the baseline mpc, obj_std is to be evaluated according to 

49 user definition 

50 

51 """ 

52 if comfort_variable: 

53 cost_func = ( 

54 "return ca.if_else(self.in_provision.sym, " 

55 "ca.if_else(self.time < self.rel_start.sym, obj_std, " 

56 "ca.if_else(self.time >= self.rel_end.sym, obj_std, " 

57 f"sum([self.profile_deviation_weight*(self.{power_variable} - " 

58 f"self._P_external)**2, " 

59 f"self.{comfort_variable}**2 * self.profile_comfort_weight]))),obj_std)" 

60 ) 

61 else: 

62 cost_func = ( 

63 "return ca.if_else(self.in_provision.sym, " 

64 "ca.if_else(self.time < self.rel_start.sym, obj_std, " 

65 "ca.if_else(self.time >= self.rel_end.sym, obj_std, " 

66 f"sum([self.profile_deviation_weight*(self.{power_variable} - " 

67 f"self._P_external)**2]))),obj_std)" 

68 ) 

69 return cost_func