Coverage for examples/SimpleBuilding/main_single_run.py: 95%

1import logging 

2from agentlib_flexquant.generate_flex_agents import FlexAgentGenerator 

3from agentlib.utils.multi_agent_system import LocalMASAgency 

4 

5logging.basicConfig(level=logging.WARN) 

6until = 3600 * 24 

7 

8ENV_CONFIG = {"rt": False, "factor": 0.002, "t_sample": 1} 

9sim_config = "mpc_and_sim/fmu_config.json" 

10mpc_config = "mpc_and_sim/simple_building.json" 

11predictor_config = "predictor/predictor_config.json" 

12flex_config = "flex_configs/flexibility_agent_config.json" 

13 

14def run_example(until=until): 

15 """Runs MAS simulation with specified flex event duration. 

16  

17 mpc_config:  

18 Sets inputs, outputs, states, and parameters for the MPC agent.  

19 It points to the path of the MPC problem definition file (simple_building.py) and defines the MPC parameters. 

20 sim_config:  

21 Sets inputs, outputs, and states for the simulation agent.  

22 It points to the path of the FMU file and defines the simulation parameters. 

23 predictor_config: 

24 Sets parameters for the predictor agent and points to the path of the predictor formulation file (predictor.py). 

25 flex_config: 

26 Sets various options for the flexibility quantification framework:  

27 - characteristic times for the indicator module (e.g. market time, preparation time, flex event duration) 

28 - options for the cost calculation 

29 - whether to use a constant electricity price or to input a time series sent by the predictor agent 

30 - whether to use a constant feed-in tariff or to input a time series sent by the predictor agent 

31 - if no feed-in is required (e.g. for a house without electricity generation), use a constant feed-in tariff with value 0 

32 - option to correct the cost for stored energy at the end of the prediction horizon  

33 - option to include a market config (points to a market config file)  

34 - options for the flexibility agent generator:  

35 - power variable of the baseline agent  

36 - cost functions of PF-MPC and NF-MPC agents, including custom parameters and variables for the shadow MPCs  

37 - general options such as results paths  

38 

39 """ 

40 

41 generator = FlexAgentGenerator( 

42 flex_config=flex_config, mpc_agent_config=mpc_config 

43 ) 

44 

45 config_list = generator.generate_flex_agents() 

46 sim_config_new = generator.adapt_sim_results_path(sim_config, save_name_suffix="_temp") 

47 

48 agent_configs = [sim_config_new, predictor_config] 

49 agent_configs.extend(config_list) 

50 

51 mas = LocalMASAgency( 

52 agent_configs=agent_configs, env=ENV_CONFIG, variable_logging=False 

53 ) 

54 mas.run(until=until) 

55 results = mas.get_results(cleanup=False) 

56 return results 

57 

58 

59if __name__ == "__main__": 

60 # Here the simulation is run once,  

61 # generated files are stored in --> the current working directory 

62 # For an example with multiple runs, see: examples\SimpleBuilding\main_multi_run.py 

63 # For plotting of results generated from this main file,  

64 # see: examples\SimpleBuilding\plot_results_single.py 

65 run_example(until)