Walkthrough of the enflow frameworkο
This guide provides a step-by-step approach to setting up and running a simulation using the enflow library. Follow these steps to create a comprehensive energy resource simulation.
Step 1: Define Your Energy Assetsο
Begin by defining the energy assets in your simulation. This includes any resources, facilities, equipment, or other entities involved in your energy model.
# Define your energy assets
assets = enflow.define_assets(...)
# Add more details specific to your energy assets.
Step 2: Specify Dynamic State Variablesο
Next, outline the dynamic state variables. These are the variables that represent the state of your energy system and will change over time during the simulation.
# Define state variables
state_variables = enflow.define_state(...)
# Provide more specifics about your state variables.
Step 3: Define Action Variablesο
Now, define the action variables. These are the variables that represent the actions or decisions that can be made in your environment.
# Define action variables
actions = enflow.define_actions(...)
# Elaborate on the possible actions in your simulation.
Step 4: Create the Environmentο
Create the simulation environment. This includes defining the transition function, which describes how the state of the system changes in response to actions.
# Create the environment
environment = enflow.create_environment(assets, state_variables, actions)
# Further details on setting up the environment.
Step 5: Establish the Objective Functionο
Define the objective function. This function should quantify the goal of the simulation, such as minimizing costs or maximizing efficiency.
# Define the objective function
objective = enflow.define_objective(...)
# Additional information on your specific objective function.
Step 6: Design Agentsβ Policiesο
Design the policy for your agents. This involves specifying the strategy that the agents will use to make decisions in the environment.
# Design agent policies
agent_policy = enflow.design_policy(...)
# More details on how to design and implement these policies.
Step 7: Run the Simulated Environmentο
Finally, run the simulation with the defined assets, environment, and agent policies. Analyze the output to evaluate the performance of your model.
# Run the simulation
simulation_results = enflow.run_simulation(environment, agent_policy)
# Instructions on how to run and what to expect from the simulation.
Conclusionο
Following these steps will allow you to create a detailed and functional simulation using the enflow library. Explore different configurations and policies to fully understand the capabilities and dynamics of your energy resource model.