len(env.state_series()) different than env.observation_space.high.shape[0]

[Alfonso00MA]

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• python version: Python 3.10.13
• python-microgrid version: python-microgrid==1.4.1

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Question

• Question:

  I have been following the "Quick Start" section in the docs:

small_battery = BatteryModule(min_capacity=10,
                              max_capacity=100,
                              max_charge=50,
                              max_discharge=50,
                              efficiency=0.9,
                              init_soc=0.2)

large_battery = BatteryModule(min_capacity=10,
                              max_capacity=1000,
                              max_charge=10,
                              max_discharge=10,
                              efficiency=0.7,
                              init_soc=0.2)

load_ts = 100+100*np.random.rand(24*90) # random load data in the range [100, 200].
pv_ts = 200*np.random.rand(24*90) # random pv data in the range [0, 200].

load = LoadModule(time_series=load_ts)

pv = RenewableModule(time_series=pv_ts)

grid_ts = [0.2, 0.1, 0.5] * np.ones((24*90, 3))

grid = GridModule(max_import=100,
                  max_export=100,
                  time_series=grid_ts)

modules = [
    small_battery,
    large_battery,
    ('pv', pv),
    load,
    grid]

microgrid = Microgrid(modules)

Finally I created a discrete env with the following command:

env = DiscreteMicrogridEnv.from_microgrid(microgrid)

But I noticed the following assertion is not being satisfied. Contrary to what I expected:

assert(len(env.state_series()) == env.observation_space.high.shape[0])

However, the same assertion is satisfied in all the benchmark microgrids:

for i in range(25):
    env = DiscreteMicrogridEnv.from_scenario(microgrid_number=i)
    assert(len(env.state_series()) == env.observation_space.high.shape[0])

Is that the expected behauviour? I am not sure if it should be reported as a bug or not. Any clarification will be appreciated