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The storage state equation def_storage_state (and an upcoming PR #52 for demand side management) assume(s) that time step labels are numeric and allow for arithmetic operations like:
def def_storage_state_rule(m, t, sit, sto, com):
return (m.e_sto_con[t, sit, sto, com] ==
m.e_sto_con[t-1, sit, sto, com]
However, nothing in the input prevents time steps to have textual or (in future preferably) datetime type. The code should be changed to remove that assumption.
Find out how to idiomatically rewrite the code
Roll out change
Document it (could be the stem for a future contributor's guide doc/contributing.rst)
The text was updated successfully, but these errors were encountered:
A new numeric, "timestep indexer" pyomo.Set can be introduced such as: m.timestepsnum = range(1,len(timesteps)) m.tnum= pyomo.Set(initialize=m.timestepsnum,ordered=True)
and then the required storage/DSM rules and corresponding pyomo variables such as m.e_sto_con can be defined over m.tnum rather than m.tm, regardless of the input timesteps are numeric or not?
This first needs a minimal prototype that examines which "ripple" effects a change of t = [1, 2, 3, ...] to t = [2001-01-01 00:00, 2001-01-01 01:00, ...] would have on the different model steps:
data I/O (guess: positive)
model generation (between 'no effect' to 'one more abstraction layer necessary' everything seems possible. Time step weights w and m.dt must be derived and could possibly change per time step. Or not, then this should trigger warnings/errors.)
plotting (guess: automagic labelling of x-axis ticks)
The storage state equation
def_storage_state
(and an upcoming PR #52 for demand side management) assume(s) that time step labels are numeric and allow for arithmetic operations like:However, nothing in the input prevents time steps to have textual or (in future preferably) datetime type. The code should be changed to remove that assumption.
doc/contributing.rst
)The text was updated successfully, but these errors were encountered: