Constraining StorageUnit duration of charge

[Anas Abuzayed]

Dear PyPSa Community,

I am trying to model a battery using storage unit, where whatever is being charged at time x, should maximum be completely discharged at e.g., time x+3.

My initial thought was to create a constraint and accessing time x+3 using the SHIFT command as in here (https://github.com/PyPSA/PyPSA/blob/2f2181ad030cbf56dba1f93ae5ba81ded55da96e/pypsa/optimization/constraints.py#L135),

but didn't work well with me. Here's a minimal example to reproduce my network

Also, when I create the model (n.optimize.create_model()) after the storage unit is added, I keep getting a ValueError: coordinate '_term' not present in all datasets.

Any thoughts on this are appreciated.

Best,

Anas

import pypsa
from pypsa.optimization.compat import get_var, linexpr, define_constraints

days=365
load=[39,37,36,35,34,33,32,33,
      36,38,42,44,43,43,44,47,
      50,51,50,48,47,47,43,40]*days

p_max_pu=[0,0,0,0,0.003,0.252,0.499,0.655,
          0.735,0.761,0.734,0.651,0.504,
          0.277,0.022,0,0,0,0,0,0,0,0,0]*days

n = pypsa.Network()
n.set_snapshots(range(len(load)))
n.add("Bus", "bus0")
n.add("Load", "load", bus="bus0", p_set=load)
n.add("Generator","bus0 RES",bus="bus0",
      p_max_pu=p_max_pu,marginal_cost = 0.1,
      capital_cost=68565,p_nom_extendable=True
      )
n.add("Generator","bus0 CCGT",
      bus="bus0",marginal_cost = 80,
      capital_cost=94469,p_nom_extendable=True
           )

n.add("StorageUnit","bus0 Battery",bus="bus0",
            capital_cost=40000,p_nom_extendable=True
           )

n.optimize.create_model()

var_d=get_var(n, "StorageUnit", "p_dispatch").loc[:, 'bus0 Battery']
var_s=get_var(n, "StorageUnit", "p_store").loc[:, 'bus0 Battery'].shift(snapshot=3)

lhs = linexpr((1, var_d))-linexpr((1, var_s))
rhs= 0

define_constraints(n, lhs, "=", rhs, 'StorageUnit', '3_hour')

n.lopf(solver_name='gurobi')

StorageUnit  p_dispatch p_store
0                0.000000      0.000000
1                0.000000      0.000000
2                0.000000      7.427140
3                7.427140      0.000000
4                0.000000      0.000000
5                0.000000      0.000000
6                0.000000      0.000000
7                0.000000      9.004008
8                0.000000     11.134269
9                0.000000     10.801603
10               0.000000      5.070140
11               2.252505      0.000000
12              10.679359      0.000000
13               0.000000     12.093902
14               0.000000      0.837962
15               3.572860      0.000000
16               6.572860      0.000000
17               7.572860      0.000000
18               6.572860      0.000000
19               4.572860      0.000000
20               3.572860      0.000000
21               3.572860      0.000000
22               0.000000      0.000000
23               0.000000      0.000000