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Merged
dpinney-nreca merged 1 commit into from
Dec 5, 2025
Merged

Splits do_manual_balance_approach into two functions in accordance wi… #9

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2 changes: 1 addition & 1 deletion Dockerfile
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ RUN apt-get -y update && apt-get install -y python3 git sudo vim python3-pip pyt

# Install the OMF
# Warning: clone might be cached. Consider invalidating manually.
RUN git clone --depth 1 https://github.com/dpinney/omf.git
RUN git clone --depth 1 https://github.com/nreca-bts/omf.git
RUN cd omf; sudo python3 install.py
# Install a compatible version of numpy<2.0.0
RUN pip install numpy==1.26.4
Expand Down
118 changes: 94 additions & 24 deletions microgridup_control.py
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Expand Up @@ -253,7 +253,13 @@ def plot_inrush_data(dssPath, microgrids, out_html, outage_start, outage_end, ou
table_data['Microgrid ID'].append(key)

# # of Interruptions --> Number of times gen drops to zero during sim.
new_dss_tree, new_batt_loadshape, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw = do_manual_balance_approach(outage_start, outage_end, microgrids[key], dssTree, logger)
# new_dss_tree, new_batt_loadshape, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw = do_manual_balance_approach(outage_start, outage_end, microgrids[key], dssTree, logger)
compute_result = compute_manual_balance(outage_start, outage_end, microgrids[key], dssTree, logger)
new_dss_tree = apply_manual_balance_to_tree(compute_result, dssTree, logger) # Need the tree for transformer/load lists below
new_batt_loadshape = list(compute_result['new_batt_loadshape_sliced'])
cumulative_existing_batt_shapes = list(compute_result['cumulative_existing_batt_shapes'])
all_rengen_shapes = list(compute_result['all_rengen_shapes'])
all_loads_shapes_kw = compute_result['all_loads_shapes_kw']
# Stole a few lines from plot_manual_balance_approach().
new_batt_loadshape = list(new_batt_loadshape)
cumulative_existing_batt_shapes = list(cumulative_existing_batt_shapes)
Expand Down Expand Up @@ -421,18 +427,28 @@ def _parse_mult_field(dss_tree, mult_name):
return None
return None

def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, logger):
def compute_manual_balance(outage_start, outage_end, mg_values, dssTree, logger):
'''
Manually constructs battery loadshapes for outage and reinserts into tree based on a proportional to kWh basis.
Returns: (new_dss_tree, new_batt_loadshape_sliced, cumulative_existing_batt_shapes,
all_rengen_shapes, total_surplus, all_loads_shapes_kw)
Given a dssTree (read-only), compute:
- per-hour net load (load - rengen)
- sliced outage battery loadshape (hours outage_start:outage_end)
- cumulative existing battery shapes (full-year)
- all_rengen_shapes (full-year)
- total_surplus list (per outage hour)
- all_loads_shapes_kw (full-year)
- batt_obj (list of battery objects found)
- batt_kwh, batt_kw (scalars)
- batt_obj_loadshape_names (list) to know which mult objects to replace later
No mutating dssTree
Returns a dict (compute_result)
'''
# Validate inputs
gen_bus = mg_values.get('gen_bus')
if not gen_bus:
msg = f"Manual balance: missing gen_bus in microgrid values: {mg_values}"
msg = f'Manual balance: missing gen_bus in microgrid values: {mg_values}'
logger.warning(msg)
raise ValueError(msg)
# First: collect loads and their yearly shapes
# Collect loads and their yearly shapes
all_mg_loads = [
ob for ob in dssTree
if ob.get('object') and ob.get('object').startswith('load.')
Expand All @@ -451,7 +467,7 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
logger.warning(msg)
raise ValueError(msg)
load_shapes.append(arr)
# Ensure consistent length
# Ensure consistent length
lengths = {len(a) for a in load_shapes}
if len(lengths) != 1:
msg = f'Inconsistent loadshape lengths for microgrid {gen_bus}: lengths {lengths}'
Expand All @@ -476,18 +492,18 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
all_rengen_shapes = np.sum(np.vstack(rengen_shapes), axis=0)
else:
all_rengen_shapes = np.zeros_like(all_loads_shapes_kw)
# Third: battery objects at gen_bus
# Battery objects at gen_bus
batt_obj = [
ob for ob in dssTree
if ob.get('bus1', 'x.x').split('.')[0] == gen_bus and 'storage' in ob.get('object', '')
]
# Keep deterministic ordering like original
# Deterministic ordering (small to large)
batt_obj.sort(key=lambda x: float(x.get('kwhrated', 0.0)))
batt_kws = [float(ob.get('kwrated', 0.0)) for ob in batt_obj]
batt_kwhs = [float(ob.get('kwhrated', 0.0)) for ob in batt_obj]
batt_kw = sum(batt_kws)
batt_kwh = sum(batt_kwhs)
# Net (load - rengen)
# Net (load - rengen) (full-year)
new_batt_loadshape = all_loads_shapes_kw - all_rengen_shapes
# Validate outage window
if outage_start < 0 or outage_end > len(new_batt_loadshape) or outage_end <= outage_start:
Expand All @@ -497,14 +513,16 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
new_batt_loadshape_sliced = new_batt_loadshape[outage_start:outage_end].astype(float)
# Cumulative existing battery shapes
cumulative_existing_batt_shapes = np.zeros(len(new_batt_loadshape))
batt_obj_loadshape_names = []
for ob in batt_obj:
batt_shape_name = ob.get('yearly')
arr = _parse_mult_field(dssTree, batt_shape_name) if batt_shape_name else None
if arr is None:
logger.warning(f"Missing battery yearly shape for {ob.get('object')}; treating as zeros.")
arr = np.zeros_like(cumulative_existing_batt_shapes)
cumulative_existing_batt_shapes = cumulative_existing_batt_shapes + arr
# Starting capacity
batt_obj_loadshape_names.append(batt_shape_name)
# Starting capacity and battery simulation over outage slice
try:
starting_capacity = batt_kwh + float(np.sum(cumulative_existing_batt_shapes[:outage_start]))
except Exception:
Expand All @@ -521,7 +539,7 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
except Exception:
batt_kwh = 0.0
battery_available_kwh = float(starting_capacity)
# Work on a copy
# Work on a copy of the outage slice
new_shape_arr = np.array(new_batt_loadshape_sliced, dtype=float)
for hour_idx in range(len(new_shape_arr)):
net_kw = new_shape_arr[hour_idx] # positive => net load; negative => surplus
Expand All @@ -545,12 +563,41 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
if needed_kwh > actual_discharge_kwh:
unsupported_load_kwh += (needed_kwh - actual_discharge_kwh)
total_surplus.append(surplus_this_hour)
# Assign back
# Assign back final processed outage slice
new_batt_loadshape_sliced = new_shape_arr
# Build new dss tree shallow copy
# Build and return compute_result dict
compute_result = {
'gen_bus': gen_bus,
'outage_start': int(outage_start),
'outage_end': int(outage_end),
'new_batt_loadshape_sliced': new_batt_loadshape_sliced, # numpy array
'cumulative_existing_batt_shapes': cumulative_existing_batt_shapes, # numpy array
'all_rengen_shapes': all_rengen_shapes, # numpy array
'total_surplus': total_surplus, # list
'all_loads_shapes_kw': all_loads_shapes_kw, # numpy array
'batt_obj': batt_obj, # list of battery objects (dicts)
'batt_obj_loadshape_names': batt_obj_loadshape_names, # list of string names
'batt_kwh': batt_kwh,
'batt_kw': batt_kw
}
return compute_result

def apply_manual_balance_to_tree(compute_result, dssTree, logger):
'''
Take the compute_result (from compute_manual_balance) and return a new_dss_tree where battery 'mult' entries for batt_obj_loadshape_names have been patched to include the outage slice values computed in compute_manual_balance().
Does not modify the input dssTree in place — returns a shallow copy with the modified entries.
'''
outage_start = compute_result['outage_start']
outage_end = compute_result['outage_end']
new_batt_loadshape_sliced = compute_result['new_batt_loadshape_sliced']
batt_obj = compute_result['batt_obj']
batt_obj_loadshape_names = compute_result['batt_obj_loadshape_names']
batt_kwh = compute_result['batt_kwh']
# Shallow copy the tree (copy each dict)
new_dss_tree = [dict(ob) for ob in dssTree]
if batt_kwh > 0 and len(batt_obj) > 0:
for batt_ob in batt_obj:
# Iterate the batt_obj same order as compute()
for batt_ob, batt_shape_name in zip(batt_obj, batt_obj_loadshape_names):
try:
this_kwhr = float(batt_ob.get('kwhrated', 0.0))
this_kw = float(batt_ob.get('kwrated', 0.0))
Expand All @@ -559,18 +606,18 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
per_unit_outage_shape = (new_batt_loadshape_sliced * factor) / this_kw
else:
per_unit_outage_shape = np.zeros_like(new_batt_loadshape_sliced)
batt_loadshape_name = batt_ob.get('yearly')
# Find the matching mult object index in new_dss_tree
found_index = None
for i, t in enumerate(new_dss_tree):
if t.get('object') and batt_loadshape_name in t.get('object'):
if t.get('object') and batt_shape_name in t.get('object'):
found_index = i
break
if found_index is None:
logger.warning(f"Could not find battery loadshape object for {batt_loadshape_name}; skipping replacement.")
logger.warning(f"Could not find battery loadshape object for {batt_shape_name}; skipping replacement.")
continue
full_loadshape_arr = _parse_mult_field(dssTree, batt_loadshape_name)
full_loadshape_arr = _parse_mult_field(dssTree, batt_shape_name)
if full_loadshape_arr is None:
logger.warning(f"Battery loadshape {batt_loadshape_name} missing or unparsable; skipping.")
logger.warning(f"Battery loadshape {batt_shape_name} missing or unparsable; skipping.")
continue
full_loadshape_list = full_loadshape_arr.tolist()
if outage_end > len(full_loadshape_list):
Expand All @@ -580,11 +627,27 @@ def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, log
end_idx = outage_end
new_outage_vals = per_unit_outage_shape.tolist()
full_loadshape_list[outage_start:end_idx] = new_outage_vals[:end_idx - outage_start]
# Store back without spaces
new_dss_tree[found_index]['mult'] = str(full_loadshape_list).replace(' ', '')
except Exception as e:
logger.warning(f"Error updating battery loadshape for {batt_ob.get('object', '<unknown>')}: {e}")
# Final return (matching original signature)
return new_dss_tree, new_batt_loadshape_sliced, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw
return new_dss_tree

def do_manual_balance_approach(outage_start, outage_end, mg_values, dssTree, logger):
'''
Backwards-compatible wrapper: compute -> apply -> return tuple
Keeps callers unaffected while separating implementation
'''
compute_result = compute_manual_balance(outage_start, outage_end, mg_values, dssTree, logger)
new_dss_tree = apply_manual_balance_to_tree(compute_result, dssTree, logger)
return (
new_dss_tree,
compute_result['new_batt_loadshape_sliced'],
compute_result['cumulative_existing_batt_shapes'],
compute_result['all_rengen_shapes'],
compute_result['total_surplus'],
compute_result['all_loads_shapes_kw']
)

def plot_manual_balance_approach(mg_key, year, outage_start, outage_end, outage_length, new_batt_loadshape, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw):
# Creates plot of manually constructed battery activity, load, and renewable generation (all cumulative).
Expand Down Expand Up @@ -1650,7 +1713,14 @@ def play(data, outage_start, outage_length, logger):
else:
manual_balance_approach = True
# Manually construct battery loadshapes for outage.
new_dss_tree, new_batt_loadshape, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw = do_manual_balance_approach(outage_start, outage_end, mg, dssTree, logger)
# new_dss_tree, new_batt_loadshape, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw = do_manual_balance_approach(outage_start, outage_end, mg, dssTree, logger)
compute_result = compute_manual_balance(outage_start, outage_end, mg, dssTree, logger)
new_dss_tree = apply_manual_balance_to_tree(compute_result, dssTree, logger)
new_batt_loadshape = compute_result['new_batt_loadshape_sliced']
cumulative_existing_batt_shapes = compute_result['cumulative_existing_batt_shapes']
all_rengen_shapes = compute_result['all_rengen_shapes']
total_surplus = compute_result['total_surplus']
all_loads_shapes_kw = compute_result['all_loads_shapes_kw']
# Manual Balance Approach plotting call.
if manual_balance_approach == True:
fname = plot_manual_balance_approach(mg_name, 2019, outage_start, outage_end, outage_length, new_batt_loadshape, cumulative_existing_batt_shapes, all_rengen_shapes, total_surplus, all_loads_shapes_kw)
Expand Down
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