def runopp_map(ssp, link_table, **kwargs):
"""
Run OPF in pandapower using ``pp.runopp()`` and map results back to ANDES
based on the link table.
Parameters
----------
ssp : pandapower network
The pandapower network
link_table : DataFrame
The link table of ADNES system
Returns
-------
DataFrame
The DataFrame contains the OPF results with columns ``p_mw``,
``q_mvar``, ``vm_pu`` in p.u., and the corresponding ``idx`` of
``StaticGen``, ``Exciter``, ``TurbineGov`` in ANDES.
Notes
-----
- The pandapower net and the ANDES system must have same base MVA.
- Multiple ``DG`` connected to the same ``StaticGen`` will be converted to one generator.
The power is dispatched to each ``DG`` by the power ratio ``gammap``
"""
try:
pp.runopp(ssp, **kwargs)
except Exception:
pp.rundcopp(ssp, **kwargs)
logger.warning("ACOPF failed, DCOPF is used instead.")
# take dispatch results from pp
ssp_gen = ssp.gen.rename(columns={'name': 'stg_idx'})
ssp_res = pd.concat(
[ssp_gen[['stg_idx']], ssp.res_gen[['p_mw', 'q_mvar', 'vm_pu']]],
axis=1)
ssp_res = pd.merge(left=ssp_res,
right=ssp_gen[['stg_idx', 'controllable']],
how='left',
on='stg_idx')
ssp_res = pd.merge(left=ssp_res,
right=link_table,
how='left',
on='stg_idx')
ssp_res['p'] = ssp_res['p_mw'] * ssp_res['gammap'] / ssp.sn_mva
ssp_res['q'] = ssp_res['q_mvar'] * ssp_res['gammaq'] / ssp.sn_mva
col = [
'stg_idx', 'p', 'q', 'vm_pu', 'bus_idx', 'controllable', 'dg_idx',
'rg_idx', 'syg_idx', 'gov_idx', 'exc_idx'
]
return ssp_res[col]
def _sumPF_ppn(ppn):
"""Summarize PF results of a pandapower net"""
rg = pd.DataFrame()
rg['gen'] = ppn.res_gen['p_mw']
rg['bus'] = ppn.gen['bus']
rg = rg.groupby('bus').sum()
rg.reset_index(inplace=True)
rd = pd.DataFrame()
rd['demand'] = ppn.res_load['p_mw']
rd['bus'] = ppn.load['bus']
rd = rd.groupby('bus').sum()
rd.reset_index(inplace=True)
rp = pd.DataFrame()
rp['bus'] = ppn.bus.index
rp = pd.merge(rp, rg, how='left', on='bus')
rp = pd.merge(rp, rd, how='left', on='bus')
rp.fillna(0, inplace=True)
rp['ngen'] = rp['gen'] - rp['demand']
return rp
def _to_pp_gen_pre(ssa):
"""Create generator data in pandapower net"""
# build StaticGen df
stg_cols = ['idx', 'u', 'bus', 'v0', 'vmax', 'vmin']
stg_calc_cols = ['p0', 'q0', 'pmax', 'pmin', 'qmax', 'qmin']
ssa_stg = build_group_table(ssa, 'StaticGen', stg_cols + stg_calc_cols)
ssa_stg['name'] = ssa_stg.idx
ssa_stg.rename(inplace=True,
columns={
"bus": "bus_idx",
"u": "stg_u",
"idx": "stg_idx"
})
# retrieve Bus idx in pp net
ssa_busn = ssa.Bus.as_df().copy().reset_index()[["uid", "idx"
]].rename(columns={
"uid": "pp_bus",
"idx": "bus_idx"
})
ssa_stg = pd.merge(ssa_stg, ssa_busn, how="left", on="bus_idx")
return ssa_stg
def make_link_table(ssa):
"""
Build the link table for generators and generator controllers in an ADNES
System, including ``SynGen`` and ``DG`` for now.
Parameters
----------
ssa : andes.system.System
The ADNES system to link
Returns
-------
DataFrame
Each column in the output Dataframe contains the ``idx`` of linked
``StaticGen``, ``Bus``, ``DG``, ``SynGen``, ``Exciter``, and ``TurbineGov``,
``gammap``, ``gammaq``.
"""
# build StaticGen df
ssa_stg = build_group_table(ssa, 'StaticGen', ['u', 'name', 'idx', 'bus'])
# build TurbineGov df
ssa_gov = build_group_table(ssa, 'TurbineGov', ['idx', 'syn'])
# build Exciter df
ssa_exc = build_group_table(ssa, 'Exciter', ['idx', 'syn'])
# build SynGen df
ssa_syg = build_group_table(ssa, 'SynGen',
['idx', 'bus', 'gen', 'gammap', 'gammaq'],
['GENCLS', 'GENROU'])
# build DG df
ssa_dg = build_group_table(ssa, 'DG',
['idx', 'bus', 'gen', 'gammap', 'gammaq'])
# output
ssa_bus = ssa.Bus.as_df()[['name', 'idx']]
ssa_key = pd.merge(
left=ssa_stg.rename(columns={
'name': 'stg_name',
'idx': 'stg_idx',
'bus': 'bus_idx',
'u': 'stg_u'
}),
right=ssa_bus.rename(columns={
'name': 'bus_name',
'idx': 'bus_idx'
}),
how='left',
on='bus_idx')
ssa_syg = pd.merge(left=ssa_key,
how='right',
on='stg_idx',
right=ssa_syg.rename(columns={
'idx': 'syg_idx',
'gen': 'stg_idx'
}))
ssa_dg = pd.merge(left=ssa_key,
how='right',
on='stg_idx',
right=ssa_dg.rename(columns={
'idx': 'dg_idx',
'gen': 'stg_idx'
}))
# TODO: Add RenGen
ssa_key = pd.concat([ssa_syg, ssa_dg], axis=0)
ssa_key = pd.merge(left=ssa_key,
right=ssa_exc.rename(columns={
'idx': 'exc_idx',
'syn': 'syg_idx'
}),
how='left',
on='syg_idx')
ssa_key = pd.merge(left=ssa_key,
right=ssa_gov.rename(columns={
'idx': 'gov_idx',
'syn': 'syg_idx'
}),
how='left',
on='syg_idx')
cols = [
'stg_name', 'stg_u', 'stg_idx', 'bus_idx', 'dg_idx', 'syg_idx',
'exc_idx', 'gov_idx', 'bus_name', 'gammap', 'gammaq'
]
return ssa_key[cols]
def make_link_table(ssa):
"""
Build the link table for generators and generator controllers in an ADNES
System, including ``SynGen`` and ``DG`` for now.
Parameters
----------
ssa : andes.system.System
The ADNES system to link
Returns
-------
DataFrame
Each column in the output Dataframe contains the ``idx`` of linked
``StaticGen``, ``Bus``, ``DG``, ``RenGen``, ``RenExciter``, ``SynGen``,
``Exciter``, and ``TurbineGov``, ``gammap``, ``gammaq``.
"""
# build StaticGen df
ssa_stg = build_group_table(ssa, 'StaticGen', ['u', 'name', 'idx', 'bus'])
# build TurbineGov df
ssa_gov = build_group_table(ssa, 'TurbineGov', ['idx', 'syn'])
# build Exciter df
ssa_exc = build_group_table(ssa, 'Exciter', ['idx', 'syn'])
# build SynGen df
ssa_syg = build_group_table(ssa, 'SynGen',
['idx', 'bus', 'gen', 'gammap', 'gammaq'],
['GENCLS', 'GENROU'])
# build DG df
ssa_dg = build_group_table(ssa, 'DG',
['idx', 'bus', 'gen', 'gammap', 'gammaq'])
# build RenGen df
ssa_rg = build_group_table(ssa, 'RenGen',
['idx', 'bus', 'gen', 'gammap', 'gammaq'])
# build RenExciter df
ssa_rexc = build_group_table(ssa, 'RenExciter', ['idx', 'reg'])
# output
ssa_bus = ssa.Bus.as_df()[['name', 'idx']]
ssa_key = pd.merge(
left=ssa_stg.rename(columns={
'name': 'stg_name',
'idx': 'stg_idx',
'bus': 'bus_idx',
'u': 'stg_u'
}),
right=ssa_bus.rename(columns={
'name': 'bus_name',
'idx': 'bus_idx'
}),
how='left',
on='bus_idx')
ssa_syg = pd.merge(left=ssa_key,
how='right',
on='stg_idx',
right=ssa_syg.rename(columns={
'idx': 'syg_idx',
'gen': 'stg_idx'
}))
ssa_dg = pd.merge(left=ssa_key,
how='right',
on='stg_idx',
right=ssa_dg.rename(columns={
'idx': 'dg_idx',
'gen': 'stg_idx'
}))
ssa_rg = pd.merge(left=ssa_key,
how='right',
on='stg_idx',
right=ssa_rg.rename(columns={
'idx': 'rg_idx',
'gen': 'stg_idx'
}))
ssa_key0 = pd.merge(left=ssa_key,
how='left',
on='stg_idx',
right=ssa_syg[['stg_idx', 'syg_idx']])
ssa_key0 = pd.merge(left=ssa_key0,
how='left',
on='stg_idx',
right=ssa_dg[['stg_idx', 'dg_idx']])
ssa_key0 = pd.merge(left=ssa_key0,
how='left',
on='stg_idx',
right=ssa_rg[['stg_idx', 'rg_idx']])
ssa_key0.fillna(False, inplace=True)
ssa_key0['dyr'] = ssa_key0['syg_idx'].astype(bool) + ssa_key0[
'dg_idx'].astype(bool) + ssa_key0['rg_idx'].astype(bool)
ssa_key0['dyr'] = 1 - ssa_key0['dyr'].astype(int)
ssa_key0['dyr'] = ssa_key0['dyr'].astype(bool)
ssa_dyr0 = ssa_key0[ssa_key0.dyr].drop(['dyr'], axis=1)
ssa_dyr0['gammap'] = 1
ssa_dyr0['gammaq'] = 1
ssa_key = pd.concat([ssa_syg, ssa_dg, ssa_rg, ssa_dyr0], axis=0)
ssa_key = pd.merge(left=ssa_key,
right=ssa_exc.rename(columns={
'idx': 'exc_idx',
'syn': 'syg_idx'
}),
how='left',
on='syg_idx')
ssa_key = pd.merge(left=ssa_key,
right=ssa_gov.rename(columns={
'idx': 'gov_idx',
'syn': 'syg_idx'
}),
how='left',
on='syg_idx')
ssa_key = pd.merge(left=ssa_key,
how='left',
on='rg_idx',
right=ssa_rexc.rename(columns={
'idx': 'rexc_idx',
'reg': 'rg_idx'
}))
cols = [
'stg_name', 'stg_u', 'stg_idx', 'bus_idx', 'dg_idx', 'rg_idx',
'rexc_idx', 'syg_idx', 'exc_idx', 'gov_idx', 'bus_name', 'gammap',
'gammaq'
]
return ssa_key[cols].reset_index(drop=True)