Merge pull request #108 from CURENT/develop

Prep for v0.9.13

README.md

@@ -1,10 +1,11 @@
 # LTB AMS
 
-Python Software for Power System Scheduling Modeling and Co-Simulation with Dynanic, serving as the market simulator for the [CURENT Largescale Testbed][LTB Repository].
+Python Software for Power System Scheduling Modeling and Co-Simulation with Dynamics, serving as the market simulator for the [CURENT Largescale Testbed][LTB Repository].
 
 [![License: GPL-3.0](https://img.shields.io/badge/License-GPL--3.0-blue.svg)](https://github.com/CURENT/ams/blob/master/LICENSE)
 ![platforms](https://anaconda.org/conda-forge/ltbams/badges/platforms.svg)
 [![Python Versions](https://img.shields.io/badge/Python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue)](https://www.python.org/)
+[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
 ![Repo Size](https://img.shields.io/github/repo-size/CURENT/ams)
 [![GitHub last commit (master)](https://img.shields.io/github/last-commit/CURENT/ams/master?label=last%20commit%20to%20master)](https://github.com/CURENT/ams/commits/master/)
 [![GitHub last commit (develop)](https://img.shields.io/github/last-commit/CURENT/ams/develop?label=last%20commit%20to%20develop)](https://github.com/CURENT/ams/commits/develop/)
@@ -31,6 +32,10 @@ Python Software for Power System Scheduling Modeling and Co-Simulation with Dyna
 With the built-in interface with ANDES, AMS enables **Dynamics Incorporated**
 **Stability-Constrained Scheduling**.
 
+This package can be helpful for power system engineers, researchers, and students
+who need to conduct scheduling studies and transient stability studies at given
+operating points.
+
 AMS is a **Modeling Framework** that provides a descriptive way to formulate
 scheduling problems. The optimization problems are then handled by **CVXPY**
 and solved with third-party solvers.
@@ -67,6 +72,7 @@ Use the following resources to get involved.
 - Version **0.9.9** has known issues and has been yanked from PyPI
 - `kvxopt` is recommended to install via `conda` as sometimes ``pip`` struggles to set the correct path for compiled libraries
 - `cvxpy` versions **below 1.5** are incompatible with `numpy` versions **2.0 and above**
+- If solver `SCIP` run into import error, try to reinstall its Python interface by running `pip install pyscipopt --no-binary scip --force`
 
 AMS is released as ``ltbams`` on PyPI and conda-forge.
 Install from PyPI using pip:
@@ -89,15 +95,22 @@ pip install git+https://github.com/CURENT/ams.git
 
 # Example Usage
 
-Using AMS to run a Real-Time Economic Dispatch (RTED) simulation:
-
 ```python
 import ams
 
-ss = ams.load(ams.get_case('ieee14_uced.xlsx'))
-ss.RTED.run()
+ss = ams.load(ams.get_case('ieee14/ieee14_uced.xlsx'))
+
+# solve RTED
+ss.RTED.run(solver='CLARABEL')
+
+ss.RTED.pg.v
+>>> array([1.8743862, 0.3226138, 0.01     , 0.02     , 0.01     ])
 
-print(ss.RTED.pg.v)
+# convert to ANDES case
+sa = ss.to_andes(addfile=andes.get_case('ieee14/ieee14_full.xlsx'),
+                 setup=True, verify=False)
+sa
+>>> <andes.system.System at 0x14bd98190>
 ```
 
 # Sponsors and Contributors

ams/interface.py

@@ -78,7 +78,6 @@ def sync_adsys(amsys, adsys):
                 ad_mdl.set(src=param, attr='v', idx=idx,
                            value=am_mdl.get(src=param, attr='v', idx=idx))
             except Exception:
-                logger.debug(f"Skip updating {mname}.{param}")
                 continue
     return True
 
@@ -333,6 +332,27 @@ def parse_addfile(adsys, amsys, addfile):
                 df[idxn] = df[idxn].replace(idx_map[mdl_guess])
                 logger.debug(f'Adjust {idxp.class_name} <{name}.{idxp.name}>')
 
+    # NOTE: Group TimedEvent needs special treatment
+    # adjust Toggle and Fault models
+    toggle_df = df_models.get('Toggle') or df_models.get('Toggler')
+    if toggle_df is not None:
+        toggle_df['dev'] = toggle_df.apply(replace_dev, axis=1,
+                                           mdl='model', dev='dev',
+                                           idx_map=idx_map)
+
+    alter_df = df_models.get('Alter')
+    if alter_df is not None:
+        alter_df['dev'] = alter_df.apply(replace_dev, axis=1,
+                                         mdl='model', dev='dev',
+                                         idx_map=idx_map)
+
+    # adjust Fault model
+    fault_df = df_models.get('Fault')
+    if fault_df is not None:
+        fault_df['bus'] = fault_df.apply(replace_dev, axis=1,
+                                         mdl='bus', dev='bus',
+                                         idx_map=idx_map)
+
     # add dynamic models
     for name, df in df_models.items():
         # drop rows that all nan
@@ -966,7 +986,7 @@ def make_link_table(adsys):
                         right=ssa_rg[['stg_idx', 'rg_idx']])
 
     # NOTE: use this instead of fillna to avoid type conversion
-    idxc = ['stg_idx', 'syg_idx', 'dg_idx', 'rg_idx']
+    idxc = ['syg_idx', 'dg_idx', 'rg_idx']
     ssa_key0[idxc] = ssa_key0[idxc].astype('str').replace({'nan': ''}).astype('bool')
 
     dyr = ssa_key0['syg_idx'] + ssa_key0['dg_idx'] + ssa_key0['rg_idx']
@@ -1037,3 +1057,27 @@ def verify_pf(amsys, adsys, tol=1e-3):
         logger.warning(msg)
         logger.warning(diff_msg)
     return check
+
+
+def replace_dev(row, mdl, dev, idx_map):
+    """
+    Replace the device idx in the row based on the idx_map.
+
+    Parameters
+    ----------
+    row : pd.Series
+        The row of the DataFrame.
+    mdl : str
+        The column name for the Model.
+    dev : str
+        The column name for the Device idx.
+    idx_map : dict
+        The index map for replacement.
+
+    Returns
+    -------
+    str
+        The new device idx.
+    """
+    old_idx = row[dev]
+    return idx_map.get(row[mdl], {}).get(old_idx, old_idx)