Misc

README.md

@@ -28,7 +28,10 @@ Python Software for Power System Scheduling Modeling and Co-Simulation with Dyna
 
 # Why AMS
 
-With the built-in interface with dynamic simulation engine, ANDES, AMS enables Dynamics Interfaced Stability Constrained Production Cost and Market Operation Modeling.
+With the built-in interface with ANDES, AMS enables **Dynamics Incorporated Stability-Constrained Scheduling**.
+
+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.
 
 AMS produces credible scheduling results and competitive performance.
 The following results show the comparison of DCOPF between AMS and other tools.

ams/__init__.py

@@ -1,6 +1,7 @@
 from . import _version
 __version__ = _version.get_versions()['version']
 
+from ams import opt  # NOQA
 from ams import benchmarks  # NOQA
 
 from ams.main import config_logger, load, run  # NOQA
@@ -10,4 +11,4 @@
 
 __author__ = 'Jining Wang'
 
-__all__ = ['System', 'get_case', 'System']
+__all__ = ['System', 'get_case']

ams/core/documenter.py

@@ -223,9 +223,10 @@
         # add tables
         self.parent.syms.generate_symbols()
         out += self._obj_doc(max_width=max_width, export=export)
-        out += self._constr_doc(max_width=max_width, export=export)
         out += self._expr_doc(max_width=max_width, export=export)
+        out += self._constr_doc(max_width=max_width, export=export)
         out += self._var_doc(max_width=max_width, export=export)
+        out += self._exprc_doc(max_width=max_width, export=export)
         out += self._service_doc(max_width=max_width, export=export)
         out += self._param_doc(max_width=max_width, export=export)
         out += self.config.doc(max_width=max_width, export=export)
@@ -316,17 +317,26 @@
                               rest_dict=rest_dict)
 
     def _expr_doc(self, max_width=78, export='plain'):
-        # expression documentation
+        # Expression documentation
         if len(self.parent.exprs) == 0:
             return ''
 
         # prepare temporary lists
-        names, var_names, info = list(), list(), list()
+        names, info = list(), list()
+        units, sources, units_rest = list(), list(), list()
 
         for p in self.parent.exprs.values():
             names.append(p.name)
-            var_names.append(p.var)
             info.append(p.info if p.info else '')
+            units.append(p.unit if p.unit else '')
+            units_rest.append(f'*{p.unit}*' if p.unit else '')
+
+            slist = []
+            if p.owner is not None and p.src is not None:
+                slist.append(f'{p.owner.class_name}.{p.src}')
+            elif p.owner is not None and p.src is None:
+                slist.append(f'{p.owner.class_name}')
+            sources.append(','.join(slist))
 
         # expressions based on output format
         expressions = []
@@ -342,13 +352,67 @@
         expressions = math_wrap(expressions, export=export)
 
         plain_dict = OrderedDict([('Name', names),
-                                  ('Variable', var_names),
                                   ('Description', info),
+                                  ('Unit', units),
+                                  ])
+        rest_dict = OrderedDict([('Name', names),
+                                 ('Description', info),
+                                 ('Expression', expressions),
+                                 ('Unit', units_rest),
+                                 ('Source', sources),
+                                 ])
+
+        # convert to rows and export as table
+        return make_doc_table(title=title,
+                              max_width=max_width,
+                              export=export,
+                              plain_dict=plain_dict,
+                              rest_dict=rest_dict)
+
+    def _exprc_doc(self, max_width=78, export='plain'):
+        # ExpressionCalc documentation
+        if len(self.parent.exprcs) == 0:
+            return ''
+
+        # prepare temporary lists
+        names, info = list(), list()
+        units, sources, units_rest = list(), list(), list()
+
+        for p in self.parent.exprcs.values():
+            names.append(p.name)
+            info.append(p.info if p.info else '')
+            units.append(p.unit if p.unit else '')
+            units_rest.append(f'*{p.unit}*' if p.unit else '')
+
+            slist = []
+            if p.owner is not None and p.src is not None:
+                slist.append(f'{p.owner.class_name}.{p.src}')
+            elif p.owner is not None and p.src is None:
+                slist.append(f'{p.owner.class_name}')
+            sources.append(','.join(slist))
+
+        # expressions based on output format
+        expressions = []
+        if export == 'rest':
+            for p in self.parent.exprcs.values():
+                expr = _tex_pre(self, p, self.parent.syms.tex_map)
+                logger.debug(f'{p.name} math: {expr}')
+                expressions.append(expr)
+
+            title = 'ExpressionCalcs\n----------------------------------'
+        else:
+            title = 'ExpressionCalcs'
+        expressions = math_wrap(expressions, export=export)
+
+        plain_dict = OrderedDict([('Name', names),
+                                  ('Description', info),
+                                  ('Unit', units),
                                   ])
         rest_dict = OrderedDict([('Name', names),
-                                 ('Variable', var_names),
                                  ('Description', info),
                                  ('Expression', expressions),
+                                 ('Unit', units_rest),
+                                 ('Source', sources),
                                  ])
 
         # convert to rows and export as table
@@ -423,6 +487,8 @@
             slist = []
             if p.owner is not None and p.src is not None:
                 slist.append(f'{p.owner.class_name}.{p.src}')
+            elif p.owner is not None and p.src is None:
+                slist.append(f'{p.owner.class_name}')
             sources.append(','.join(slist))
 
         # symbols based on output format
@@ -490,6 +556,8 @@
             slist = []
             if p.owner is not None and p.src is not None:
                 slist.append(f'{p.owner.class_name}.{p.src}')
+            elif p.owner is not None and p.src is None:
+                slist.append(f'{p.owner.class_name}')
             sources.append(','.join(slist))
 
         # symbols based on output format

ams/core/matprocessor.py

@@ -13,7 +13,7 @@
 from andes.shared import tqdm, tqdm_nb
 from andes.utils.misc import elapsed, is_notebook
 
-from ams.opt.omodel import Param
+from ams.opt import Param
 from ams.shared import pd, sps
 
 logger = logging.getLogger(__name__)
@@ -140,7 +140,9 @@ def class_name(self):
 
 class MatProcessor:
     """
-    Class for matrix processing in AMS system.
+    Class for matrices processing in AMS system.
+    The connectivity matrices `Cft`, `Cg`, `Cl`, and `Csh` ***have taken*** the
+    devices connectivity into account.
 
     The MParams' row names and col names are assigned in `System.setup()`.
     """

ams/core/param.py

@@ -10,7 +10,7 @@
 import numpy as np
 from scipy.sparse import issparse
 
-from ams.opt.omodel import Param
+from ams.opt import Param
 
 logger = logging.getLogger(__name__)
 

ams/core/service.py

@@ -10,7 +10,7 @@
 
 from andes.core.service import BaseService
 
-from ams.opt.omodel import Param
+from ams.opt import Param
 
 
 logger = logging.getLogger(__name__)
@@ -33,8 +33,6 @@ class RBaseService(BaseService, Param):
         Description.
     vtype : Type, optional
         Variable type.
-    model : str, optional
-        Model name.
     no_parse: bool, optional
         True to skip parsing the service.
     sparse: bool, optional
@@ -106,8 +104,8 @@ class ValueService(RBaseService):
         Description.
     vtype : Type, optional
         Variable type.
-    model : str, optional
-        Model name.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -155,8 +153,8 @@ class ROperationService(RBaseService):
         Description.
     vtype : Type, optional
         Variable type.
-    model : str, optional
-        Model name.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -194,6 +192,8 @@ class LoadScale(ROperationService):
         Unit.
     info : str, optional
         Description.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -236,7 +236,7 @@ class NumOp(ROperationService):
 
     Note that the scalar output is converted to a 1D array.
 
-    The optional kwargs are passed to the input function.
+    The `rargs` are passed to the input function.
 
     Parameters
     ----------
@@ -397,8 +397,6 @@ class NumOpDual(NumOp):
         Description.
     vtype : Type, optional
         Variable type.
-    model : str, optional
-        Model name.
     rfun : Callable, optional
         Function to apply to the output of ``fun``.
     rargs : dict, optional
@@ -407,6 +405,8 @@ class NumOpDual(NumOp):
         Expand the dimensions of the output array along a specified axis.
     array_out : bool, optional
         Whether to force the output to be an array.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -467,6 +467,10 @@ class MinDur(NumOpDual):
         Unit.
     info : str, optional
         Description.
+    vtype : Type, optional
+        Variable type.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -537,8 +541,12 @@ class NumHstack(NumOp):
         Description.
     vtype : Type, optional
         Variable type.
-    model : str, optional
-        Model name.
+    rfun : Callable, optional
+        Function to apply to the output of ``fun``.
+    rargs : dict, optional
+        Keyword arguments to pass to ``rfun``.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -624,8 +632,12 @@ class ZonalSum(NumOp):
         Description.
     vtype : Type
         Variable type.
-    model : str
-        Model name.
+    rfun : Callable, optional
+        Function to apply to the output of ``fun``.
+    rargs : dict, optional
+        Keyword arguments to pass to ``rfun``.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -676,7 +688,7 @@ class VarSelect(NumOp):
     A numerical matrix to select a subset of a 2D variable,
     ``u.v[:, idx]``.
 
-    For example, if nned to select Energy Storage output
+    For example, if need to select Energy Storage output
     power from StaticGen `pg`, following definition can be used:
     ```python
     class RTED:
@@ -709,6 +721,8 @@ class RTED:
         Keyword arguments to pass to ``rfun``.
     array_out : bool, optional
         Whether to force the output to be an array.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -801,8 +815,12 @@ class VarReduction(NumOp):
         A description of the operation.
     vtype : Type, optional
         The variable type.
-    model : str, optional
-        The model name associated with the operation.
+    rfun : Callable, optional
+        Function to apply to the output of ``fun``.
+    rargs : dict, optional
+        Keyword arguments to pass to ``rfun``.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """
@@ -818,13 +836,11 @@ def __init__(self,
                  rfun: Callable = None,
                  rargs: dict = None,
                  no_parse: bool = False,
-                 sparse: bool = False,
-                 **kwargs):
+                 sparse: bool = False,):
         super().__init__(name=name, tex_name=tex_name, unit=unit,
                          info=info, vtype=vtype,
                          u=u, fun=None, rfun=rfun, rargs=rargs,
-                         no_parse=no_parse, sparse=sparse,
-                         **kwargs)
+                         no_parse=no_parse, sparse=sparse,)
         self.fun = fun
 
     @property
@@ -859,8 +875,12 @@ class RampSub(NumOp):
         Description.
     vtype : Type
         Variable type.
-    model : str
-        Model name.
+    rfun : Callable, optional
+        Function to apply to the output of ``fun``.
+    rargs : dict, optional
+        Keyword arguments to pass to ``rfun``.
+    no_parse: bool, optional
+        True to skip parsing the service.
     sparse: bool, optional
         True to return output as scipy csr_matrix.
     """