fixes to ERCOT data issues including line capacities and load forecasts

README.md

@@ -27,10 +27,9 @@ pip install .
 
 The Vatic repository includes the [May 2021 version of the Texas-7k grid dataset](
 https://electricgrids.engr.tamu.edu/electric-grid-test-cases/datasets-for-arpa-e-perform-program/)
-produced by Adam Birchfield et al. at Texas A&M. You can add this dataset to your installation of Vatic (size ~200MB)
-by installing git-lfs, and then running ```cd Vatic; git lfs install; git lfs fetch; git lfs pull```.
-
-You can also download the [RTS-GMLC](https://github.com/GridMod/RTS-GMLC) grid for use with Vatic by running
+produced by [Adam Birchfield et al.](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8423655) at Texas A&M with a
+few modifications (see release notes). You can also download the smaller testing
+[RTS-GMLC](https://github.com/GridMod/RTS-GMLC) grid for use with Vatic by running
 ```cd Vatic; git submodule init; git submodule update; pip install .```.
 
 

setup.py

@@ -4,7 +4,7 @@
 
 setuptools.setup(
     name='Vatic',
-    version='0.3.0-a2',
+    version='0.4.0-a0',
     description='lightweight PJM power grid interface for Egret + Pyomo',
 
     author='Michal Radoslaw Grzadkowski',

vatic/command_line.py

@@ -45,7 +45,7 @@ def run_deterministic():
 
     parser.add_argument(
         '--lmps', action='store_true',
-        help="solve for locational marginal prices after each SCED"
+        help="solve for locational marginal prices after each SCED?"
         )
 
     #TODO: separate mipgaps for RUCs and SCEDs

vatic/data/loaders.py

@@ -916,29 +916,15 @@ def timeseries_cohorts(self):
     @staticmethod
     def get_dispatch_types(renew_types):
         return {
-            'DispatchRenewables': set(),
+            'DispatchRenewables': {gen for gen, gen_type in renew_types.items()
+                                   if gen_type != 'H'},
 
-            'NondispatchRenewables': {gen
-                                      for gen, gen_type in renew_types.items()
-                                      if gen_type != 'H'},
+            'NondispatchRenewables': set(),
 
             'ForecastRenewables': {gen for gen, gen_type in renew_types.items()
                                    if gen_type != 'H'}
             }
 
-    def __init__(self,
-                 init_state_file: Optional[Union[str, Path]] = None,
-                 mins_per_time_period: int = 60) -> None:
-        super().__init__(init_state_file, mins_per_time_period)
-
-        max_min_downtime = max(self.template['MinimumDownTime'].values())
-        for gen, power in self.template['PowerGeneratedT0'].items():
-            if power == 0:
-                self.template['UnitOnT0State'][gen] = -max_min_downtime
-
-        for line in ['A1', 'A2', 'A3', 'A4', 'A5', 'A6']:
-            self.template['ThermalLimit'][line] = 1e4
-
     def map_wind_generators(self, asset_df: pd.DataFrame) -> pd.DataFrame:
         wind_maps = pd.read_csv(Path(self.in_dir, self.grid_dir,
                                      "Texas7k_NREL_wind_map.csv"),