Merge pull request #36 from grgmiller/pyomo_update

Pyomo update (Fixes #25)

CHANGELOG.md

@@ -1,3 +1,22 @@
+-------------------------------------------------------------------------------
+Commmit 2021.08.26 (Version 0.2.0)
+-------------------------------------------------------------------------------
+Fixes #25
+Updates the code to work with Pyomo 6.1, from Pyomo 5.6.8, so that the code is compatible with CPLEX as a solver.
+The environment.yml file has been updated to require use of Pyomo>=6.0.0 and pyutilib>=6.0.0, so continued use will require updating your environment. 
+
+Specific updates include:
+ - pyomo elements with "Simple" in their name were renamed to "Scalar"
+ - For any params with string elements, needed to manually specify `within=Any` when defining the param in order to silence a deprecation warning
+ - Needed to manually specify `dimen=1` for Sets that are used to index parameters when loading data
+ - When loading data, you can no longer specify the index as a cross product of multiple sets (e.g. `index=mod.PERIODS*mod.MONTHS`). Instead, they must be specified as a list of Sets (e.g. `index=[mod.PERIODS, mod.MONTHS]`)
+
+Other cleanup included:
+ - when loading data, replaced specifying multiple parameters as tuples with specifying them as lists, to speed the data loading process
+ - Removed `PERIODS_FOR_GEN_BLD_YR`, and `TPS_FOR_GEN_IN_PERIOD` because they are not used in the model
+ - changed the `gen_capacity_value` to `elcc` for Effective Load Carrying Capacity
+
+
 -------------------------------------------------------------------------------
 Commmit 2021.08.11
 -------------------------------------------------------------------------------

environment.yml

@@ -17,9 +17,9 @@ dependencies:
   - pandas
   - pint
   - plotly
-  - pyomo<=5.6.8
+  - pyomo>=6.0.0
   - python>=2.7.12
   - pytz
-  - pyutilib<=5.7.3
+  - pyutilib>=6.0.0
   - requests
   - xlrd

setup.py

@@ -28,12 +28,12 @@ def read(*rnames):
 setup(
     name='switch_model',
     version=__version__,
-    maintainer='Switch Authors',
-    maintainer_email='[email protected]',
+    maintainer='Gregory Miller',
+    maintainer_email='[email protected]',
     url='http://switch-model.org',
     license='Apache License 2.0',
     platforms=["any"],
-    description='Switch Power System Planning Model',
+    description='Switch 24x7 Planning Model',
     long_description=read('README.md'),
     long_description_content_type="text/markdown",
     classifiers=[
@@ -62,11 +62,11 @@ def read(*rnames):
     ],
     python_requires='>=2.7.12',
     install_requires=[
-        'Pyomo>=4.4.1, <=5.6.8', # We need a version that works with glpk 4.60+
+        'Pyomo', # We need a version that works with glpk 4.60+
         'pint',         # needed by Pyomo when we run our tests, but not included
         'testfixtures', # used for standard tests
         'pandas',       # used for input upgrades and testing that functionality
-        'pyutilib <=5.7.3', 
+        'pyutilib', 
     ],
     extras_require={
         # packages used for advanced demand response, progressive hedging

switch_model/balancing/demand_response/simple.py

@@ -102,10 +102,10 @@ def load_inputs(mod, switch_data, inputs_dir):
         optional=True,
         filename=os.path.join(inputs_dir, 'dr_data.csv'),
         autoselect=True,
-        param=(mod.dr_shift_down_limit, mod.dr_shift_up_limit))
+        param=[mod.dr_shift_down_limit, mod.dr_shift_up_limit])
 
     switch_data.load_aug(
         filename=os.path.join(inputs_dir, 'days.csv'),
         select=('timepoint_id','tp_day'),
         index=mod.TIMEPOINTS,
-        param=(mod.tp_day))
+        param=[mod.tp_day])

switch_model/balancing/load_zones.py

@@ -150,7 +150,7 @@ def load_inputs(mod, switch_data, inputs_dir):
         filename=os.path.join(inputs_dir, 'loads.csv'),
         auto_select=True,
         index=mod.ZONE_TIMEPOINTS,
-        param=(mod.zone_demand_mw))
+        param=[mod.zone_demand_mw])
 
 
 def post_solve(instance, outdir):

switch_model/balancing/renewable_target.py

@@ -156,8 +156,7 @@ def load_inputs(mod, switch_data, inputs_dir):
     switch_data.load_aug(
         filename=os.path.join(inputs_dir, 'renewable_target.csv'),
         autoselect=True,
-        index=mod.PERIODS,
-        param=(mod.renewable_target,))
+        param=[mod.renewable_target])
 
     #load inputs which include costs for each timepoint in each zone
     switch_data.load_aug(
@@ -171,7 +170,7 @@ def load_inputs(mod, switch_data, inputs_dir):
         filename=os.path.join(inputs_dir, 'days.csv'),
         select=('timepoint_id','tp_in_subset'),
         index=mod.TIMEPOINTS,
-        param=(mod.tp_in_subset))
+        param=[mod.tp_in_subset])
 
 def post_solve(instance, outdir):
     """

switch_model/energy_sources/properties.py

@@ -91,7 +91,7 @@ def define_components(mod):
     """
 
     mod.NON_FUEL_ENERGY_SOURCES = Set()
-    mod.FUELS = Set()
+    mod.FUELS = Set(dimen=1)
     mod.f_co2_intensity = Param(mod.FUELS, within=NonNegativeReals)
     mod.f_upstream_co2_intensity = Param(
         mod.FUELS, within=Reals, default=0)
@@ -103,7 +103,7 @@ def define_components(mod):
     # ENERGY_SOURCES is the union of fuel and non-fuels sets. Pipe | is
     # the union operator for Pyomo sets.
     mod.ENERGY_SOURCES = Set(
-        initialize=mod.NON_FUEL_ENERGY_SOURCES | mod.FUELS)
+        initialize=mod.NON_FUEL_ENERGY_SOURCES | mod.FUELS, dimen=1)
     mod.min_data_check('ENERGY_SOURCES')
 
 
@@ -145,4 +145,4 @@ def load_inputs(mod, switch_data, inputs_dir):
         filename=os.path.join(inputs_dir, 'fuels.csv'),
         select=('fuel', 'co2_intensity', 'upstream_co2_intensity'),
         index=mod.FUELS,
-        param=(mod.f_co2_intensity, mod.f_upstream_co2_intensity))
+        param=[mod.f_co2_intensity, mod.f_upstream_co2_intensity])

switch_model/explore_model_instance.ipynb

@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "source": [
     "from pathlib import Path\r\n",
     "import pickle\r\n",
@@ -24,7 +24,7 @@
     "import pandas as pd\r\n",
     "\r\n",
     "# specify where the pickle file is located\r\n",
-    "model_path = '../MODEL_RUNS/generic_office_example/outputs/hourly_95/'"
+    "model_path = '../MODEL_RUNS/generic_office_example/outputs/annual_goal/'"
    ],
    "outputs": [],
    "metadata": {}
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "source": [
     "# read instance file\r\n",
     "with open((Path.cwd() / model_path / 'instance.pickle'), mode='rb') as file:\r\n",
@@ -47,6 +47,26 @@
    "outputs": [],
    "metadata": {}
   },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "source": [
+    "len(instance.GENERATION_PROJECTS)"
+   ],
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "9"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 13
+    }
+   ],
+   "metadata": {}
+  },
   {
    "cell_type": "markdown",
    "source": [
@@ -228,24 +248,89 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "source": [
     "# read results file\r\n",
     "with open((Path.cwd() / model_path / 'results.pickle'), 'rb') as file:\r\n",
     "    results = pickle.load(file)\r\n",
     "\r\n",
     "print(results.problem)"
    ],
-   "outputs": [],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "\n",
+      "- Name: unknown\n",
+      "  Lower bound: 726748.0428\n",
+      "  Upper bound: 726748.0428\n",
+      "  Number of objectives: 1\n",
+      "  Number of constraints: 43803\n",
+      "  Number of variables: 35051\n",
+      "  Number of binary variables: <undefined>\n",
+      "  Number of integer variables: <undefined>\n",
+      "  Number of continuous variables: <undefined>\n",
+      "  Number of nonzeros: 17479\n",
+      "  Sense: minimize\n",
+      "\n"
+     ]
+    }
+   ],
    "metadata": {}
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "source": [
     "print(results.solver)"
    ],
-   "outputs": [],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "\n",
+      "- Name: <undefined>\n",
+      "  Status: ok\n",
+      "  Return code: <undefined>\n",
+      "  Message: <undefined>\n",
+      "  User time: -1.0\n",
+      "  System time: 28.21\n",
+      "  Wallclock time: 28.21\n",
+      "  Termination condition: optimal\n",
+      "  Termination message: Model was solved to optimality (subject to tolerances), and an optimal solution is available.\n",
+      "  Statistics: \n",
+      "    Branch and bound: \n",
+      "      Number of bounded subproblems: None\n",
+      "      Number of created subproblems: None\n",
+      "    Black box: \n",
+      "      Number of function evaluations: <undefined>\n",
+      "      Number of gradient evaluations: <undefined>\n",
+      "      Number of iterations: 33511\n",
+      "  Error rc: 0\n",
+      "  Time: 28.228245973587036\n",
+      "\n"
+     ]
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "source": [
+    "print(results.pyomo_solve_time)"
+   ],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "26.032098054885864\n"
+     ]
+    }
+   ],
    "metadata": {}
   },
   {

switch_model/financials.py

@@ -314,7 +314,7 @@ def load_inputs(mod, switch_data, inputs_dir):
     switch_data.load_aug(
         filename=os.path.join(inputs_dir, 'financials.csv'),
         optional=False, auto_select=True,
-        param=(mod.base_financial_year, mod.interest_rate, mod.discount_rate)
+        param=[mod.base_financial_year, mod.interest_rate, mod.discount_rate]
     )
 
 def post_solve(instance, outdir):

switch_model/generate_input_files.py

@@ -116,12 +116,12 @@ def generate_inputs(model_workspace):
 
     # ra_requirement.csv
     xl_ra_req = pd.read_excel(io=model_inputs, sheet_name='RA_requirements').dropna(axis=1, how='all')
-    ra_requirement = xl_ra_req[xl_ra_req['RA_RESOURCE'] != 'flexible_RA']
+    ra_requirement = xl_ra_req.copy()[xl_ra_req['RA_RESOURCE'] != 'flexible_RA']
     ra_requirement['period'] = year
     ra_requirement = ra_requirement[['period','RA_RESOURCE','tp_month','ra_requirement','ra_cost','ra_resell_value']]
 
     # flexible_ra_requirement.csv
-    flexible_ra_requirement = xl_ra_req[xl_ra_req['RA_RESOURCE'] == 'flexible_RA']
+    flexible_ra_requirement = xl_ra_req.copy()[xl_ra_req['RA_RESOURCE'] == 'flexible_RA']
     flexible_ra_requirement['period'] = year
     flexible_ra_requirement = flexible_ra_requirement.drop(columns=['RA_RESOURCE'])
     flexible_ra_requirement = flexible_ra_requirement.rename(columns={'ra_requirement':'flexible_ra_requirement','ra_cost':'flexible_ra_cost', 'ra_resell_value':'flexible_ra_resell_value'})
@@ -130,7 +130,7 @@ def generate_inputs(model_workspace):
     # ra_capacity_value.csv
     ra_capacity_value = pd.read_excel(io=model_inputs, sheet_name='RA_capacity_value').dropna(axis=1, how='all')
     ra_capacity_value['period'] = year
-    ra_capacity_value = ra_capacity_value[['period','gen_energy_source','tp_month','gen_capacity_value']]
+    ra_capacity_value = ra_capacity_value[['period','gen_energy_source','tp_month','elcc']]
 
     # ra_requirement_areas.csv
     ra_requirement_areas = pd.read_excel(io=model_inputs, sheet_name='RA_areas')

switch_model/generators/core/build.py

@@ -214,14 +214,15 @@ def define_components(mod):
     This aggregation is performed for the benefit of the objective function.
 
     """
-    mod.GENERATION_PROJECTS = Set()
+    mod.GENERATION_PROJECTS = Set(dimen=1)
 
-    mod.gen_tech = Param(mod.GENERATION_PROJECTS)
+    mod.gen_tech = Param(mod.GENERATION_PROJECTS, within=Any)
     mod.GENERATION_TECHNOLOGIES = Set(initialize=lambda m:
-        {m.gen_tech[g] for g in m.GENERATION_PROJECTS}
+        {m.gen_tech[g] for g in m.GENERATION_PROJECTS},
+        ordered=False
     )
     mod.gen_energy_source = Param(mod.GENERATION_PROJECTS,
-        validate=lambda m,val,g: val in m.ENERGY_SOURCES or val == "multiple")
+        validate=lambda m,val,g: val in m.ENERGY_SOURCES or val == "multiple", within=Any)
     mod.gen_load_zone = Param(mod.GENERATION_PROJECTS, within=mod.LOAD_ZONES)
     mod.gen_max_age = Param(mod.GENERATION_PROJECTS, within=PositiveIntegers, default=25)
     mod.gen_is_variable = Param(mod.GENERATION_PROJECTS, within=Boolean)
@@ -322,22 +323,15 @@ def gen_build_can_operate_in_period(m, g, build_year, period):
         # mid_period = m.period_start[period] + 0.5 * m.period_length_years[period]
         # return online <= m.period_start[period] and mid_period <= retirement
 
-    # The set of periods when a project built in a certain year will be online
-    mod.PERIODS_FOR_GEN_BLD_YR = Set(
-        mod.GEN_BLD_YRS,
-        within=mod.PERIODS,
-        ordered=True,
-        initialize=lambda m, g, bld_yr: set(
-            period for period in m.PERIODS
-            if gen_build_can_operate_in_period(m, g, bld_yr, period)))
     # The set of build years that could be online in the given period
     # for the given project.
     mod.BLD_YRS_FOR_GEN_PERIOD = Set(
         mod.GENERATION_PROJECTS, mod.PERIODS,
         initialize=lambda m, g, period: set(
             bld_yr for (gen, bld_yr) in m.GEN_BLD_YRS
             if gen == g and
-               gen_build_can_operate_in_period(m, g, bld_yr, period)))
+               gen_build_can_operate_in_period(m, g, bld_yr, period)),
+        ordered=False)
     # The set of periods when a generator is available to run
     mod.PERIODS_FOR_GEN = Set(
         mod.GENERATION_PROJECTS,
@@ -549,13 +543,13 @@ def load_inputs(mod, switch_data, inputs_dir):
         'gen_forced_outage_rate', 'gen_capacity_limit_mw', 'gen_unit_size',
         'gen_min_build_capacity', 'gen_is_cogen', 'gen_variant_group'],
         index=mod.GENERATION_PROJECTS,
-        param=(mod.gen_tech, mod.gen_energy_source,
+        param=[mod.gen_tech, mod.gen_energy_source,
                mod.gen_load_zone, mod.gen_is_variable, mod.gen_is_storage,
                mod.gen_is_baseload, mod.gen_scheduled_outage_rate,
                mod.gen_forced_outage_rate, mod.gen_capacity_limit_mw,
                mod.gen_unit_size, mod.ppa_energy_cost, mod.gen_min_build_capacity,
                mod.ppa_capacity_cost, mod.gen_is_cogen,
-               mod.gen_variant_group, mod.gen_pricing_node))
+               mod.gen_variant_group, mod.gen_pricing_node])
     # Construct sets of capacity-limited, ccs-capable and unit-size-specified
     # projects. These sets include projects for which these parameters have
     # a value
@@ -575,7 +569,7 @@ def load_inputs(mod, switch_data, inputs_dir):
         filename=os.path.join(inputs_dir, 'gen_build_predetermined.csv'),
         auto_select=True,
         index=mod.PREDETERMINED_GEN_BLD_YRS,
-        param=(mod.gen_predetermined_cap))
+        param=[mod.gen_predetermined_cap])
     switch_data.load_aug(
         filename=os.path.join(inputs_dir, 'gen_build_years.csv'),
         set=mod.GEN_BLD_YRS)