initial pass at PTDF extension

examples/uc/ptdf_ext.py

@@ -0,0 +1,246 @@
+# Copyright 2020 by B. Knueven, D. Mildebrath, C. Muir, J-P Watson, and D.L. Woodruff
+# This software is distributed under the 3-clause BSD License.
+
+import pyomo.environ as pyo
+from pyomo.common.collections import ComponentMap, ComponentSet
+from mpisppy.extensions.extension import Extension
+from mpisppy.utils.sputils import is_persistent
+
+import egret.common.lazy_ptdf_utils as lpu
+from egret.models.unit_commitment import (_lazy_ptdf_check_violations,
+                                          _lazy_ptdf_log_terminate_on_violations,
+                                          _lazy_ptdf_warmstart_copy_violations,
+                                          _lazy_ptdf_solve,
+                                          _lazy_ptdf_normal_terminatation,
+                                          _lazy_ptdf_violation_adder,
+                                         )
+import logging
+from egret.common.log import logger
+
+logger.setLevel(logging.ERROR)
+
+class PTDFExtension(Extension):
+    ''' Abstract base class for extensions to general SPBase objects.
+
+        Args:
+            ph (PHBase): The PHBase object for the current model
+    '''
+    def __init__(self, spopt_object, **kwargs):
+        # attach self.opt
+        super().__init__(spopt_object)
+
+        self.pre_lp_iteration_limit = kwargs.get('pre_lp_iteration_limit', 100)
+        self.lp_iteration_limit = kwargs.get('lp_iteration_limit', 100)
+        self.lp_cleanup_phase = kwargs.get('lp_cleanup_phase', True)
+        self.iteration_limit = kwargs.get('iteration_limit', 100000)
+        self.verbose = kwargs.get('verbose',False)
+
+        if self.verbose:
+            logger.setLevel(logging.INFO)
+
+        self.initial_pass_complete = ComponentSet()
+        self.bundling = self.opt.bundling
+
+        self.vars_to_load = ComponentMap()
+        self.time_periods = ComponentMap()
+        self.bundle_conditional_probability = ComponentMap()
+
+    def pre_solve(self, subproblem):
+        if subproblem not in self.initial_pass_complete:
+            self.spoke_name = None
+            if self.opt.spcomm is not None:
+                self.spoke_name = self.opt.spcomm.__class__.__name__
+            self._initial_pass(subproblem)
+            self.initial_pass_complete.add(subproblem)
+
+    def post_solve(self, subproblem, results):
+        scenario_blocks = self._get_scenario_blocks(subproblem)
+        termination_cond, results, iterations = \
+            self._mip_pass(subproblem, scenario_blocks, results)
+        return results
+
+    def _get_scenario_blocks(self, subproblem):
+        if self.bundling:
+            return tuple( subproblem.component(sname) \
+                          for sname in subproblem._ef_scenario_names )
+        else:
+            return ( subproblem, )
+
+    def _initial_pass(self, subproblem):
+        # get vars_to_load for later
+        scenario_blocks = self._get_scenario_blocks(subproblem)
+        if is_persistent(subproblem._solver_plugin):
+            subproblem_vars_to_load = []
+            for s in scenario_blocks:
+                for t in s.TimePeriods:
+                    b = s.TransmissionBlock[t]
+                    assert isinstance(b.p_nw, pyo.Var)
+                    subproblem_vars_to_load.extend(b.p_nw.values())
+
+            self.vars_to_load[subproblem] = subproblem_vars_to_load
+        else:
+            self.vars_to_load[subproblem] = None
+
+        for s in scenario_blocks:
+            self.time_periods[s] = s.TimePeriods
+            if self.bundling:
+                self.bundle_conditional_probability[s] = \
+                        s._mpisppy_data.bundle_conditional_probability
+            else:
+                self.bundle_conditional_probability[s] = 1.
+
+        self.tee = ("tee-rank0-solves" in self.opt.options
+                    and self.opt.options['tee-rank0-solves']
+                    and self.opt.cylinder_rank == 0
+                    )
+
+        if (self.pre_lp_iteration_limit + self.lp_iteration_limit) == 0:
+            return
+
+        # relax the initial subproblems
+        for s in scenario_blocks:
+            lpu.uc_instance_binary_relaxer(s, subproblem._solver_plugin)
+
+        # solve the model
+        for k,val in self.opt.current_solver_options.items():
+            subproblem._solver_plugin.options[k] = val
+
+        if is_persistent(subproblem._solver_plugin):
+            results = subproblem._solver_plugin.solve(subproblem, tee=self.tee, save_results=False, load_solutions=False)
+            subproblem._solver_plugin.load_vars(self.vars_to_load[subproblem])
+        else:
+            results = subproblem._solver_plugin.solve(subproblem, tee=self.tee, load_solutions=False)
+            subproblem.solutions.load_from(results)
+
+        if self.pre_lp_iteration_limit > 0:
+            lp_warmstart_termination_cond, results, lp_warmstart_iterations = \
+                    self._pre_lp_pass(subproblem, scenario_blocks)
+
+        if self.lp_iteration_limit > 0:
+            lp_termination_cond, results, lp_iterations = \
+                    self._lp_pass(subproblem, scenario_blocks)
+
+        if self.lp_cleanup_phase:
+            tot_removed = 0
+            for s in scenario_blocks:
+                for t,b in s.TransmissionBlock.items():
+                    tot_removed += lpu.remove_inactive(b, subproblem._solver_plugin, 
+                                                        t, prepend_str=f"[LP cleanup phase on rank {self.opt.global_rank}] ")
+            logger.info(f"[LP cleanup phase on rank {self.opt.global_rank} for {self.spoke_name}] removed {tot_removed} inactive flow constraint(s)")
+        # enforce binaries in subproblems
+        for s in scenario_blocks:
+            lpu.uc_instance_binary_enforcer(s, subproblem._solver_plugin)
+
+        # mpi-sppy will solve the MIP
+        return
+
+    def _do_pass(self, subproblem, scenario_blocks, time_periods, vars_to_load, 
+            prepend_str, iteration_limit, add_all_lazy_violations=False, 
+            results=None, pre_lp_cleanup=False):
+
+        persistent_solver = is_persistent(subproblem._solver_plugin)
+        for i in range(iteration_limit):
+            flows, viol_lazy = ComponentMap(), ComponentMap()
+            terminate_this_iter, all_viol_in_model = ComponentMap(), ComponentMap()
+            for s in scenario_blocks:
+                flows[s], viol_num, mon_viol_num, viol_lazy[s] = \
+                        _lazy_ptdf_check_violations(s, s.model_data, time_periods[s],
+                                s._ptdf_options, prepend_str)
+
+                terminate_this_iter[s], all_viol_in_model[s] = \
+                        _lazy_ptdf_log_terminate_on_violations(viol_num, mon_viol_num,
+                                                                i, prepend_str)
+
+            all_viol_in_model = all(all_viol_in_model.values())
+            terminate_this_iter = all(terminate_this_iter.values())
+            if terminate_this_iter and not add_all_lazy_violations:
+                if pre_lp_cleanup:
+                    results = self._pre_lp_cleanup(subproblem, scenario_blocks,
+                                                    persistent_solver, time_periods, prepend_str)
+                return _lazy_ptdf_normal_terminatation(all_viol_in_model, results, i, prepend_str)
+
+            for s in scenario_blocks:
+                _lazy_ptdf_violation_adder(s, s.model_data, flows[s], viol_lazy[s], time_periods[s],
+                                subproblem._solver_plugin, s._ptdf_options, prepend_str, i,
+                                obj_multi=self.bundle_conditional_probability[s])
+
+            if terminate_this_iter and add_all_lazy_violations:
+                if pre_lp_cleanup:
+                    results = self._pre_lp_cleanup(subproblem, scenario_blocks,
+                                                    persistent_solver, time_periods, prepend_str)
+                return _lazy_ptdf_normal_terminatation(all_viol_in_model, results, i, prepend_str)
+
+            results = _lazy_ptdf_solve(subproblem, subproblem._solver_plugin, persistent_solver,
+                                       symbolic_solver_labels=False, solver_tee=self.tee,
+                                       vars_to_load=vars_to_load, solve_method_options=None)
+        else:
+            if pre_lp_cleanup:
+                results = self._pre_lp_cleanup(subproblem, scenario_blocks,
+                                        persistent_solver, time_periods, prepend_str)
+            return lpu.LazyPTDFTerminationCondition.ITERATION_LIMIT, results, i
+
+    def _pre_lp_cleanup(self, subproblem, scenario_blocks, persistent_solver, time_periods, prepend_str):
+        if persistent_solver:
+            # unpack lpu._load_pf_slacks into a single call to load_vars
+            vars_to_load = []
+            for s in scenario_blocks:
+                for t in time_periods[s]:
+                    b = s.TransmissionBlock[t]
+                    vars_to_load.extend(b.pf_slack_pos.values())
+                    vars_to_load.extend(b.pf_slack_neg.values())
+                    vars_to_load.extend(b.pfi_slack_pos.values())
+                    vars_to_load.extend(b.pfi_slack_neg.values())
+                    vars_to_load.extend(b.pfc_slack_pos.values())
+                    vars_to_load.extend(b.pfc_slack_neg.values())
+            if vars_to_load:
+                subproblem._solver_plugin.load_vars(vars_to_load)
+
+        for s in scenario_blocks:
+            _lazy_ptdf_warmstart_copy_violations(s, s.model_data, time_periods[s],
+                    subproblem._solver_plugin, s._ptdf_options, prepend_str,
+                    obj_multi=self.bundle_conditional_probability[s])
+
+        results = _lazy_ptdf_solve(subproblem, subproblem._solver_plugin, persistent_solver,
+                                   symbolic_solver_labels=False, solver_tee=self.tee,
+                                   vars_to_load=self.vars_to_load[subproblem],
+                                   solve_method_options=None)
+        return results
+
+    def _pre_lp_pass(self, subproblem, scenario_blocks):
+        vars_to_load_t_subset = ComponentMap()
+        t_subset = ComponentMap()
+        persistent_solver = is_persistent(subproblem._solver_plugin)
+
+        if persistent_solver:
+            vars_to_load = []
+        else:
+            vars_to_load = None
+        for s in scenario_blocks:
+            max_demand_time = max(s.TotalDemand, key=s.TotalDemand.__getitem__)
+            t_subset[s] = [max_demand_time,]
+            if persistent_solver:
+                transmission_block = s.TransmissionBlock[max_demand_time]
+                assert isinstance(transmission_block.p_nw, pyo.Var)
+                vars_to_load.extend(transmission_block.p_nw.values())
+
+        return self._do_pass(subproblem, scenario_blocks, t_subset, vars_to_load,
+                             prepend_str=f"[LP warmstart phase on rank {self.opt.global_rank} for {self.spoke_name}] ",
+                             iteration_limit=self.pre_lp_iteration_limit,
+                             add_all_lazy_violations=False,
+                             results=None, pre_lp_cleanup=True) 
+
+    def _lp_pass(self, subproblem, scenario_blocks):
+        return self._do_pass(subproblem, scenario_blocks,
+                             self.time_periods, self.vars_to_load[subproblem],
+                             prepend_str=f"[LP phase on rank {self.opt.global_rank} for {self.spoke_name}] ",
+                             iteration_limit=self.lp_iteration_limit,
+                             add_all_lazy_violations=True,
+                             results=None, pre_lp_cleanup=False) 
+
+    def _mip_pass(self, subproblem, scenario_blocks, results):
+        return self._do_pass(subproblem, scenario_blocks,
+                             self.time_periods, self.vars_to_load[subproblem],
+                             prepend_str=f"[MIP phase on rank {self.opt.global_rank} for {self.spoke_name}] ",
+                             iteration_limit=self.iteration_limit,
+                             add_all_lazy_violations=False,
+                             results=results, pre_lp_cleanup=False) 

examples/uc/uc_cylinders.py

@@ -20,6 +20,7 @@
 from mpisppy.utils import vanilla
 from mpisppy.extensions.cross_scen_extension import CrossScenarioExtension
 
+from ptdf_ext import PTDFExtension
 
 def _parse_args():
     parser = baseparsers.make_parser("uc_cylinders")
@@ -30,6 +31,7 @@ def _parse_args():
     parser = baseparsers.xhatlooper_args(parser)
     parser = baseparsers.xhatshuffle_args(parser)
     parser = baseparsers.cross_scenario_cuts_args(parser)
+    parser = baseparsers.mip_options(parser)
     parser.add_argument("--ph-mipgaps-json",
                         help="json file with mipgap schedule (default None)",
                         dest="ph_mipgaps_json",
@@ -47,6 +49,12 @@ def _parse_args():
                         action='store_true',
                         dest='xhat_closest_tree',
                         default=False)
+    parser.add_argument("--add-contingency-constraints",
+                        help="Use EGRET to monitor all possible"
+                             " non-disconnecting contingencies (default False)",
+                        action='store_true',
+                        dest='add_contingency_constraints',
+                        default=False)
     args = parser.parse_args()
     return args
 
@@ -65,15 +73,19 @@ def main():
     fixer_tol = args.fixer_tol
     with_cross_scenario_cuts = args.with_cross_scenario_cuts
 
-    scensavail = [3,5,10,25,50,100]
+    scensavail = [3,4,5,10,25,50,100]
     if num_scen not in scensavail:
         raise RuntimeError("num-scen was {}, but must be in {}".\
                            format(num_scen, scensavail))
 
     scenario_creator_kwargs = {
-        "scenario_count": num_scen,
-        "path": str(num_scen) + "scenarios_r1",
-    }
+            "scenario_count": num_scen,
+            "path": str(num_scen) + "scenarios_r1",
+            "add_contingency_constraints": args.add_contingency_constraints,
+        }
+    if num_scen == 4:
+        scenario_creator_kwargs["path"] = str(num_scen) + "scenarios_rtsgmlc"
+
     scenario_creator = uc.scenario_creator
     scenario_denouement = uc.scenario_denouement
     all_scenario_names = [f"Scenario{i+1}" for i in range(num_scen)]
@@ -90,7 +102,7 @@ def main():
                               rho_setter = rho_setter)
 
     # Extend and/or correct the vanilla dictionary
-    ext_classes =  [Gapper]
+    ext_classes =  [Gapper, PTDFExtension]
     if with_fixer:
         ext_classes.append(Fixer)
     if with_cross_scenario_cuts:
@@ -134,24 +146,30 @@ def main():
     # FWPH spoke
     if with_fwph:
         fw_spoke = vanilla.fwph_spoke(*beans, scenario_creator_kwargs=scenario_creator_kwargs)
+        fw_spoke["opt_kwargs"]["extensions"] = PTDFExtension
 
     # Standard Lagrangian bound spoke
     if with_lagrangian:
         lagrangian_spoke = vanilla.lagrangian_spoke(*beans,
                                               scenario_creator_kwargs=scenario_creator_kwargs,
                                               rho_setter = rho_setter)
+        lagrangian_spoke["opt_kwargs"]["extensions"] = PTDFExtension
 
     # xhat looper bound spoke
     if with_xhatlooper:
         xhatlooper_spoke = vanilla.xhatlooper_spoke(*beans, scenario_creator_kwargs=scenario_creator_kwargs)
+        xhatlooper_spoke["opt_kwargs"]["extensions"] = PTDFExtension
 
     # xhat shuffle bound spoke
     if with_xhatshuffle:
         xhatshuffle_spoke = vanilla.xhatshuffle_spoke(*beans, scenario_creator_kwargs=scenario_creator_kwargs)
+        xhatshuffle_spoke["opt_kwargs"]["extensions"] = PTDFExtension
 
     # cross scenario cut spoke
     if with_cross_scenario_cuts:
         cross_scenario_cut_spoke = vanilla.cross_scenario_cut_spoke(*beans, scenario_creator_kwargs=scenario_creator_kwargs)
+        cross_scenario_cut_spoke["opt_kwargs"]["extensions"] = PTDFExtension
+
 
     list_of_spoke_dict = list()
     if with_fwph: