more condition checking on AELMP

docs/src/usage.md

@@ -189,7 +189,7 @@ This method has two configurable parameters: `allow_offline_participation` and `
 
 !!! warning
 
-    This approximation method is still under active research, and has several limitations. The implementation provided in the package is based on MISO Phase I only. It only supports fast start resources. More specifically, the minimum up/down time of all generators must be 1. The method does not support time-varying start-up costs. AELMPs are only calculated for the first time period if offline participation is not allowed.
+    This approximation method is still under active research, and has several limitations. The implementation provided in the package is based on MISO Phase I only. It only supports fast start resources. More specifically, the minimum up/down time of all generators must be 1, the initial power of all generators must be 0, and the initial status of all generators must be negative. The method does not support time-varying start-up costs. If offline participation is not allowed, AELMPs treats an asset to be  offline if it is never on throughout all time periods. 
 
 ```julia
 using UnitCommitment

src/lmp/aelmp.jl

@@ -8,8 +8,8 @@ using JuMP
     function compute_lmp(
         model::JuMP.Model,
         method::AELMP;
-        optimizer = nothing,
-    )
+        optimizer,
+    )::OrderedDict{Tuple{String,Int},Float64}
 
 Calculates the approximate extended locational marginal prices of the given unit commitment instance.
 
@@ -25,7 +25,7 @@ WARNING: This approximation method is not fully developed. The implementation is
 
 1. It only supports Fast Start resources. More specifically, the minimum up/down time has to be zero.
 2. The method does NOT support time-varying start-up costs.
-3. AELMPs are only calculated for the first time period if offline participation is not allowed.
+3. An asset is considered offline if it is never on throughout all time periods. 
 
 Arguments
 ---------
@@ -82,7 +82,7 @@ function compute_lmp(
 )::OrderedDict{Tuple{String,Int},Float64}
     @info "Building the approximation model..."
     instance = deepcopy(model[:instance])
-    _aelmp_check_parameters(method, model)
+    _aelmp_check_parameters(instance, model, method)
     _modify_instance!(instance, model, method)
 
     # prepare the result dictionary and solve the model 
@@ -111,7 +111,11 @@ function compute_lmp(
     return elmp
 end
 
-function _aelmp_check_parameters(method::AELMP, model::JuMP.Model)
+function _aelmp_check_parameters(
+    instance::UnitCommitmentInstance,
+    model::JuMP.Model,
+    method::AELMP,
+)
     # CHECK: model must be solved if allow_offline_participation=false
     if !method.allow_offline_participation
         if isnothing(model) || !has_values(model)
@@ -120,6 +124,29 @@ function _aelmp_check_parameters(method::AELMP, model::JuMP.Model)
             )
         end
     end
+    all_units = instance.units;
+    # CHECK: model cannot handle non-fast-starts (MISO Phase I: can ONLY solve fast-starts)
+    if any(u -> u.min_uptime > 1 || u.min_downtime > 1, all_units) 
+        error(
+            "The minimum up/down time of all generators must be 1. AELMP only supports fast-starts.",
+        )
+    end
+    if any(u -> u.initial_power > 0, all_units)
+        error(
+            "The initial power of all generators must be 0.",
+        )
+    end
+    if any(u -> u.initial_status >= 0, all_units)
+        error(
+            "The initial status of all generators must be negative.",
+        )
+    end
+    # CHECK: model does not support startup costs (in time series)
+    if any(u -> length(u.startup_categories) > 1, all_units)
+        error(
+            "The method does NOT support time-varying start-up costs.",
+        )
+    end
 end
 
 function _modify_instance!(
@@ -128,22 +155,25 @@ function _modify_instance!(
     method::AELMP,
 )
     # this function modifies the instance units (generators)
-    # 1. remove (if NOT allowing) the offline generators
     if !method.allow_offline_participation
+        # 1. remove (if NOT allowing) the offline generators
+        units_to_remove = []
         for unit in instance.units
             # remove based on the solved UC model result
-            # here, only look at the first time slot (TIME-SERIES-NOT-SUPPORTED)
-            if value(model[:is_on][unit.name, 1]) == 0
+            # remove the unit if it is never on
+            if all(t -> value(model[:is_on][unit.name, t]) == 0, instance.time)
                 # unregister from the bus 
                 filter!(x -> x.name != unit.name, unit.bus.units)
                 # unregister from the reserve
                 for r in unit.reserves
                     filter!(x -> x.name != unit.name, r.units)
                 end
+                # append the name to the remove list
+                push!(units_to_remove, unit.name)
             end
         end
-        # unregister the units
-        filter!(x -> value(model[:is_on][x.name, 1]) != 0, instance.units)
+        # unregister the units from the remove list
+        filter!(x -> !(x.name in units_to_remove), instance.units)
     end
 
     for unit in instance.units
@@ -164,7 +194,6 @@ function _modify_instance!(
         end
 
         # 3. average the start-up costs (if considering)
-        # for now, consider first element only (TIME-SERIES-NOT-SUPPORTED)
         # if consider_startup_costs = false, then use the current first_startup_cost
         first_startup_cost = unit.startup_categories[1].cost
         if method.consider_startup_costs
@@ -174,17 +203,8 @@ function _modify_instance!(
             end
             first_startup_cost = 0.0 # zero out the start up cost
         end
-
-        # 4. other adjustments...
-        ### FIXME in the future
-        # MISO Phase I: can ONLY solve fast-starts, force all startup time to be 0
         unit.startup_categories =
-            StartupCategory[StartupCategory(0, first_startup_cost)]
-        unit.initial_status = -100
-        unit.initial_power = 0
-        unit.min_uptime = 0
-        unit.min_downtime = 0
-        ### END FIXME
+            StartupCategory[StartupCategory(0, first_startup_cost)]        
     end
     return instance.units_by_name = Dict(g.name => g for g in instance.units)
 end