REF: main function to add Docs, better efficiency

src/app/main.jl

@@ -22,11 +22,11 @@ function parse_commandline()
             help = "path to output file"
             default = "./output.json"
         "--formulation", "-f"
-            help = "mathematical formulation to solve (acr, acp, lindistflow, nfa)"
-            default = "acr"
+            help = "mathematical formulation to solve (lindistflow (default), acr, acp, nfa)"
+            default = "lindistflow"
         "--problem", "-p"
             help = "optimization problem type (opf, mld)"
-            default = "mld"
+            default = "opf"
         "--protection-settings"
             help = "XLSX (Excel) File with Protection settings"
             default = ""
@@ -55,46 +55,66 @@ function entrypoint(args::Dict{String,<:Any})
         Memento.setlevel!(Memento.getlogger(PowerModelsONM.PMD._PM), "error")
     end
 
+    # Load events
     events = haskey(args, "events") && !isempty(args["events"]) && !isnothing(args["events"]) ? parse_events(args["events"]) : Vector{Dict{String,Any}}([])
 
-    data_eng, mn_data_eng = prepare_network_case(args["network-file"]; events=events)
+    # ENGINEERING MODEL, mutlinetwork and base case with timeseries objects
+    (data_eng, mn_data_eng) = prepare_network_case(args["network-file"]; events=events);
+
+    # Initialize output data structure
     output_data = build_blank_output(data_eng)
 
+    # MATHEMATICAL MULTINETWORK MODEL
     mn_data_math = PMD._map_eng2math_multinetwork(mn_data_eng)
     PMD.correct_network_data!(mn_data_math; make_pu=true)
 
-    form = get_formulation(args["formulation"])
-    problem = get_problem(args["problem"], haskey(mn_data_math, "nw"))
-
+    # NLP Solver to use for Load shed and OPF
     solver = build_solver_instance(args["solver-tolerance"], get(args, "verbose", false))
 
-    result = solve_problem(problem, mn_data_math, form, solver)
+    # Optimal Load Shed
+    result = solve_problem(PMD.solve_mn_mc_mld_simple, mn_data_math, PMD.LPUBFDiagPowerModel, solver; solution_processors=[getproperty(PowerModelsONM, Symbol("sol_ldf2$(args["formulation"])!"))])
 
+    # Apply the results of the load-shed to the MATHEMATICAL MODEL
     apply_load_shed!(mn_data_math, result)
 
-    optimize_switches!(mn_data_math)
+    # Optimal Switching
+    if haskey(data_eng, "switch") && !isempty(data_eng["switch"]) && any(sw["dispatchable"] == PMD.YES for (_,sw) in data_eng["switch"])
+        osw_result = optimize_switches!(mn_data_math; solution_processors=[getproperty(PowerModelsONM, Symbol("sol_ldf2$(args["formulation"])!"))]);
+    end
 
+    # Output switching actions to output data
     get_timestep_device_actions!(output_data, mn_data_math)
 
-    sol_pu, sol_si = transform_solutions(result["solution"], mn_data_math)
+    # Final optimal dispatch
+    form = get_formulation(args["formulation"])
+    problem = get_problem(args["problem"], haskey(mn_data_math, "nw"))
+    result = solve_problem(problem, mn_data_math, form, solver; solution_processors=[PMD.sol_data_model!])
+
+    # Build solutions for statistics outputs
+    sol_pu, sol_si = transform_solutions(result["solution"], mn_data_math);
 
+    # Building output statistics
     get_timestep_voltage_stats!(output_data, sol_pu, data_eng)
     get_timestep_load_served!(output_data, sol_si, data_eng)
     get_timestep_generator_profiles!(output_data, sol_si)
     get_timestep_powerflow_output!(output_data, sol_si, data_eng)
     get_timestep_storage_soc!(output_data, sol_si, data_eng)
 
+    # Get Protection Settings for Switch settings
     protection_data = haskey(args, "protection-settings") && !isempty(args["protection-settings"]) && !isnothing(args["protection-settings"]) ? parse_protection_tables(args["protection-settings"]) : Dict{NamedTuple,Dict{String,Any}}()
     get_timestep_protection_settings!(output_data, protection_data)
 
+    # Pass events to output data
     output_data["Events"] = events
 
+    # Export final result dict (debugging)
     if !isempty(args["export"])
         open(args["export"], "w") do f
             JSON.print(f, result, 2)
         end
     end
 
+    # Save output data
     open(args["output-file"], "w") do f
         JSON.print(f, output_data, 2)
     end