Compatability update for ClustForOpt 0.4.0

Project.toml

@@ -4,7 +4,7 @@ keywords = ["energy", "capacity", "JuMP", "optimization"]
 license = "MIT"
 desc = "Capacity Expansion Problem Formulation for Julia"
 author = ["Elias Kuepper <elias.kuepper@rwth-aachen.de>"]
-version = "0.1.4"
+version = "0.1.5"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
@@ -19,4 +19,4 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 [compat]
 julia = "^1.0"
 JuMP = "^0.19"
-ClustForOpt = "^0.3.4"
+ClustForOpt = "^0.4.0"

docs/src/assets/plots.jl

@@ -9,7 +9,7 @@ plot(ts_input_data.data["solar-germany"], legend=false, linestyle=:dot, xlabel="
 savefig(joinpath(dirname(@__FILE__),"preparing_clust_data_load.svg"))
 
 
-ts_clust_data = run_clust(ts_input_data;method="kmeans",representation="centroid",n_init=50,n_clust=5).best_results
+ts_clust_data = run_clust(ts_input_data;method="kmeans",representation="centroid",n_init=50,n_clust=5).clust_data
 plot(ts_clust_data.data["solar-germany"], legend=false, linestyle=:solid, width=3, xlabel="Time [h]", ylabel="Solar availability factor [%]")
 savefig(joinpath(dirname(@__FILE__),"preparing_clust_data_agg.svg"))
 

examples/workflow_example_cep.jl

@@ -20,30 +20,30 @@ ts_seg_data = run_clust(ts_input_data;method="kmeans",representation="centroid",
 optimizer=Clp.Optimizer
 
 # tweak the CO2 level
-co2_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;co2_limit=50) #generally values between 1250 and 10 are interesting
+co2_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;co2_limit=50) #generally values between 1250 and 10 are interesting
 
 # Include a Slack-Variable
-slack_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;lost_el_load_cost=1e6, lost_CO2_emission_cost=700)
+slack_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;lost_el_load_cost=1e6, lost_CO2_emission_cost=700)
 
 
 # Include existing infrastructure at no COST
-ex_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;existing_infrastructure=true)
+ex_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;existing_infrastructure=true)
 
 # Intraday storage (just within each period, same storage level at beginning and end)
-simplestor_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;storage="simple")
+simplestor_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;storage="simple")
 
 # Interday storage (within each period & between the periods)
-seasonalstor_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;storage="seasonal")
+seasonalstor_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;storage="seasonal")
 
 # Transmission
-transmission_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;transmission=true)
+transmission_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;transmission=true)
 
 # Segmentation
-seg_result = run_opt(ts_seg_data.best_results,cep_data,optimizer)
+seg_result = run_opt(ts_seg_data.clust_data,cep_data,optimizer)
 
 # Desing with clusered data and operation with ts_full_data
 # First solve the clustered case
-design_result = run_opt(ts_clust_data.best_results,cep_data,optimizer;co2_limit=50)
+design_result = run_opt(ts_clust_data.clust_data,cep_data,optimizer;co2_limit=50)
 
 #capacity_factors
 design_variables=get_cep_design_variables(design_result)

examples/workflow_example_cep_plot.jl

@@ -18,7 +18,7 @@ ts_clust_data = run_clust(ts_input_data;method="kmeans",representation="centroid
 optimizer=Clp.Optimizer
 
 # Optimize the capacity expansion problem with a co2_limit of 1000
-cep = run_opt(ts_clust_data.best_results,cep_data,optimizer;co2_limit=1000)
+cep = run_opt(ts_clust_data.clust_data,cep_data,optimizer;co2_limit=1000)
 
 # Extract the CAP-Variable
 cap=cep.variables["CAP"]

examples/workflow_introduction.jl

@@ -64,7 +64,7 @@ end
 #############
 # Quick example and investigation of the best result:
 ts_clust_result = run_clust(ts_input_data; method="kmeans", representation="centroid", n_init=5, n_clust=5) # note that you should use n_init=1000 at least for kmeans.
-ts_clust_data = ts_clust_result.best_results
+ts_clust_data = ts_clust_result.clust_data
 # And some plotting:
 plot_comb_solar=plot!(plot_input_solar, ts_clust_data.data["solar-germany"], linestyle=:solid, width=3)
 plot_clust_soar=plot(ts_clust_data.data["el_demand-germany"], legend=false, linestyle=:solid, width=3, xlabel="Time [h]", ylabel="Solar availability factor [%]")

src/utils/datastructs.jl

@@ -165,13 +165,13 @@ end
 
 
 """
-     Scenario{descriptor::String,clust_res::ClustResult,opt_res::OptResult}
+     Scenario{descriptor::String,clust_res::AbstractClustResult,opt_res::OptResult}
 -`descriptor::String`
--`clust_res::ClustResult`
+-`clust_res::AbstractClustResult`
 -`opt_res::OptResult`
 """
 struct Scenario
  descriptor::String
- clust_res::ClustResult
+ clust_res::AbstractClustResult
  opt_res::OptResult
 end

src/utils/utils.jl

@@ -257,21 +257,21 @@ function get_total_demand(cep::OptModelCEP,
 end
 
 """
-    get_cost_series(cep_data::OptDataCEP,clust_res::ClustResultBest, opt_res::OptResult)
+    get_cost_series(cep_data::OptDataCEP,clust_res::ClustResult, opt_res::OptResult)
 Return an array for the time series of costs in all the impact dimensions and the set of impacts
 """
 function get_cost_series(nodes::DataFrame,
                         var_costs::DataFrame,
-                       clust_res::ClustResultBest,
+                       clust_res::ClustResult,
                        set::Dict{String,Array},
                        variables::Dict{String,OptVariable})
   ## DATA ##
   # ts_ids:   n_clustered periods
   ts_ids=clust_res.best_ids
   #ts_weights: k - weight of each period:
-  ts_weights=clust_res.best_results.weights
+  ts_weights=clust_res.clust_data.weights
   #ts_deltas:  t x k - Δt of each segment x period
-  ts_deltas=clust_res.best_results.delta_t
+  ts_deltas=clust_res.clust_data.delta_t
 
   #emision at each period-step
   cost_ts=zeros(length(ts_ids)+1,length(set["impact"]))

test/cep.jl

@@ -25,13 +25,13 @@ using Clp
         ## OPTIMIZATION ##
         optimizer=Clp.Optimizer
         optimizer_config=Dict{Symbol,Any}(:LogLevel => 0)
-        scenarios["$state-$years-co2"] = run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="co2",co2_limit=1000,optimizer_config=optimizer_config)
-        scenarios["$state-$years-slack"] = run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="slack",lost_el_load_cost=1e6, lost_CO2_emission_cost=700,optimizer_config=optimizer_config)
-        scenarios["$state-$years-ex"] = run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="ex",existing_infrastructure=true,optimizer_config=optimizer_config)
-        scenarios["$state-$years-simple"] = run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="simple storage",storage="simple",optimizer_config=optimizer_config)
-        scenarios["$state-$years-seasonal"] = run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="seasonal storage",storage="seasonal",optimizer_config=optimizer_config)
-        design_result=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="des&op",optimizer_config=optimizer_config)
-        scenarios["$state-$years-des&op"] = run_opt(ts_full_data.best_results,cep_data,design_result.opt_config,get_cep_design_variables(design_result),optimizer;lost_el_load_cost=1e6,lost_CO2_emission_cost=700)
+        scenarios["$state-$years-co2"] = run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="co2",co2_limit=1000,optimizer_config=optimizer_config)
+        scenarios["$state-$years-slack"] = run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="slack",lost_el_load_cost=1e6, lost_CO2_emission_cost=700,optimizer_config=optimizer_config)
+        scenarios["$state-$years-ex"] = run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="ex",existing_infrastructure=true,optimizer_config=optimizer_config)
+        scenarios["$state-$years-simple"] = run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="simple storage",storage="simple",optimizer_config=optimizer_config)
+        scenarios["$state-$years-seasonal"] = run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="seasonal storage",storage="seasonal",optimizer_config=optimizer_config)
+        design_result=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="des&op",optimizer_config=optimizer_config)
+        scenarios["$state-$years-des&op"] = run_opt(ts_full_data.clust_data,cep_data,design_result.opt_config,get_cep_design_variables(design_result),optimizer;lost_el_load_cost=1e6,lost_CO2_emission_cost=700)
         end
     end
     #Test transmission for a multi-node scenario
@@ -43,7 +43,7 @@ using Clp
            ts_clust_data = run_clust(ts_input_data;method="hierarchical",representation="centroid",n_init=1,n_clust=3)
            ## OPTIMIZATION ##
            optimizer=Clp.Optimizer
-           scenarios["$state-$years-trans"] = run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="trans",transmission=true,optimizer_config=Dict{Symbol,Any}(:LogLevel => 0))
+           scenarios["$state-$years-trans"] = run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="trans",transmission=true,optimizer_config=Dict{Symbol,Any}(:LogLevel => 0))
        end
     end
     #Test exact values for each of the previously calculated scenarios by comparison with exact scenarios

test/cep_exact_data.jl

@@ -10,13 +10,13 @@ for (state, years) in [["GER_1", [2016]],["CA_1", [2016]]]
        ts_full_data = run_clust(ts_input_data;method="hierarchical",representation="centroid",n_init=1,n_clust=30)
        ## OPTIMIZATION ##
        optimizer=Clp.Optimizer
-       exact_scenarios["$state-$years-co2"]=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="co2",co2_limit=1000)
-       exact_scenarios["$state-$years-slack"]=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="slack",lost_el_load_cost=1e6, lost_CO2_emission_cost=700)
-       exact_scenarios["$state-$years-ex"]=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="ex",existing_infrastructure=true)
-       exact_scenarios["$state-$years-simple"]=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="simple storage",storage="simple")
-       exact_scenarios["$state-$years-seasonal"]=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="seasonal storage",storage="seasonal")
-       design_result=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="des&op")
-       exact_scenarios["$state-$years-des&op"]=run_opt(ts_full_data.best_results,cep_data,design_result.opt_config,get_cep_design_variables(design_result),optimizer;lost_el_load_cost=1e6,lost_CO2_emission_cost=700)
+       exact_scenarios["$state-$years-co2"]=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="co2",co2_limit=1000)
+       exact_scenarios["$state-$years-slack"]=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="slack",lost_el_load_cost=1e6, lost_CO2_emission_cost=700)
+       exact_scenarios["$state-$years-ex"]=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="ex",existing_infrastructure=true)
+       exact_scenarios["$state-$years-simple"]=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="simple storage",storage="simple")
+       exact_scenarios["$state-$years-seasonal"]=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="seasonal storage",storage="seasonal")
+       design_result=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="des&op")
+       exact_scenarios["$state-$years-des&op"]=run_opt(ts_full_data.clust_data,cep_data,design_result.opt_config,get_cep_design_variables(design_result),optimizer;lost_el_load_cost=1e6,lost_CO2_emission_cost=700)
 end
 for (state, years) in [["GER_18", [2016]],["CA_14", [2016]]]
        # laod data
@@ -26,7 +26,7 @@ for (state, years) in [["GER_18", [2016]],["CA_14", [2016]]]
        ts_clust_data = run_clust(ts_input_data;method="hierarchical",representation="centroid",n_init=1,n_clust=3)
        ## OPTIMIZATION ##
        optimizer=Clp.Optimizer
-       exact_scenarios["$state-$years-trans"]=run_opt(ts_clust_data.best_results,cep_data,optimizer;descriptor="trans",transmission=true)
+       exact_scenarios["$state-$years-trans"]=run_opt(ts_clust_data.clust_data,cep_data,optimizer;descriptor="trans",transmission=true)
 end
 
 @save normpath(joinpath(dirname(@__FILE__),"cep_exact_data.jld2")) exact_scenarios