Updates based on breaking changes in 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

@@ -10,7 +10,7 @@ using Clp
  # run clustering
  ts_clust_res = run_clust(ts_input_data;method="kmeans",representation="centroid",n_init=1,n_clust=365) # default k-means
  # run optimization
- model = run_opt(ts_clust_res.best_results,cep_input_data,Clp.Optimizer;optimizer_config=Dict{Symbol,Any}(:LogLevel => 0))
+ model = run_opt(ts_clust_res.clust_data,cep_input_data,Clp.Optimizer;optimizer_config=Dict{Symbol,Any}(:LogLevel => 0))
  # compare to exact result
  exact_res=[70540.26439790576;0.0;8498.278397905757;0.0;80132.88454450261]
  @test exact_res ≈ model.variables["CAP"].data[:,1,1] atol=1
@@ -27,13 +27,13 @@ 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
@@ -45,7 +45,7 @@ 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