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58 lines
2.1 KiB
58 lines
2.1 KiB
# RELOG: Reverse Logistics Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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using DataFrames
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using CSV
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function products_report(solution; marginal_costs)::DataFrame
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df = DataFrame()
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df."product name" = String[]
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df."location name" = String[]
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df."latitude (deg)" = Float64[]
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df."longitude (deg)" = Float64[]
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df."year" = Int[]
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df."amount (tonne)" = Float64[]
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df."amount disposed (tonne)" = Float64[]
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df."marginal cost (\$/tonne)" = Float64[]
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df."acquisition cost (\$)" = Float64[]
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df."disposal cost (\$)" = Float64[]
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T = length(solution["Energy"]["Plants (GJ)"])
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for (prod_name, prod_dict) in solution["Products"]
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for (location_name, location_dict) in prod_dict
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for year = 1:T
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if marginal_costs
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marginal_cost = location_dict["Marginal cost (\$/tonne)"][year]
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else
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marginal_cost = 0.0
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end
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latitude = round(location_dict["Latitude (deg)"], digits = 6)
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longitude = round(location_dict["Longitude (deg)"], digits = 6)
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amount = location_dict["Amount (tonne)"][year]
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amount_disposed = location_dict["Dispose (tonne)"][year]
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acquisition_cost = location_dict["Acquisition cost (\$)"][year]
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disposal_cost = location_dict["Disposal cost (\$)"][year]
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push!(
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df,
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[
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prod_name,
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location_name,
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latitude,
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longitude,
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year,
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amount,
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amount_disposed,
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marginal_cost,
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acquisition_cost,
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disposal_cost,
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],
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)
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end
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end
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end
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return df
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end
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write_products_report(solution, filename; marginal_costs = true) =
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CSV.write(filename, products_report(solution; marginal_costs))
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