From d74a79799d7ef9aeeb3436ca9b5a79f814e7779f Mon Sep 17 00:00:00 2001
From: Ni Wang <125902905+gnawin@users.noreply.github.com>
Date: Fri, 20 Sep 2024 12:02:20 +0200
Subject: [PATCH] Add multi-year information to advanced concepts in the doc
 (#1082)

* Add multi-year docs

* improve docs

* minor edit

* remove files

* Add error
---
 docs/make.jl                                  |   1 +
 .../figs_multi-year/discounted_annuities.png  | Bin 0 -> 20336 bytes
 docs/src/advanced_concepts/multi-year.md      |  53 ++++++++++++++++++
 src/data_structure/economic_structure.jl      |   5 ++
 .../check_economic_structure.jl               |  48 ++++++++++++++++
 5 files changed, 107 insertions(+)
 create mode 100644 docs/src/advanced_concepts/figs_multi-year/discounted_annuities.png
 create mode 100644 docs/src/advanced_concepts/multi-year.md

diff --git a/docs/make.jl b/docs/make.jl
index ae4809a583..1003165803 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -60,6 +60,7 @@ pages = [
     "Standard model features" => Any[
         "Unit Commitment" => joinpath("advanced_concepts", "unit_commitment.md"),
         "Investment Optimization" => joinpath("advanced_concepts", "investment_optimization.md"),
+        "Multi-year Investments" => joinpath("advanced_concepts", "multi-year.md"),
         "Reserves" => joinpath("advanced_concepts", "reserves.md"),
         "Ramping" => joinpath("advanced_concepts", "ramping.md"),
         "Lossless nodal DC power flows" => joinpath("advanced_concepts", "Lossless_DC_power_flow.md"),
diff --git a/docs/src/advanced_concepts/figs_multi-year/discounted_annuities.png b/docs/src/advanced_concepts/figs_multi-year/discounted_annuities.png
new file mode 100644
index 0000000000000000000000000000000000000000..642ba3ea2e90377016b44ba8f958d32f7e337494
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diff --git a/docs/src/advanced_concepts/multi-year.md b/docs/src/advanced_concepts/multi-year.md
new file mode 100644
index 0000000000..51638b59c0
--- /dev/null
+++ b/docs/src/advanced_concepts/multi-year.md
@@ -0,0 +1,53 @@
+# Multi-year investments
+
+Multi-year investments refer to making investment decisions at different points in time, such that a pathway of investments can be modeled. This is particularly useful when long-term scenarios are modeled, but modeling each year is not practical. Or in a business case, investment decisions are supposed to be made in different years which has an impact on the cash flow.
+
+There are two tutorials related to multi-year investments: [Capacity planning Tutorial](https://spine-tools.github.io/SpineOpt.jl/latest/tutorial/capacity_planning/) and [Multi-year investments](https://spine-tools.github.io/SpineOpt.jl/latest/tutorial/capacity_planning/#Multi-year-investments). This section covers the concepts of multi-year investments in SpineOpt, but we highly recommend checking out these tutorial for a more thorough understanding of how the model is set up.
+
+## Basic idea
+
+SpineOpt offers flexibility to the users so that different things can be modeled given specific set-ups and inputs of the model. This flexibility can be greatly illustrated by the multi-year investments modeling. We apply the same mathematical formulation for any capacity planning exercises, as shown in [Capacity planning Tutorial](https://spine-tools.github.io/SpineOpt.jl/latest/tutorial/capacity_planning/). For the multi-year model, what you would need differently from a single-year model is mainly the specification of the temporal structure, i.e., the investment period and operational period, and the rest works very much similarly to a single-year model.
+
+## Economic representation
+
+### Parameters
+It can be tricky to put the correct cost parameters into the model since factors like discounting and end-of-lifetime effects have to be taken into account. For that purpose, SpineOpt has incorporated some dedicated parameters for economic representation. Set `use_economic_representation` to `true` will activate these paramters.
+
+**Discounted annuities**
+
+This factor translates the overnight costs of investment into discounted (to the discount_year) annual payments, distributed over the total lifetime of the investment. Investment payments are assumed to increase linearly over the lead-time, and decrease linearly towards the end of the economic lifetime. This is also illustrated here:
+
+![image](figs_multi-year/discounted_annuities.png)
+
+For this purpose, we first calculate first the fraction of payment per year (e.g. something like 0.25, 0.5, 0.75,1 over the lead time; 1 for the economic lifetime minus the lead time, and 0.75, 0.5, 0.25 and 0 for the remaining economic lifetime). Each payment fraction is then multiplied by the discounting factor of the payment year with respect to the discounting year (e.g. start of optimization).
+
+**Salvage fraction**
+
+As we consider (discounted and annuitized) overnight costs in the objective function, it can happen that the lifetime of a unit exceeds the model horizon. In such cases, the salvage fraction needs to be deducted from the objective function. In principle, this means, that the annuities "already paid", which exceed the modelling horizon, are recuperated.
+
+**Discounted durations**
+
+The discounted duration is used to discount operational costs within a certain investment period to the discount year (e.g. beginning of the optimization). If milestone years are used for investments, the discounted duration is calculated for each investment period as defined by investment temporal blocks, otherwise, it will be calculated on a yearly basis.
+
+**Technology specific discount factors**
+
+The technology specific discount factor can be used, if e.g. investments in a certain technology are particularly risky. The default value for this parameter is 1.
+
+### Adaptions objective terms
+
+When `use_economic_representation` is set to `true`:
+
+- Investment costs are multiplied with discounted annuties conversion factor and the technological discount factor and (1 - salvage fraction).
+
+- Operational cost terms are multiplied with the discounted duration factor.
+
+### Additional information
+
+More information can be found in the following files.
+
+- [Economic representation in SpineOpt](https://github.com/Spine-project/SpineOpt.jl/files/9130471/Spine_invest.3.pdf) contains the details of the calculation of the economic prameters. Note that this document covers more concepts than what is currently available in SpineOpt (the available ones are the parameters listed above and the adaptions in the objective), the rest is under development.
+
+- [Economic parameters calculation tool](https://github.com/Spine-project/SpineOpt.jl/files/9130469/parameter_illustration.2.xlsx) is an excel tool that you can use to calculate the economic parameters on your own.
+
+!!! Warning
+    Please also note that the use of economic representation in SpineOpt does not support rolling horizon and Benders' decomposition, which warrants future improvements.
\ No newline at end of file
diff --git a/src/data_structure/economic_structure.jl b/src/data_structure/economic_structure.jl
index 089cba9cc4..b48ce2300e 100644
--- a/src/data_structure/economic_structure.jl
+++ b/src/data_structure/economic_structure.jl
@@ -22,6 +22,11 @@
 """
 function generate_economic_structure!(m; log_level=3)
     use_economic_representation(model=m.ext[:spineopt].instance) || return
+    if !isnothing(roll_forward(model=m.ext[:spineopt].instance))
+        error("Using economic representation with rolling horizon is currently not supported.")
+    elseif model_type(model=m.ext[:spineopt].instance) === :spineopt_benders 
+        error("Using economic representation with Benders' decomposition is currently not supported.")
+    end
     !isempty(
         [
             model__default_investment_temporal_block()
diff --git a/test/data_structure/check_economic_structure.jl b/test/data_structure/check_economic_structure.jl
index 67fe60c557..13f0cccea3 100644
--- a/test/data_structure/check_economic_structure.jl
+++ b/test/data_structure/check_economic_structure.jl
@@ -280,4 +280,52 @@
         expected_coe_obj = (1 - salvage_frac) * conv_to_disc_annuities * tech_fac * inv_cost
         @test expected_coe_obj ≈ observed_coe_obj rtol = 1e-6
     end
+    @testset "test rolling error exception" begin
+        _load_test_data(url_in, test_data)
+        discnt_year = Dict("type" => "date_time", "data" => "2020-01-01T00:00:00")
+        discnt_rate = 0.05
+        tech_discnt_rate = 0.85
+        use_mlstne_year = false
+        candidate_unts = 1
+        inv_cost = 2
+        object_parameter_values = [
+            ["model", "instance", "discount_rate", discnt_rate],
+            ["model", "instance", "discount_year", discnt_year],
+            ["model", "instance", "use_milestone_years", use_mlstne_year],
+            ["model", "instance", "use_economic_representation", true],
+            ["model", "instance", "roll_forward", Dict("type" =>"duration","data"=>"1D")],
+            ["unit", "unit_ab", "candidate_units", candidate_unts],
+            ["unit", "unit_ab", "unit_investment_cost", inv_cost],
+            ["unit", "unit_ab", "unit_discount_rate_technology_specific", tech_discnt_rate],
+            ["unit", "unit_ab", "unit_lead_time", Dict("type" => "duration", "data" => "1Y")],
+            ["unit", "unit_ab", "unit_investment_tech_lifetime", Dict("type" => "duration", "data" => "5Y")],
+            ["unit", "unit_ab", "unit_investment_econ_lifetime", Dict("type" => "duration", "data" => "5Y")],
+        ]
+        SpineInterface.import_data(url_in; object_parameter_values=object_parameter_values)
+        @test_throws ErrorException run_spineopt(url_in; optimize=false, log_level=1)
+    end
+    @testset "test Benders error exception" begin
+        _load_test_data(url_in, test_data)
+        discnt_year = Dict("type" => "date_time", "data" => "2020-01-01T00:00:00")
+        discnt_rate = 0.05
+        tech_discnt_rate = 0.85
+        use_mlstne_year = false
+        candidate_unts = 1
+        inv_cost = 2
+        object_parameter_values = [
+            ["model", "instance", "discount_rate", discnt_rate],
+            ["model", "instance", "discount_year", discnt_year],
+            ["model", "instance", "use_milestone_years", use_mlstne_year],
+            ["model", "instance", "use_economic_representation", true],
+            ["model", "instance", "model_type", "spineopt_benders"],
+            ["unit", "unit_ab", "candidate_units", candidate_unts],
+            ["unit", "unit_ab", "unit_investment_cost", inv_cost],
+            ["unit", "unit_ab", "unit_discount_rate_technology_specific", tech_discnt_rate],
+            ["unit", "unit_ab", "unit_lead_time", Dict("type" => "duration", "data" => "1Y")],
+            ["unit", "unit_ab", "unit_investment_tech_lifetime", Dict("type" => "duration", "data" => "5Y")],
+            ["unit", "unit_ab", "unit_investment_econ_lifetime", Dict("type" => "duration", "data" => "5Y")],
+        ]
+        SpineInterface.import_data(url_in; object_parameter_values=object_parameter_values)
+        @test_throws ErrorException run_spineopt(url_in; optimize=false, log_level=1)
+    end
 end
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