refactor and remove capacity term from npv objective

docs/model/investment.md

@@ -139,14 +139,15 @@ operational constraints (e.g., minimum load levels) and the balance level of the
 
 - **Optimise capacity and dispatch to maximise annualised profit:** Solve a small optimisation
   sub-problem to maximise the asset’s surplus, subject to its operational rules and the specific
-  demand tranche it is being asked to serve.
+  demand tranche it is being asked to serve. \\(\varepsilon \approx 1×10^{-14}\\) is added to each
+  \\(AC_t \\) to allow assets which are breakeven (or very close to breakeven) to be dispatched.
 
   \\[
-    maximise \Big\\{ -AFC \* cap - \sum_t act_t \* AC_t
+    maximise \Big\\{ - \sum_t act_t \* (AC_t + \varepsilon)
     \Big\\}
   \\]
 
-  Where \\( cap \\) and \\( act_t \\) are decision variables, and subject to:
+  Where \\( act_t \\) is a decision variable, and subject to:
 
   - The asset operational constraints (e.g., \\( avail_{LB}, avail_{EQ} \\), etc.), activity less
     than capacity, applied to its activity profile \\( act_t \\).

src/simulation/investment/appraisal.rs

@@ -8,6 +8,7 @@ use crate::model::Model;
 use crate::time_slice::TimeSliceID;
 use crate::units::{Activity, Capacity};
 use anyhow::Result;
+use costs::annual_fixed_cost;
 use indexmap::IndexMap;
 use std::cmp::Ordering;
 
@@ -126,7 +127,7 @@ fn calculate_npv(
     )?;
 
     // Calculate profitability index for the hypothetical investment
-    let annual_fixed_cost = -coefficients.capacity_coefficient;
+    let annual_fixed_cost = annual_fixed_cost(asset);
     let activity_surpluses = &coefficients.activity_coefficients;
     let profitability_index = profitability_index(
         results.capacity,

src/simulation/investment/appraisal/coefficients.rs

@@ -90,9 +90,6 @@ pub fn calculate_coefficients_for_npv(
     // assets are still dispatched
     const EPSILON_ACTIVITY_COEFFICIENT: MoneyPerActivity = MoneyPerActivity(f64::EPSILON * 100.0);
 
-    // Capacity coefficient
-    let capacity_coefficient = -annual_fixed_cost(asset);
-
     // Activity coefficients
     let mut activity_coefficients = IndexMap::new();
     for time_slice in time_slice_info.iter_ids() {
@@ -107,7 +104,7 @@ pub fn calculate_coefficients_for_npv(
     let unmet_demand_coefficient = MoneyPerFlow(0.0);
 
     ObjectiveCoefficients {
-        capacity_coefficient,
+        capacity_coefficient: MoneyPerCapacity(0.0),
         activity_coefficients,
         unmet_demand_coefficient,
     }

src/simulation/investment/appraisal/optimisation.rs

@@ -1,6 +1,6 @@
 //! Optimisation problem for investment tools.
 use super::DemandMap;
-use super::coefficients::ObjectiveCoefficients;
+use super::ObjectiveCoefficients;
 use super::constraints::{
     add_activity_constraints, add_capacity_constraint, add_demand_constraints,
 };
@@ -22,10 +22,46 @@ struct VariableMap {
     capacity_var: Variable,
     /// Activity variables in each time slice
     activity_vars: IndexMap<TimeSliceID, Variable>,
-    // Unmet demand variables
+    /// Unmet demand variables
     unmet_demand_vars: IndexMap<TimeSliceID, Variable>,
 }
 
+impl VariableMap {
+    /// Creates a new variable map by adding variables to the optimisation problem.
+    ///
+    /// # Arguments
+    /// * `problem` - The optimisation problem to add variables to
+    /// * `cost_coefficients` - Objective function coefficients for each variable
+    ///
+    /// # Returns
+    /// A new `VariableMap` containing all created decision variables
+    fn add_to_problem(problem: &mut Problem, cost_coefficients: &ObjectiveCoefficients) -> Self {
+        // Create capacity variable with its associated cost
+        let capacity_var =
+            problem.add_column(cost_coefficients.capacity_coefficient.value(), 0.0..);
+
+        // Create activity variables for each time slice
+        let mut activity_vars = IndexMap::new();
+        for (time_slice, cost) in &cost_coefficients.activity_coefficients {
+            let var = problem.add_column(cost.value(), 0.0..);
+            activity_vars.insert(time_slice.clone(), var);
+        }
+
+        // Create unmet demand variables for each time slice
+        let mut unmet_demand_vars = IndexMap::new();
+        for time_slice in cost_coefficients.activity_coefficients.keys() {
+            let var = problem.add_column(cost_coefficients.unmet_demand_coefficient.value(), 0.0..);
+            unmet_demand_vars.insert(time_slice.clone(), var);
+        }
+
+        Self {
+            capacity_var,
+            activity_vars,
+            unmet_demand_vars,
+        }
+    }
+}
+
 /// Map containing optimisation results and coefficients
 pub struct ResultsMap {
     /// Capacity variable
@@ -36,33 +72,6 @@ pub struct ResultsMap {
     pub unmet_demand: DemandMap,
 }
 
-/// Add variables to the problem based on cost coefficients
-fn add_variables(problem: &mut Problem, cost_coefficients: &ObjectiveCoefficients) -> VariableMap {
-    // Create capacity variable
-    let capacity_var = problem.add_column(cost_coefficients.capacity_coefficient.value(), 0.0..);
-
-    // Create activity variables
-    let mut activity_vars = IndexMap::new();
-    for (time_slice, cost) in &cost_coefficients.activity_coefficients {
-        let var = problem.add_column(cost.value(), 0.0..);
-        activity_vars.insert(time_slice.clone(), var);
-    }
-
-    // Create unmet demand variables
-    // One per time slice, all of which use the same coefficient
-    let mut unmet_demand_vars = IndexMap::new();
-    for time_slice in cost_coefficients.activity_coefficients.keys() {
-        let var = problem.add_column(cost_coefficients.unmet_demand_coefficient.value(), 0.0..);
-        unmet_demand_vars.insert(time_slice.clone(), var);
-    }
-
-    VariableMap {
-        capacity_var,
-        activity_vars,
-        unmet_demand_vars,
-    }
-}
-
 /// Adds constraints to the problem.
 fn add_constraints(
     problem: &mut Problem,
@@ -103,11 +112,9 @@ pub fn perform_optimisation(
     time_slice_info: &TimeSliceInfo,
     sense: Sense,
 ) -> Result<ResultsMap> {
-    // Set up problem
+    // Create problem and add variables
     let mut problem = Problem::default();
-
-    // Add variables
-    let variables = add_variables(&mut problem, coefficients);
+    let variables = VariableMap::add_to_problem(&mut problem, coefficients);
 
     // Add constraints
     add_constraints(