Merge pull request #1006 from EnergySystemsModellingLab/add-warning-for-asset-deadlock

add warning for multiple assets with same metrics

Author: Aurashk

README.md

@@ -69,7 +69,7 @@ If you use MUSE2 in your work, please cite us. For information on how to cite th
 
 ## Contributors ✨
 
-Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
+Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/emoji-key)):
 
 <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
 <!-- prettier-ignore-start -->
@@ -95,7 +95,7 @@ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/d
     <tr>
       <td align="center" size="13px" colspan="7">
         <img src="https://raw.githubusercontent.com/all-contributors/all-contributors-cli/1b8533af435da9854653492b1327a23a4dbd0a10/assets/logo-small.svg">
-          <a href="https://all-contributors.js.org/docs/en/bot/usage">Add your contributions</a>
+          <a href="https://allcontributors.org/bot/usage">Add your contributions</a>
         </img>
       </td>
     </tr>

src/simulation/investment.rs

@@ -1,6 +1,6 @@
 //! Code for performing agent investment.
 use super::optimisation::{DispatchRun, FlowMap};
-use crate::agent::Agent;
+use crate::agent::{Agent, AgentID};
 use crate::asset::{Asset, AssetIterator, AssetRef, AssetState};
 use crate::commodity::{Commodity, CommodityID, CommodityMap};
 use crate::model::ALLOW_BROKEN_OPTION_NAME;
@@ -13,13 +13,16 @@ use crate::units::{Capacity, Dimensionless, Flow, FlowPerCapacity};
 use anyhow::{Context, Result, bail, ensure};
 use indexmap::IndexMap;
 use itertools::{Itertools, chain};
-use log::debug;
+use log::{debug, warn};
 use std::collections::HashMap;
 use std::fmt::Display;
 
 pub mod appraisal;
 use appraisal::coefficients::calculate_coefficients_for_assets;
-use appraisal::{AppraisalOutput, appraise_investment};
+use appraisal::{
+    AppraisalComparisonMethod, AppraisalOutput, appraise_investment,
+    classify_appraisal_comparison_method,
+};
 
 /// A map of demand across time slices for a specific market
 type DemandMap = IndexMap<TimeSliceID, Flow>;
@@ -281,6 +284,7 @@ fn select_assets_for_single_market(
             opt_assets,
             commodity,
             agent,
+            region_id,
             prices,
             demand_portion_for_market,
             year,
@@ -617,13 +621,45 @@ fn get_candidate_assets<'a>(
         })
 }
 
+fn select_from_assets_with_equal_metric(
+    region_id: &RegionID,
+    agent_id: &AgentID,
+    commodity_id: &CommodityID,
+    equally_good_assets: Vec<AppraisalOutput>,
+) -> AppraisalOutput {
+    // Format asset details for diagnostic logging
+    let asset_details = equally_good_assets
+        .iter()
+        .map(|output| {
+            format!(
+                "Process id: '{}' (State: {}{})",
+                output.asset.process_id(),
+                output.asset.state(),
+                output
+                    .asset
+                    .id()
+                    .map(|id| format!(", Asset id: {id}"))
+                    .unwrap_or_default(),
+            )
+        })
+        .collect::<Vec<_>>()
+        .join(", ");
+    let warning_message = format!(
+        "Could not resolve deadlock between equally good appraisals for Agent id: {agent_id}, Commodity: '{commodity_id}', Region: {region_id}. Options: [{asset_details}]. Selecting first option.",
+    );
+    warn!("{warning_message}");
+    // Select the first asset arbitrarily from the equally performing options
+    equally_good_assets.into_iter().next().unwrap()
+}
+
 /// Get the best assets for meeting demand for the given commodity
 #[allow(clippy::too_many_arguments)]
 fn select_best_assets(
     model: &Model,
     mut opt_assets: Vec<AssetRef>,
     commodity: &Commodity,
     agent: &Agent,
+    region_id: &RegionID,
     prices: &CommodityPrices,
     mut demand: DemandMap,
     year: u32,
@@ -679,22 +715,56 @@ fn select_best_assets(
             &outputs_for_opts,
         )?;
 
-        // Select the best investment option according to `AppraisalOutput::compare_metric`
-        let Some(best_output) = outputs_for_opts
+        // Sort assets by appraisal metric
+        let assets_sorted_by_metric: Vec<_> = outputs_for_opts
             .into_iter()
-            // Investment options with zero capacity are excluded. This may happen if the asset has
-            // zero activity limits for all time slices with demand. This can also happen due to a
-            // known issue with the NPV objective, for which we do not currently have a solution
-            // (see https://github.com/EnergySystemsModellingLab/MUSE2/issues/716).
             .filter(|output| output.capacity > Capacity(0.0))
-            .min_by(AppraisalOutput::compare_metric)
-        else {
-            // If None, this means all investment options have zero capacity. In this case, we
-            // cannot meet demand, so have to bail out.
+            .sorted_by(AppraisalOutput::compare_metric)
+            .collect();
+
+        // check if all options have zero capacity
+        if assets_sorted_by_metric.is_empty() {
+            // In this case, we cannot meet demand, so have to bail out.
+            // This may happen if:
+            // - the asset has zero activity limits for all time slices with demand.
+            // - known issue with the NPV objective
+            // (see https://github.com/EnergySystemsModellingLab/MUSE2/issues/716).
             bail!(
                 "No feasible investment options for commodity '{}' after appraisal",
                 &commodity.id
             )
+        }
+
+        let appraisal_comparison_method = classify_appraisal_comparison_method(
+            &assets_sorted_by_metric.iter().collect::<Vec<_>>(),
+        );
+
+        // Determine the best asset based on whether multiple equally-good options exist
+        let best_output = match appraisal_comparison_method {
+            // there are multiple equally good assets by metric
+            AppraisalComparisonMethod::EqualMetrics => {
+                // Count how many assets have the same metric as the best one
+                let count = assets_sorted_by_metric
+                    .iter()
+                    .take_while(|output| {
+                        AppraisalOutput::compare_metric(&assets_sorted_by_metric[0], output).is_eq()
+                    })
+                    .count();
+
+                // select from all equally good assets
+                let equally_good_assets: Vec<_> =
+                    assets_sorted_by_metric.into_iter().take(count).collect();
+                select_from_assets_with_equal_metric(
+                    region_id,
+                    &agent.id,
+                    &commodity.id,
+                    equally_good_assets,
+                )
+            }
+            // there is a single best asset by metric
+            AppraisalComparisonMethod::Metric => {
+                assets_sorted_by_metric.into_iter().next().unwrap()
+            }
         };
 
         // Log the selected asset

src/simulation/investment/appraisal.rs

@@ -54,11 +54,62 @@ impl AppraisalOutput {
         );
 
         if approx_eq!(f64, self.metric, other.metric) {
-            Ordering::Equal
+            self.compare_with_equal_metrics(other)
         } else {
             self.metric.partial_cmp(&other.metric).unwrap()
         }
     }
+
+    /// Compare this appraisal to another when the metrics are known to be equal.
+    pub fn compare_with_equal_metrics(&self, other: &Self) -> Ordering {
+        assert!(
+            approx_eq!(f64, self.metric, other.metric),
+            "Appraisal metrics must be equal"
+        );
+
+        // Favour commissioned assets over non-commissioned
+        if self.asset.is_commissioned() && !other.asset.is_commissioned() {
+            return Ordering::Less;
+        }
+        if !self.asset.is_commissioned() && other.asset.is_commissioned() {
+            return Ordering::Greater;
+        }
+
+        // if both commissioned, favour newer ones
+        if self.asset.is_commissioned() && other.asset.is_commissioned() {
+            return self
+                .asset
+                .commission_year()
+                .cmp(&other.asset.commission_year())
+                .reverse();
+        }
+
+        Ordering::Equal
+    }
+}
+
+/// methods used to compare multiple appraisal outputs
+pub enum AppraisalComparisonMethod {
+    /// If all appraisal outputs have different metrics
+    Metric,
+    /// two or more appraisal outputs have equal metrics
+    EqualMetrics,
+}
+
+/// Classify the appropriate method to compare appraisal outputs
+/// given an array of appraisal outputs sorted by metric
+pub fn classify_appraisal_comparison_method(
+    appraisals_sorted_by_metric: &[&AppraisalOutput],
+) -> AppraisalComparisonMethod {
+    if appraisals_sorted_by_metric.len() >= 2
+        && appraisals_sorted_by_metric[0]
+            .compare_metric(appraisals_sorted_by_metric[1])
+            .is_eq()
+    {
+        AppraisalComparisonMethod::EqualMetrics
+    } else {
+        AppraisalComparisonMethod::Metric
+    }
 }
 
 /// Calculate LCOX for a hypothetical investment in the given asset.

tests/data/muse1_default/assets.csv

@@ -7,10 +7,10 @@ asset_id,process_id,region_id,agent_id,commission_year,decommission_year,capacit
 5,gasCCGT,R1,A1_PWR,2030,,5.831988336023331
 6,heatpump,R1,A1_RES,2035,,6.119987760024477
 7,windturbine,R1,A1_PWR,2035,,3.5999928000144
-8,gasCCGT,R1,A1_PWR,2035,2050,1.119997760004481
+8,gasCCGT,R1,A1_PWR,2035,,1.119997760004481
 9,heatpump,R1,A1_RES,2040,,8.387983224033553
 10,windturbine,R1,A1_PWR,2040,,8.387983224033553
 11,heatpump,R1,A1_RES,2045,,4.787990424019152
 12,windturbine,R1,A1_PWR,2045,,4.787990424019152
-13,heatpump,R1,A1_RES,2050,,4.823990352019292
-14,windturbine,R1,A1_PWR,2050,,16.199967600064802
+13,heatpump,R1,A1_RES,2050,,5.3999892000216
+14,windturbine,R1,A1_PWR,2050,,5.399989200021599

tests/data/muse1_default/commodity_flows.csv

@@ -513,7 +513,7 @@ milestone_year,asset_id,commodity_id,time_slice,flow
 2050,0,gas,all-year.morning,-0.0
 2050,0,gas,all-year.afternoon,-0.0
 2050,0,gas,all-year.early-peak,-0.0
-2050,0,gas,all-year.late-peak,0.47494800000000054
+2050,0,gas,all-year.late-peak,1.6773480000000012
 2050,0,gas,all-year.evening,-0.0
 2050,2,electricity,all-year.night,-0.0
 2050,2,heat,all-year.night,0.0
@@ -523,8 +523,8 @@ milestone_year,asset_id,commodity_id,time_slice,flow
 2050,2,heat,all-year.afternoon,0.0
 2050,2,electricity,all-year.early-peak,-0.0
 2050,2,heat,all-year.early-peak,0.0
-2050,2,electricity,all-year.late-peak,-1.1172000000000009
-2050,2,heat,all-year.late-peak,2.793000000000002
+2050,2,electricity,all-year.late-peak,-1.0788000000000006
+2050,2,heat,all-year.late-peak,2.6970000000000014
 2050,2,electricity,all-year.evening,-0.0
 2050,2,heat,all-year.evening,0.0
 2050,3,wind,all-year.night,-1.1171999999999997
@@ -541,16 +541,16 @@ milestone_year,asset_id,commodity_id,time_slice,flow
 2050,3,electricity,all-year.evening,1.1171999999999997
 2050,4,electricity,all-year.night,-0.0
 2050,4,heat,all-year.night,0.0
-2050,4,electricity,all-year.morning,-0.19200000000000036
-2050,4,heat,all-year.morning,0.48000000000000087
+2050,4,electricity,all-year.morning,-0.15360000000000015
+2050,4,heat,all-year.morning,0.38400000000000034
 2050,4,electricity,all-year.afternoon,-0.0
 2050,4,heat,all-year.afternoon,0.0
-2050,4,electricity,all-year.early-peak,-0.19200000000000036
-2050,4,heat,all-year.early-peak,0.48000000000000087
+2050,4,electricity,all-year.early-peak,-0.15360000000000015
+2050,4,heat,all-year.early-peak,0.38400000000000034
 2050,4,electricity,all-year.late-peak,-0.8748
 2050,4,heat,all-year.late-peak,2.187
-2050,4,electricity,all-year.evening,-0.7920000000000004
-2050,4,heat,all-year.evening,1.9800000000000009
+2050,4,electricity,all-year.evening,-0.7536
+2050,4,heat,all-year.evening,1.884
 2050,5,gas,all-year.night,-0.0
 2050,5,electricity,all-year.night,0.0
 2050,5,CO2f,all-year.night,0.0
@@ -563,18 +563,18 @@ milestone_year,asset_id,commodity_id,time_slice,flow
 2050,5,gas,all-year.early-peak,-0.0
 2050,5,electricity,all-year.early-peak,0.0
 2050,5,CO2f,all-year.early-peak,0.0
-2050,5,gas,all-year.late-peak,-0.47494800000000054
-2050,5,electricity,all-year.late-peak,0.2844000000000003
-2050,5,CO2f,all-year.late-peak,26.07094800000003
+2050,5,gas,all-year.late-peak,-1.3967880000000008
+2050,5,electricity,all-year.late-peak,0.8364000000000005
+2050,5,CO2f,all-year.late-peak,76.67278800000004
 2050,5,gas,all-year.evening,-0.0
 2050,5,electricity,all-year.evening,0.0
 2050,5,CO2f,all-year.evening,0.0
-2050,6,electricity,all-year.night,0.0
-2050,6,heat,all-year.night,-0.0
+2050,6,electricity,all-year.night,-0.0
+2050,6,heat,all-year.night,0.0
 2050,6,electricity,all-year.morning,-0.40799999999999986
 2050,6,heat,all-year.morning,1.0199999999999996
-2050,6,electricity,all-year.afternoon,0.0
-2050,6,heat,all-year.afternoon,-0.0
+2050,6,electricity,all-year.afternoon,-0.0
+2050,6,heat,all-year.afternoon,0.0
 2050,6,electricity,all-year.early-peak,-0.40799999999999986
 2050,6,heat,all-year.early-peak,1.0199999999999996
 2050,6,electricity,all-year.late-peak,-0.40799999999999986
@@ -593,12 +593,30 @@ milestone_year,asset_id,commodity_id,time_slice,flow
 2050,7,electricity,all-year.late-peak,0.24000000000000005
 2050,7,wind,all-year.evening,-0.24000000000000005
 2050,7,electricity,all-year.evening,0.24000000000000005
-2050,9,electricity,all-year.night,-0.5592
-2050,9,heat,all-year.night,1.3980000000000001
+2050,8,gas,all-year.night,-0.0
+2050,8,electricity,all-year.night,0.0
+2050,8,CO2f,all-year.night,0.0
+2050,8,gas,all-year.morning,-0.0
+2050,8,electricity,all-year.morning,0.0
+2050,8,CO2f,all-year.morning,0.0
+2050,8,gas,all-year.afternoon,-0.0
+2050,8,electricity,all-year.afternoon,0.0
+2050,8,CO2f,all-year.afternoon,0.0
+2050,8,gas,all-year.early-peak,-0.0
+2050,8,electricity,all-year.early-peak,0.0
+2050,8,CO2f,all-year.early-peak,0.0
+2050,8,gas,all-year.late-peak,-0.28056000000000025
+2050,8,electricity,all-year.late-peak,0.16800000000000015
+2050,8,CO2f,all-year.late-peak,15.400560000000015
+2050,8,gas,all-year.evening,-0.0
+2050,8,electricity,all-year.evening,0.0
+2050,8,CO2f,all-year.evening,0.0
+2050,9,electricity,all-year.night,-0.5208
+2050,9,heat,all-year.night,1.302
 2050,9,electricity,all-year.morning,-0.5592
 2050,9,heat,all-year.morning,1.3980000000000001
-2050,9,electricity,all-year.afternoon,-0.5592
-2050,9,heat,all-year.afternoon,1.3980000000000001
+2050,9,electricity,all-year.afternoon,-0.5208
+2050,9,heat,all-year.afternoon,1.302
 2050,9,electricity,all-year.early-peak,-0.5592
 2050,9,heat,all-year.early-peak,1.3980000000000001
 2050,9,electricity,all-year.late-peak,-0.5592
@@ -641,27 +659,27 @@ milestone_year,asset_id,commodity_id,time_slice,flow
 2050,12,electricity,all-year.late-peak,0.31920000000000004
 2050,12,wind,all-year.evening,-0.31920000000000004
 2050,12,electricity,all-year.evening,0.31920000000000004
-2050,13,electricity,all-year.night,-0.3215999999999998
-2050,13,heat,all-year.night,0.8039999999999994
-2050,13,electricity,all-year.morning,-0.3215999999999998
-2050,13,heat,all-year.morning,0.8039999999999994
-2050,13,electricity,all-year.afternoon,-0.3215999999999998
-2050,13,heat,all-year.afternoon,0.8039999999999994
-2050,13,electricity,all-year.early-peak,-0.3215999999999998
-2050,13,heat,all-year.early-peak,0.8039999999999994
-2050,13,electricity,all-year.late-peak,-0.3215999999999998
-2050,13,heat,all-year.late-peak,0.8039999999999994
-2050,13,electricity,all-year.evening,-0.3215999999999998
-2050,13,heat,all-year.evening,0.8039999999999994
-2050,14,wind,all-year.night,-1.0800000000000003
-2050,14,electricity,all-year.night,1.0800000000000003
-2050,14,wind,all-year.morning,-1.0800000000000003
-2050,14,electricity,all-year.morning,1.0800000000000003
-2050,14,wind,all-year.afternoon,-1.0800000000000003
-2050,14,electricity,all-year.afternoon,1.0800000000000003
-2050,14,wind,all-year.early-peak,-1.0800000000000003
-2050,14,electricity,all-year.early-peak,1.0800000000000003
-2050,14,wind,all-year.late-peak,-1.0800000000000003
-2050,14,electricity,all-year.late-peak,1.0800000000000003
-2050,14,wind,all-year.evening,-1.0800000000000003
-2050,14,electricity,all-year.evening,1.0800000000000003
+2050,13,electricity,all-year.night,-0.36000000000000004
+2050,13,heat,all-year.night,0.9
+2050,13,electricity,all-year.morning,-0.36000000000000004
+2050,13,heat,all-year.morning,0.9
+2050,13,electricity,all-year.afternoon,-0.36000000000000004
+2050,13,heat,all-year.afternoon,0.9
+2050,13,electricity,all-year.early-peak,-0.36000000000000004
+2050,13,heat,all-year.early-peak,0.9
+2050,13,electricity,all-year.late-peak,-0.36000000000000004
+2050,13,heat,all-year.late-peak,0.9
+2050,13,electricity,all-year.evening,-0.36000000000000004
+2050,13,heat,all-year.evening,0.9
+2050,14,wind,all-year.night,-0.36
+2050,14,electricity,all-year.night,0.36
+2050,14,wind,all-year.morning,-0.36
+2050,14,electricity,all-year.morning,0.36
+2050,14,wind,all-year.afternoon,-0.36
+2050,14,electricity,all-year.afternoon,0.36
+2050,14,wind,all-year.early-peak,-0.36
+2050,14,electricity,all-year.early-peak,0.36
+2050,14,wind,all-year.late-peak,-0.36
+2050,14,electricity,all-year.late-peak,0.36
+2050,14,wind,all-year.evening,-0.36
+2050,14,electricity,all-year.evening,0.36