[Issue-155] User setting of NULLCOST parameter

metrix-integration/src/main/groovy/com/powsybl/metrix/integration/ParametersData.groovy

@@ -36,6 +36,7 @@ class ParametersData {
     Float lossOfLoadCost
     Float curativeLossOfLoadCost
     Float curativeLossOfGenerationCost
+    Float generatorMinCost
     Float contingenciesProbability
     Integer nominalU
     Integer nbMaxIteration
@@ -143,6 +144,10 @@ class ParametersData {
         this.curativeLossOfGenerationCost = lossOfGenerationCost
     }
 
+    void generatorMinCost(Float generatorMinCost) {
+        this.generatorMinCost = generatorMinCost
+    }
+
     void contingenciesProbability(Float contingenciesProbability) {
         this.contingenciesProbability = contingenciesProbability
     }
@@ -269,6 +274,9 @@ class ParametersData {
         if (spec.curativeLossOfGenerationCost != null) {
             parameters.setCurativeLossOfGenerationCost(spec.curativeLossOfGenerationCost)
         }
+        if (spec.generatorMinCost != null) {
+            parameters.setGeneratorMinCost(spec.generatorMinCost)
+        }
         if (spec.contingenciesProbability != null) {
             parameters.setContingenciesProbability(spec.contingenciesProbability)
         }

metrix-integration/src/main/java/com/powsybl/metrix/integration/MetrixParameters.java

@@ -76,6 +76,7 @@ public static MetrixParameters load() {
     private Float curativeLossOfLoadCost = null;
     private Float curativeLossOfGenerationCost = null;
     private Float contingenciesProbability = null;
+    private Float generatorMinCost = null;
 
     public MetrixParameters() {
         this(DEFAULT_COMPUTATION_TYPE, DEFAULT_LOSS_FACTOR, DEFAULT_NOMINAL_U);
@@ -239,6 +240,11 @@ private Float getContingenciesProbability() {
         return contingenciesProbability;
     }
 
+    @JsonGetter
+    private Float getGeneratorMinCost() {
+        return generatorMinCost;
+    }
+
     public MetrixComputationType getComputationType() {
         return computationType;
     }
@@ -529,6 +535,17 @@ public MetrixParameters setCurativeLossOfGenerationCost(Float curativeLossOfGene
         return this;
     }
 
+    // Generator min cost
+    @JsonIgnore
+    public Optional<Float> getOptionalGeneratorMinCost() {
+        return Optional.ofNullable(generatorMinCost);
+    }
+
+    public MetrixParameters setGeneratorMinCost(Float generatorMinCost) {
+        this.generatorMinCost = generatorMinCost;
+        return this;
+    }
+
     // Outage probability
     @JsonIgnore
     public Optional<Float> getOptionalContingenciesProbability() {
@@ -617,6 +634,7 @@ public int hashCode() {
                     lossOfLoadCost,
                     curativeLossOfLoadCost,
                     curativeLossOfGenerationCost,
+                    generatorMinCost,
                     contingenciesProbability,
                     maxSolverTime,
                     nbMaxIteration,
@@ -654,6 +672,7 @@ public boolean equals(Object obj) {
                     Objects.equals(lossOfLoadCost, other.lossOfLoadCost) &&
                     Objects.equals(curativeLossOfLoadCost, other.curativeLossOfLoadCost) &&
                     Objects.equals(curativeLossOfGenerationCost, other.curativeLossOfGenerationCost) &&
+                    Objects.equals(generatorMinCost, other.generatorMinCost) &&
                     Objects.equals(contingenciesProbability, other.contingenciesProbability) &&
                     Objects.equals(maxSolverTime, other.maxSolverTime) &&
                     Objects.equals(nbMaxIteration, other.nbMaxIteration) &&
@@ -696,6 +715,7 @@ public String toString() {
         getOptionalLossOfLoadCost().ifPresent(value -> builder.put("lossOfLoadCost", value));
         getOptionalCurativeLossOfLoadCost().ifPresent(value -> builder.put("curativeLossOfLoadCost", value));
         getOptionalCurativeLossOfGenerationCost().ifPresent(value -> builder.put("curativeLossOfGenerationCost", value));
+        getOptionalGeneratorMinCost().ifPresent(value -> builder.put("generatorMinCost", value));
         getOptionalContingenciesProbability().ifPresent(value -> builder.put("contingenciesProbability", value));
         getOptionalMaxSolverTime().ifPresent(value -> builder.put("maxSolverTime", value));
         getOptionalNbMaxIteration().ifPresent(value -> builder.put("nbMaxIteration", value));

metrix-integration/src/main/java/com/powsybl/metrix/integration/dataGenerator/MetrixInputData.java

@@ -239,6 +239,7 @@ private void writeOptions(MetrixDie die) {
         parameters.getOptionalLossOfLoadCost().ifPresent(value -> die.setFloat("COUTDEFA", value));
         parameters.getOptionalCurativeLossOfLoadCost().ifPresent(value -> die.setFloat("COUENDCU", value));
         parameters.getOptionalCurativeLossOfGenerationCost().ifPresent(value -> die.setFloat("COUENECU", value));
+        parameters.getOptionalGeneratorMinCost().ifPresent(value -> die.setFloat("NULLCOST", value));
         parameters.getOptionalContingenciesProbability().ifPresent(value -> die.setFloat("PROBAINC", value));
         parameters.getOptionalMaxSolverTime().ifPresent(value -> die.setInt("MAXSOLVE", value));
         parameters.getOptionalNbMaxIteration().ifPresent(value -> die.setInt("NBMAXMIT", value));

metrix-integration/src/test/java/com/powsybl/metrix/integration/MetrixDslDataLoaderTest.java

@@ -530,6 +530,7 @@ void testParameters() throws IOException {
                     "    lossOfLoadCost 12000",
                     "    curativeLossOfLoadCost 26000",
                     "    curativeLossOfGenerationCost 100",
+                    "    generatorMinCost 0.5",
                     "    contingenciesProbability 0.01",
                     "    maxSolverTime (-1)",
                     "    nominalU 103",
@@ -574,6 +575,7 @@ void testParameters() throws IOException {
             assertEquals(12000f, parameters.getOptionalLossOfLoadCost().get(), 0f);
             assertEquals(26000f, parameters.getOptionalCurativeLossOfLoadCost().get(), 0f);
             assertEquals(100f, parameters.getOptionalCurativeLossOfGenerationCost().get(), 0f);
+            assertEquals(0.5f, parameters.getOptionalGeneratorMinCost().get(), 0f);
             assertEquals(0.01f, parameters.getOptionalContingenciesProbability().get(), 0f);
             assertEquals(4, parameters.getOptionalNbMaxIteration().getAsInt());
             assertEquals(2, parameters.getOptionalNbMaxCurativeAction().getAsInt());

metrix-integration/src/test/java/com/powsybl/metrix/integration/MetrixInputTest.java

@@ -314,6 +314,7 @@ void metrixInputTest() throws IOException {
                 .setLossOfLoadCost(13000f)
                 .setCurativeLossOfLoadCost(26000f)
                 .setCurativeLossOfGenerationCost(100f)
+                .setGeneratorMinCost(-100.5f)
                 .setContingenciesProbability(0.001f)
                 .setNbMaxIteration(3)
                 .setNbMaxCurativeAction(4)

metrix-integration/src/test/java/com/powsybl/metrix/integration/MetrixParametersTest.java

@@ -48,6 +48,7 @@ private void checkOptionalParametersAreNotPresent(MetrixParameters p) {
         assertFalse(p.getOptionalLossOfLoadCost().isPresent());
         assertFalse(p.getOptionalCurativeLossOfLoadCost().isPresent());
         assertFalse(p.getOptionalCurativeLossOfGenerationCost().isPresent());
+        assertFalse(p.getOptionalGeneratorMinCost().isPresent());
         assertFalse(p.getOptionalContingenciesProbability().isPresent());
         assertFalse(p.isWithLostLoadDetailedResultsOnContingency().isPresent());
     }
@@ -145,6 +146,7 @@ void optionalParametersTest() {
             .setLossOfLoadCost(9000f)
             .setCurativeLossOfLoadCost(1000f)
             .setCurativeLossOfGenerationCost(11000f)
+            .setGeneratorMinCost(1.5f)
             .setContingenciesProbability(0.001f);
 
         assertFalse(p.isWithGridCost().get());
@@ -164,6 +166,7 @@ void optionalParametersTest() {
         assertEquals(0.0001f, p.getOptionalPstCostPenality().get(), 0f);
         assertEquals(0.01f, p.getOptionalHvdcCostPenality().get(), 0f);
         assertEquals(9000f, p.getOptionalLossOfLoadCost().get(), 0f);
+        assertEquals(1.5f, p.getOptionalGeneratorMinCost().get(), 0f);
         assertEquals(1000f, p.getOptionalCurativeLossOfLoadCost().get(), 0f);
         assertEquals(11000f, p.getOptionalCurativeLossOfGenerationCost().get(), 0f);
         assertEquals(0.001f, p.getOptionalContingenciesProbability().get(), 0f);

metrix-integration/src/test/resources/simpleNetwork.json

@@ -697,6 +697,15 @@
       "firstValueIndex" : 1,
       "lastValueIndex" : 1,
       "values" : [ 100.0 ]
+    }, {
+      "name" : "NULLCOST",
+      "type" : "FLOAT",
+      "valueCount" : 1,
+      "firstIndexMaxValue" : 1,
+      "secondIndexMaxValue" : 1,
+      "firstValueIndex" : 1,
+      "lastValueIndex" : 1,
+      "values" : [ -100.5 ]
     }, {
       "name" : "PROBAINC",
       "type" : "FLOAT",

metrix-simulator/src/calculecrirecontraintesdodu.cpp

@@ -231,20 +231,20 @@ int Calculer::ecrireContraintesDeBordGroupesDodu()
                     // A la hausse
                     pbXmin_[numVar] = 0.0;
                     pbXmax_[numVar] = grp->puisMax_ - grp->prodPobj_;
-                    pbCoutLineaire_[numVar] = std::max(grp->coutHausseHR_, config::configuration().noiseCost())
-                                              + config::configuration().adequacyCostOffset();
+                    pbCoutLineaire_[numVar] = std::max(grp->coutHausseHR_
+                    + config::configuration().adequacyCostOffset(), config::configuration().noiseCost());
                     // A la baisse
                     pbXmin_[numVar + 1] = 0.0;
                     pbXmax_[numVar + 1] = grp->prodPobj_ - grp->puisMin_;
-                    pbCoutLineaire_[numVar + 1] = std::max(grp->coutBaisseHR_, config::configuration().noiseCost())
-                                                  + config::configuration().adequacyCostOffset();
+                    pbCoutLineaire_[numVar + 1] = std::max(grp->coutBaisseHR_
+                    + config::configuration().adequacyCostOffset(), config::configuration().noiseCost());
 
                 } else { // P_min>P_0
                     // A la hausse
                     pbXmin_[numVar] = grp->puisMin_ - grp->prodPobj_;
                     pbXmax_[numVar] = grp->puisMax_ - grp->prodPobj_;
-                    pbCoutLineaire_[numVar] = std::max(grp->coutHausseHR_, config::configuration().noiseCost())
-                                              + config::configuration().adequacyCostOffset();
+                    pbCoutLineaire_[numVar] = std::max(grp->coutHausseHR_
+                    + config::configuration().adequacyCostOffset(), config::configuration().noiseCost());
                     // A la baisse
                     pbXmin_[numVar + 1] = 0.0;
                     pbXmax_[numVar + 1] = 0.0;
@@ -255,13 +255,13 @@ int Calculer::ecrireContraintesDeBordGroupesDodu()
                 // A la hausse
                 pbXmin_[numVar] = 0.;
                 pbXmax_[numVar] = grp->puisMax_ - grp->prodPobj_;
-                pbCoutLineaire_[numVar] = std::max(grp->coutHausseHR_, config::configuration().noiseCost())
-                                          + config::configuration().adequacyCostOffset();
+                pbCoutLineaire_[numVar] = std::max(grp->coutHausseHR_
+                + config::configuration().adequacyCostOffset(), config::configuration().noiseCost());
                 // A la baisse
                 pbXmin_[numVar + 1] = 0.;
                 pbXmax_[numVar + 1] = grp->prodPobj_ - grp->puisMin_;
-                pbCoutLineaire_[numVar + 1] = std::max(grp->coutBaisseHR_, config::configuration().noiseCost())
-                                              + config::configuration().adequacyCostOffset();
+                pbCoutLineaire_[numVar + 1] = std::max(grp->coutBaisseHR_
+                + config::configuration().adequacyCostOffset(), config::configuration().noiseCost());
             }
         } else { // Groupe deconnecte ou fixe HR
             // A la hausse
@@ -294,13 +294,13 @@ void Calculer::ajoutRedispatchCostOffsetConsos()
         const auto& conso = cIt->second;
         if (conso->numVarConso_ >= 0) {
             if (conso->valeur_ >= 0) {
-                pbCoutLineaire_[conso->numVarConso_] = std::max(conso->cout_, config.noiseCost())
-                                                       + config.redispatchCostOffset();
+                pbCoutLineaire_[conso->numVarConso_] = std::max(conso->cout_ + config.redispatchCostOffset(),
+                config.noiseCost());
                 pbCoutLineaireSansOffset_[conso->numVarConso_] = conso->cout_;
             } else {
                 // consumption cost is negative so we use min instead of max to compare to cost noise
-                pbCoutLineaire_[conso->numVarConso_] = -(std::min(conso->cout_, -config.noiseCost())
-                                                         + config.redispatchCostOffset());
+                pbCoutLineaire_[conso->numVarConso_] = -(std::min(conso->cout_ + config.redispatchCostOffset(),
+                -config.noiseCost()));
                 pbCoutLineaireSansOffset_[conso->numVarConso_] = conso->cout_;
             }
         }
@@ -323,13 +323,13 @@ int Calculer::ecrireContraintesDeBordConsosDodu()
             if (consoNodale >= 0) {
                 pbXmin_[numVar] = 0.0;
                 pbXmax_[numVar] = conso->seuil_ * consoNodale;
-                pbCoutLineaire_[numVar] = std::max(conso->cout_, config::configuration().noiseCost())
-                                          + config::configuration().adequacyCostOffset();
+                pbCoutLineaire_[numVar] = std::max(conso->cout_ + config::configuration().adequacyCostOffset(),
+                config::configuration().noiseCost());
             } else {
                 pbXmin_[numVar] = conso->seuil_ * consoNodale;
                 pbXmax_[numVar] = 0.0;
-                pbCoutLineaire_[numVar] = -(std::max(conso->cout_, config::configuration().noiseCost())
-                                            + config::configuration().adequacyCostOffset());
+                pbCoutLineaire_[numVar] = -(std::max(conso->cout_ + config::configuration().adequacyCostOffset(),
+                config::configuration().noiseCost()));
             }
 
             if (pbXmax_[numVar] - pbXmin_[numVar] < config::constants::epsilon) {

metrix-simulator/tests/divers/redispatching_offset/readme.txt

@@ -2,10 +2,16 @@
 Redispatching offset test case :
 =================================
 
-In the general case, the adequacy and the rediqpatch cost offset are defined to ensure the user that no opportunity cost will lead metrix to choose generation means instead of network means. Indeed, when downward cost are negative on the balancing mechanism, it can happen that it is more interesting to decrease this geenration unit and increase another upward offer, for economical reason only. For example, if a generation unit produces at minimal power for 15 euros/MW, and another generation unit produces at maximal power at -25 euros/MW, Metrix will increase the first one and decrease the second as it allows a gain of 10 euros/MW.
-Hence, the two options adequacyCostOffset and redispatchingCostOffset allows to define a translation cost for all generation units, in order to prevent opportunity while keeping the Metrix final cost indicators identical. 
+In the general case, the adequacy and the redispatch cost offset are defined to ensure the user that no opportunity cost
+will lead Metrix to choose generation means instead of network means. Indeed, when downward cost are negative on the
+balancing mechanism, it can happen that it is more interesting to decrease this generation unit and increase another
+upward offer, for economical reason only. For example, if a generation unit produces at minimal power for 15 euros/MW,
+and another generation unit produces at maximal power at -25 euros/MW, Metrix will increase the first one and decrease
+the second as it allows a gain of 10 euros/MW.
+Hence, the two options adequacyCostOffset and redispatchingCostOffset allows to define a translation cost for all
+generation units, in order to prevent opportunity while keeping the Metrix final cost indicators identical.
 
-In this particular case, we aims to validate this "no opportunity" behavior in the special case of negative load (demand side response). 
+In this particular case, we aim to validate this "no opportunity" behavior in the special case of negative load (demand side response).
 - when load is positive (load shedding) the cost offset is positive and added to the load cost. 
 - when load is negative, the cost offset is negative and withdrawn to the load cost (which is also negative).
 By doing this in the adequacy phase and redispatch phase, we ensure that Metrix will not use the load as first means for constraint.

metrix-simulator/tests_reference/groupes/cost_offsets/metrixOut.txt

@@ -52,11 +52,11 @@ Résultats en volume (MW)
 Volume de production =     960.0000 MW
 Volume de délestage  =       0.0000 MW
 Résultats sur les couts
-Cout associé aux groupes       :     630.0000
+Cout associé aux groupes       :     600.0000
 Cout associé au délestage      :       0.0000
 Cout de pénalisation TD & HVDC :       0.0000
 Cout des écarts de transit     :       0.0000
-Valeur de la fonction objectif :     630.0000
+Valeur de la fonction objectif :     600.0000
 
 Prise en compte des couts avec reseau
 Micro itération 1 (nombre de contraintes 1)
@@ -88,11 +88,11 @@ Résultats en volume (MW)
 Volume de production =     960.0000 MW
 Volume de délestage  =       0.0000 MW
 Résultats sur les couts
-Cout associé aux groupes       :     630.0000
+Cout associé aux groupes       :     600.0000
 Cout associé au délestage      :       0.0000
 Cout de pénalisation TD & HVDC :       0.0000
 Cout des écarts de transit     :       0.0000
-Valeur de la fonction objectif :     630.0000
+Valeur de la fonction objectif :     600.0000
 
 Prise en compte des couts avec reseau
 Micro itération 1 (nombre de contraintes 1)
@@ -124,11 +124,11 @@ Résultats en volume (MW)
 Volume de production =     960.0000 MW
 Volume de délestage  =       0.0000 MW
 Résultats sur les couts
-Cout associé aux groupes       :     630.0000
+Cout associé aux groupes       :     600.0000
 Cout associé au délestage      :       0.0000
 Cout de pénalisation TD & HVDC :       0.0000
 Cout des écarts de transit     :       0.0000
-Valeur de la fonction objectif :     630.0000
+Valeur de la fonction objectif :     600.0000
 
 Prise en compte des couts avec reseau
 Micro itération 1 (nombre de contraintes 1)
@@ -178,11 +178,11 @@ Résultats en volume (MW)
 Volume de production =     960.0000 MW
 Volume de délestage  =       0.0000 MW
 Résultats sur les couts
-Cout associé aux groupes       :     630.0000
+Cout associé aux groupes       :     600.0000
 Cout associé au délestage      :       0.0000
 Cout de pénalisation TD & HVDC :       0.0000
 Cout des écarts de transit     :       0.0000
-Valeur de la fonction objectif :     630.0000
+Valeur de la fonction objectif :     600.0000
 
 Prise en compte des couts avec reseau
 Micro itération 1 (nombre de contraintes 1)
@@ -232,11 +232,11 @@ Résultats en volume (MW)
 Volume de production =     960.0000 MW
 Volume de délestage  =       0.0000 MW
 Résultats sur les couts
-Cout associé aux groupes       :     630.0000
+Cout associé aux groupes       :     600.0000
 Cout associé au délestage      :       0.0000
 Cout de pénalisation TD & HVDC :       0.0000
 Cout des écarts de transit     :       0.0000
-Valeur de la fonction objectif :     630.0000
+Valeur de la fonction objectif :     600.0000
 
 Prise en compte des couts avec reseau
 Micro itération 1 (nombre de contraintes 1)