Remove auto search tree (#1318)

* remove auto search tree

Signed-off-by: Thomas Bouquet <[email protected]>

* update json parameters

Signed-off-by: Thomas Bouquet <[email protected]>

* remove auto search tree cucumber tests

Signed-off-by: Thomas Bouquet <[email protected]>

* update doc

Signed-off-by: Thomas Bouquet <[email protected]>

* remove max-auto-depth occurrences

Signed-off-by: Thomas Bouquet <[email protected]>

* remove max-auto-depth occurrences in docs

Signed-off-by: Thomas Bouquet <[email protected]>

---------

Signed-off-by: Thomas Bouquet <[email protected]>
Co-authored-by: Godelaine <[email protected]>

Author: bqth29

docs/castor.md

@@ -130,7 +130,7 @@ As mentioned above, for NTC Capacity calculation/ CEP Validation, this stop crit
 These stop criteria only make sense for a minimum margin objective function (may it be absolute or relative).  
 
 On both stop criteria, [additional constraints](parameters.md#network-actions-optimisation-parameters) can be added, for example:
-- the maximal number of consecutive chosen network actions, also called search tree depth (for [preventive](parameters.md#max-preventive-search-tree-depth), [auto](parameters.md#max-auto-search-tree-depth) and [curative](parameters.md#max-curative-search-tree-depth) search trees),
+- the maximal number of consecutive chosen network actions, also called search tree depth (for [preventive](parameters.md#max-preventive-search-tree-depth) and [curative](parameters.md#max-curative-search-tree-depth) search trees),
 - the [minimal relative gain](parameters.md#relative-minimum-impact-threshold) of objective function between two consecutive network actions (i.e. between two search tree depths).
 
 ## Algorithm

docs/castor/performance.md

@@ -50,7 +50,7 @@ by national operators due to the timing constraint for real-time operations. For
 consideration.
 
 ---
-See also: [Preventive search stop criterion parameters](/parameters.md#max-preventive-search-tree-depth), [Automaton search stop criterion parameters](/parameters.md#max-auto-search-tree-depth), [Curative search stop criterion parameters](/parameters.md#max-curative-search-tree-depth)
+See also: [Preventive search stop criterion parameters](/parameters.md#max-preventive-search-tree-depth), [Curative search stop criterion parameters](/parameters.md#max-curative-search-tree-depth)
 
 ---
 

docs/castor/rao-steps.md

@@ -39,12 +39,12 @@ An automaton perimeter can be defined for each defined contingency. Each automat
 Optimal preventive actions selected by the preventive RAO are applied in this perimeter.
 
 While preventive and curative remedial actions are always optimized to prevent overloads in their respective perimeters,
-auto remedial actions can actually either be optimized or forced in the automaton perimeter, depending on the usage
-method. Indeed, in real life an "automated protection" is triggered when an outage takes place, even if its triggering
-causes another constraint somewhere else in the network.
+auto remedial actions are actually forced in the automaton perimeter, depending on the usage method. Indeed, in real
+life an "automated protection" is triggered when an outage takes place, even if its triggering causes another constraint
+somewhere else in the network.
 That's why, regardless of the impacts on CNECs, forced automatic remedial actions are activated if their specific
 activation conditions are met (e.g. after a given contingency).
-In CASTOR, this simulation is carried out in three stages, the first two handling specifically the automatic remedial
+In CASTOR, this simulation is carried out in two stages, the first handling specifically the automatic remedial
 actions for which there is not set-point to compute. These remedial actions are
 called [network actions](/input-data/crac/json.md#network-actions). They include topological actions, injection
 set-points, PST set-points, switch pairs.
@@ -53,22 +53,17 @@ set-points, PST set-points, switch pairs.
 
 First, all automatic network actions with a FORCED usage method are applied on the network. FORCED means that no optimization is carried out and that as long as the triggering conditions are met, the remedial action is applied.
 
-#### Automatic search tree
-
-Then, the automatic network actions which are available (i.e. not mandatory to apply) are selected by the RAO if they
-help making the network secure, using a search-tree algorithm (similar to what is done in preventive or curative).
-
 #### Automatic range actions simulation
 
-Finally, automatic range actions are applied one by one, as long as some of the perimeter's CNECs are overloaded. Range
+Then, automatic range actions are applied one by one, as long as some of the perimeter's CNECs are overloaded. Range
 actions include PSTs and HVDCs. The remedial actions' speed determines the order in which they are applied: the fastest
 range actions are simulated first. Aligned range actions are simulated simultaneously.
 
-> Note that auto range actions must have a FORCED usage method.  
+> Note that auto range actions must have a FORCED usage method too.  
 
-Automatic range actions' setpoint is computed using the results of a sensitivity analysis computation, during which the
+Automatic range actions' set-point is computed using the results of a sensitivity analysis computation, during which the
 sensitivity $\sigma$ of a range action on a CNEC is computed. By focusing on the worse overloaded CNEC, we can compute
-the automatic range action's optimal setpoint to relieve that CNEC with the following formula:
+the automatic range action's optimal set-point to relieve that CNEC with the following formula:
 
 $$\begin{equation}
 A_{optimal} = A_{current} + {sign}{(F(c)}) * \frac{\min(0, margin(c))}{\sigma}

docs/parameters.md

@@ -36,7 +36,7 @@ Examples of rao parameters with business and implementation specific parameters
 :::{group-tab} JSON
 ~~~json
 {
-  "version" : "3.0",
+  "version" : "3.1",
   "objective-function" : {
     "type" : "SECURE_FLOW",
     "unit" : "A",
@@ -73,7 +73,6 @@ Examples of rao parameters with business and implementation specific parameters
       },
       "topological-actions-optimization" : {
         "max-preventive-search-tree-depth" : 2,
-        "max-auto-search-tree-depth" : 1,
         "max-curative-search-tree-depth" : 2,
         "predefined-combinations" : [ "na1 + na2", "na4 + na5 + na6"],
         "skip-actions-far-from-most-limiting-element" : false,
@@ -182,7 +181,6 @@ rao-topological-actions-optimization:
 
 search-tree-topological-actions-optimization:
   max-preventive-search-tree-depth: 3
-  max-auto-search-tree-depth: 2
   max-curative-search-tree-depth: 3
   predefined-combinations: [ "{na1}+{na2}", "{na3}+{na4}+{na5}" ]
   relative-minimum-impact-threshold: 0.0

docs/parameters/business-parameters.md

@@ -180,7 +180,7 @@ See also: [Modelling the maximum minimum relative margin objective function](/ca
 :::{group-tab} JSON
 ~~~json
 {
-  "version" : "3.0",
+  "version" : "3.1",
   "objective-function" : {
     "type" : "SECURE_FLOW",
     "unit" : "A",

docs/parameters/implementation-specific-parameters.md

@@ -137,11 +137,6 @@ when searching for the best network actions.
 - **Usage**: maximum search-tree depth for preventive optimization.  
   Applies to the preventive RAO.
 
-##### max-auto-search-tree-depth
-- **Expected value**: integer
-- **Default value**: 2^32 -1 (max integer value)
-- **Usage**: maximum search-tree depth for the optimization of available auto network actions.
-
 ##### max-curative-search-tree-depth
 - **Expected value**: integer
 - **Default value**: 2^32 -1 (max integer value)
@@ -380,7 +375,7 @@ See also: [Modelling the maximum minimum relative margin objective function](/ca
 :::{group-tab} JSON
 ~~~json
 {
-  "version" : "3.0",
+  "version" : "3.1",
   "extensions" : {
     "open-rao-search-tree-parameters": {
       "objective-function" : {
@@ -400,7 +395,6 @@ See also: [Modelling the maximum minimum relative margin objective function](/ca
       },
       "topological-actions-optimization" : {
         "max-preventive-search-tree-depth" : 2,
-        "max-auto-search-tree-depth" : 1,
         "max-curative-search-tree-depth" : 2,
         "predefined-combinations" : [ "na1 + na2", "na4 + na5 + na6"],
         "skip-actions-far-from-most-limiting-element" : false,
@@ -498,7 +492,6 @@ search-tree-linear-optimization-solver:
 
 search-tree-topological-actions-optimization:
   max-preventive-search-tree-depth: 3
-  max-auto-search-tree-depth: 2
   max-curative-search-tree-depth: 3
   predefined-combinations: [ "{na1}+{na2}", "{na3}+{na4}+{na5}" ]
   relative-minimum-impact-threshold: 0.0

python-util/rao_parameter_modification.py

@@ -134,7 +134,7 @@ def new_rao_param(data: dict, file_path: str) -> dict:
             "hvdc-sensitivity-threshold", "injection-ra-sensitivity-threshold",
             "ra-range-shrinking", "linear-optimization-solver"])
         move_to_extension(data, "topological-actions-optimization",
-            ["max-preventive-search-tree-depth", "max-auto-search-tree-depth",
+            ["max-preventive-search-tree-depth",
             "max-curative-search-tree-depth", "predefined-combinations",
             "skip-actions-far-from-most-limiting-element",
             "max-number-of-boundaries-for-skipping-actions"])

ra-optimisation/rao-api/src/main/java/com/powsybl/openrao/raoapi/RaoParametersCommons.java

@@ -16,7 +16,7 @@ public final class RaoParametersCommons {
     private RaoParametersCommons() {
     }
 
-    public static final String RAO_PARAMETERS_VERSION = "3.0";
+    public static final String RAO_PARAMETERS_VERSION = "3.1";
 
     // header
     public static final String VERSION = "version";
@@ -57,7 +57,6 @@ private RaoParametersCommons() {
     public static final String ST_TOPOLOGICAL_ACTIONS_OPTIMIZATION_SECTION = "search-tree-topological-actions-optimization";
 
     public static final String MAX_PREVENTIVE_SEARCH_TREE_DEPTH = "max-preventive-search-tree-depth";
-    public static final String MAX_AUTO_SEARCH_TREE_DEPTH = "max-auto-search-tree-depth";
     public static final String MAX_CURATIVE_SEARCH_TREE_DEPTH = "max-curative-search-tree-depth";
     public static final String PREDEFINED_COMBINATIONS = "predefined-combinations";
     public static final String RELATIVE_MINIMUM_IMPACT_THRESHOLD = "relative-minimum-impact-threshold";

ra-optimisation/rao-api/src/main/java/com/powsybl/openrao/raoapi/json/extensions/JsonTopoOptimizationParameters.java

@@ -29,7 +29,6 @@ private JsonTopoOptimizationParameters() {
     static void serialize(OpenRaoSearchTreeParameters parameters, JsonGenerator jsonGenerator) throws IOException {
         jsonGenerator.writeObjectFieldStart(TOPOLOGICAL_ACTIONS_OPTIMIZATION);
         jsonGenerator.writeNumberField(MAX_PREVENTIVE_SEARCH_TREE_DEPTH, parameters.getTopoOptimizationParameters().getMaxPreventiveSearchTreeDepth());
-        jsonGenerator.writeNumberField(MAX_AUTO_SEARCH_TREE_DEPTH, parameters.getTopoOptimizationParameters().getMaxAutoSearchTreeDepth());
         jsonGenerator.writeNumberField(MAX_CURATIVE_SEARCH_TREE_DEPTH, parameters.getTopoOptimizationParameters().getMaxCurativeSearchTreeDepth());
         jsonGenerator.writeFieldName(PREDEFINED_COMBINATIONS);
         jsonGenerator.writeStartArray();
@@ -53,10 +52,6 @@ static void deserialize(JsonParser jsonParser, OpenRaoSearchTreeParameters searc
                     jsonParser.nextToken();
                     searchTreeParameters.getTopoOptimizationParameters().setMaxPreventiveSearchTreeDepth(jsonParser.getIntValue());
                     break;
-                case MAX_AUTO_SEARCH_TREE_DEPTH:
-                    jsonParser.nextToken();
-                    searchTreeParameters.getTopoOptimizationParameters().setMaxAutoSearchTreeDepth(jsonParser.getIntValue());
-                    break;
                 case MAX_CURATIVE_SEARCH_TREE_DEPTH:
                     jsonParser.nextToken();
                     searchTreeParameters.getTopoOptimizationParameters().setMaxCurativeSearchTreeDepth(jsonParser.getIntValue());

ra-optimisation/rao-api/src/main/java/com/powsybl/openrao/raoapi/parameters/extensions/SearchTreeRaoTopoOptimizationParameters.java

@@ -32,7 +32,6 @@ public class SearchTreeRaoTopoOptimizationParameters {
     private static final int DEFAULT_MAX_NUMBER_OF_BOUNDARIES_FOR_SKIPPING_ACTIONS = 2;
     // Attributes
     private int maxPreventiveSearchTreeDepth = DEFAULT_MAX_SEARCH_TREE_DEPTH;
-    private int maxAutoSearchTreeDepth = DEFAULT_MAX_SEARCH_TREE_DEPTH;
     private int maxCurativeSearchTreeDepth = DEFAULT_MAX_SEARCH_TREE_DEPTH;
     private List<List<String>> predefinedCombinations = DEFAULT_PREDEFINED_COMBINATIONS;
     private boolean skipActionsFarFromMostLimitingElement = DEFAULT_SKIP_ACTIONS_FAR_FROM_MOST_LIMITING_ELEMENT;
@@ -42,10 +41,6 @@ public void setMaxPreventiveSearchTreeDepth(int maxPreventiveSearchTreeDepth) {
         this.maxPreventiveSearchTreeDepth = maxPreventiveSearchTreeDepth;
     }
 
-    public void setMaxAutoSearchTreeDepth(int maxAutoSearchTreeDepth) {
-        this.maxAutoSearchTreeDepth = maxAutoSearchTreeDepth;
-    }
-
     public void setMaxCurativeSearchTreeDepth(int maxCurativeSearchTreeDepth) {
         this.maxCurativeSearchTreeDepth = maxCurativeSearchTreeDepth;
     }
@@ -71,10 +66,6 @@ public int getMaxPreventiveSearchTreeDepth() {
         return maxPreventiveSearchTreeDepth;
     }
 
-    public int getMaxAutoSearchTreeDepth() {
-        return maxAutoSearchTreeDepth;
-    }
-
     public int getMaxCurativeSearchTreeDepth() {
         return maxCurativeSearchTreeDepth;
     }
@@ -97,7 +88,6 @@ public static SearchTreeRaoTopoOptimizationParameters load(PlatformConfig platfo
         platformConfig.getOptionalModuleConfig(ST_TOPOLOGICAL_ACTIONS_OPTIMIZATION_SECTION)
                 .ifPresent(config -> {
                     parameters.setMaxPreventiveSearchTreeDepth(config.getIntProperty(MAX_PREVENTIVE_SEARCH_TREE_DEPTH, DEFAULT_MAX_SEARCH_TREE_DEPTH));
-                    parameters.setMaxAutoSearchTreeDepth(config.getIntProperty(MAX_AUTO_SEARCH_TREE_DEPTH, DEFAULT_MAX_SEARCH_TREE_DEPTH));
                     parameters.setMaxCurativeSearchTreeDepth(config.getIntProperty(MAX_CURATIVE_SEARCH_TREE_DEPTH, DEFAULT_MAX_SEARCH_TREE_DEPTH));
                     parameters.setPredefinedCombinations(ParametersUtil.convertListToListOfList(config.getStringListProperty(PREDEFINED_COMBINATIONS, ParametersUtil.convertListOfListToList(DEFAULT_PREDEFINED_COMBINATIONS))));
                     parameters.setSkipActionsFarFromMostLimitingElement(config.getBooleanProperty(SKIP_ACTIONS_FAR_FROM_MOST_LIMITING_ELEMENT, DEFAULT_SKIP_ACTIONS_FAR_FROM_MOST_LIMITING_ELEMENT));
@@ -113,13 +103,6 @@ public static int getMaxPreventiveSearchTreeDepth(RaoParameters parameters) {
         return DEFAULT_MAX_SEARCH_TREE_DEPTH;
     }
 
-    public static int getMaxAutoSearchTreeDepth(RaoParameters parameters) {
-        if (parameters.hasExtension(OpenRaoSearchTreeParameters.class)) {
-            return parameters.getExtension(OpenRaoSearchTreeParameters.class).getTopoOptimizationParameters().getMaxAutoSearchTreeDepth();
-        }
-        return DEFAULT_MAX_SEARCH_TREE_DEPTH;
-    }
-
     public static int getMaxCurativeSearchTreeDepth(RaoParameters parameters) {
         if (parameters.hasExtension(OpenRaoSearchTreeParameters.class)) {
             return parameters.getExtension(OpenRaoSearchTreeParameters.class).getTopoOptimizationParameters().getMaxCurativeSearchTreeDepth();

ra-optimisation/rao-api/src/test/java/com/powsybl/openrao/raoapi/json/JsonRaoParametersTest.java

@@ -71,7 +71,6 @@ void roundTrip() throws IOException {
         searchTreeParameters.getRangeActionsOptimizationParameters().setRaRangeShrinking(RaRangeShrinking.ENABLED);
         // TopologicalActions optimization parameters
         searchTreeParameters.getTopoOptimizationParameters().setMaxPreventiveSearchTreeDepth(10);
-        searchTreeParameters.getTopoOptimizationParameters().setMaxAutoSearchTreeDepth(3);
         searchTreeParameters.getTopoOptimizationParameters().setMaxCurativeSearchTreeDepth(10);
         parameters.getTopoOptimizationParameters().setRelativeMinImpactThreshold(0.1);
         parameters.getTopoOptimizationParameters().setAbsoluteMinImpactThreshold(20);
@@ -130,7 +129,6 @@ void update() {
         assertEquals(ObjectiveFunctionParameters.ObjectiveFunctionType.MAX_MIN_MARGIN, parameters.getObjectiveFunctionParameters().getType());
         OpenRaoSearchTreeParameters searchTreeParameters = parameters.getExtension(OpenRaoSearchTreeParameters.class);
         assertEquals(5, searchTreeParameters.getTopoOptimizationParameters().getMaxPreventiveSearchTreeDepth(), DOUBLE_TOLERANCE);
-        assertEquals(2, searchTreeParameters.getTopoOptimizationParameters().getMaxAutoSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(5, searchTreeParameters.getTopoOptimizationParameters().getMaxCurativeSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(0, parameters.getTopoOptimizationParameters().getRelativeMinImpactThreshold(), DOUBLE_TOLERANCE);
         assertEquals(1, parameters.getTopoOptimizationParameters().getAbsoluteMinImpactThreshold(), DOUBLE_TOLERANCE);

ra-optimisation/rao-api/src/test/java/com/powsybl/openrao/raoapi/parameters/RaoParametersConfigTest.java

@@ -96,7 +96,6 @@ void checkTopoActionsOptimizationConfig() {
         topoActionsModuleConfig.setStringProperty("absolute-minimum-impact-threshold", Objects.toString(22));
         MapModuleConfig topoActionsModuleConfigExt = platformCfg.createModuleConfig("search-tree-topological-actions-optimization");
         topoActionsModuleConfigExt.setStringProperty("max-preventive-search-tree-depth", Objects.toString(3));
-        topoActionsModuleConfigExt.setStringProperty("max-auto-search-tree-depth", Objects.toString(2));
         topoActionsModuleConfigExt.setStringProperty("max-curative-search-tree-depth", Objects.toString(3));
         topoActionsModuleConfigExt.setStringListProperty("predefined-combinations", List.of("{na12} + {na22}", "{na41} + {na5} + {na6}"));
         topoActionsModuleConfigExt.setStringProperty("skip-actions-far-from-most-limiting-element", Objects.toString(true));
@@ -105,7 +104,6 @@ void checkTopoActionsOptimizationConfig() {
         TopoOptimizationParameters params = parameters.getTopoOptimizationParameters();
         SearchTreeRaoTopoOptimizationParameters paramsExt = parameters.getExtension(OpenRaoSearchTreeParameters.class).getTopoOptimizationParameters();
         assertEquals(3, paramsExt.getMaxPreventiveSearchTreeDepth(), DOUBLE_TOLERANCE);
-        assertEquals(2, paramsExt.getMaxAutoSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(3, paramsExt.getMaxCurativeSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(List.of(List.of("na12", "na22"), List.of("na41", "na5", "na6")), paramsExt.getPredefinedCombinations());
         assertEquals(0.9, params.getRelativeMinImpactThreshold(), DOUBLE_TOLERANCE);

ra-optimisation/rao-api/src/test/java/com/powsybl/openrao/raoapi/parameters/RaoParametersYamlConfigTest.java

@@ -66,7 +66,6 @@ void testConfigWithExtensions() throws IOException {
 
         TopoOptimizationParameters topoOptimizationParameters = parameters.getTopoOptimizationParameters();
         assertEquals(3, searchTreeParameters.getTopoOptimizationParameters().getMaxPreventiveSearchTreeDepth(), DOUBLE_TOLERANCE);
-        assertEquals(2, searchTreeParameters.getTopoOptimizationParameters().getMaxAutoSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(3, searchTreeParameters.getTopoOptimizationParameters().getMaxCurativeSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(List.of(List.of("na1", "na2"), List.of("na3", "na4", "na5")), searchTreeParameters.getTopoOptimizationParameters().getPredefinedCombinations());
         assertEquals(0.02, topoOptimizationParameters.getRelativeMinImpactThreshold(), DOUBLE_TOLERANCE);
@@ -177,7 +176,6 @@ void testConfigWithPartialExtensions() throws IOException {
 
         TopoOptimizationParameters topoOptimizationParameters = parameters.getTopoOptimizationParameters();
         assertEquals(3, searchTreeParameters.getTopoOptimizationParameters().getMaxPreventiveSearchTreeDepth(), DOUBLE_TOLERANCE);
-        assertEquals(2, searchTreeParameters.getTopoOptimizationParameters().getMaxAutoSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(3, searchTreeParameters.getTopoOptimizationParameters().getMaxCurativeSearchTreeDepth(), DOUBLE_TOLERANCE);
         assertEquals(List.of(List.of("na1", "na2"), List.of("na3", "na4", "na5")), searchTreeParameters.getTopoOptimizationParameters().getPredefinedCombinations());
         assertEquals(0.02, topoOptimizationParameters.getRelativeMinImpactThreshold(), DOUBLE_TOLERANCE);

ra-optimisation/rao-api/src/test/resources/RaoParametersError_v2.json

@@ -1,4 +1,4 @@
 {
-  "version" : "3.0",
+  "version" : "3.1",
   "unknownField" : "abcd"
 }

ra-optimisation/rao-api/src/test/resources/RaoParametersSet_v2.json

@@ -1,5 +1,5 @@
 {
-  "version" : "3.0",
+  "version" : "3.1",
   "objective-function" : {
     "type" : "MAX_MIN_MARGIN",
     "unit" : "A",
@@ -47,7 +47,6 @@
       },
       "topological-actions-optimization" : {
         "max-preventive-search-tree-depth" : 10,
-        "max-auto-search-tree-depth" : 3,
         "max-curative-search-tree-depth" : 10,
         "predefined-combinations" : [ [ "na-id-1", "na-id-2" ], [ "na-id-1", "na-id-3", "na-id-4" ] ],
         "skip-actions-far-from-most-limiting-element" : false,

ra-optimisation/rao-api/src/test/resources/RaoParametersWithExtension_v2.json

@@ -1,5 +1,5 @@
 {
-  "version" : "3.0",
+  "version" : "3.1",
   "objective-function" : {
     "type" : "SECURE_FLOW",
     "unit" : "MW",