Initial Cariflex project

- 40 FlexMeasures assets (10 PV, 10 Bat, 10 Chg, 10 EV)
- Geolocated on Martinique
- Documentation: architecture, deployment, concepts
- Standards: Flex Ready, S2, OpenADR, EPEX SPOT
- R&D tools: HAMLET, OPLEM, lemlab
- Map patch: Mapbox -> OpenStreetMap

scripts/relocate_assets.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python3
+"""Re-localise les assets Cariflex sur la Martinique."""
+import subprocess, random
+
+def run_sql(query):
+    subprocess.run([
+        "docker", "exec", "flexmeasures-db", "psql", "-U", "flexmeasures", "-d", "flexmeasures",
+        "-t", "-c", query
+    ], capture_output=True, text=True)
+
+# Martinique bounding box (approximate)
+# Lat: 14.38 to 14.87, Lon: -61.25 to -60.82
+# But we need to avoid the sea - use known land areas
+
+# Realistic zones on Martinique (lat, lon) - major towns and industrial zones
+ZONES = [
+    # Fort-de-France area (capital, dense urban)
+    (14.6091, -61.2155),  # Fort-de-France center
+    (14.6150, -61.2080),  # Fort-de-France north
+    (14.6050, -61.2200),  # Fort-de-France south
+    (14.6200, -61.2000),  # Fort-de-France east
+    (14.5950, -61.2100),  # Fort-de-France west
+    # Le Lamentin (airport, industrial zone)
+    (14.6100, -61.0100),  # Le Lamentin center
+    (14.6150, -61.0050),  # Airport area
+    (14.6050, -61.0200),  # Industrial zone
+    # Sainte-Marie (north-east)
+    (14.7800, -60.9800),  # Sainte-Marie town
+    (14.7900, -60.9700),  # North coast
+    # Le Robert (north-east coast)
+    (14.6800, -60.9400),  # Le Robert town
+    # Le François (south-east coast)
+    (14.6600, -60.9000),  # Le François town
+    # Le Vauclin (south-east tip)
+    (14.5500, -60.8400),  # Le Vauclin
+    # Le Marin (south)
+    (14.4700, -60.8700),  # Le Marin town
+    # Sainte-Anne (south coast)
+    (14.4400, -60.8500),  # Sainte-Anne
+    # Le Diamant (south-west)
+    (14.4800, -61.0200),  # Le Diamant
+    # Les Anses-d'Arlet (south-west coast)
+    (14.5000, -61.0800),  # Les Anses-d'Arlet
+    # Sainte-Luce (south-east)
+    (14.4600, -60.9300),  # Sainte-Luce
+    # Le Lorrain (north)
+    (14.7200, -60.9300),  # Le Lorrain
+]
+
+random.seed(42)  # Reproducible
+
+# Shuffle zones and pick 10 for each asset type (with some overlap for co-location)
+random.shuffle(ZONES)
+
+# Get all assets ordered by type and name
+result = subprocess.run([
+    "docker", "exec", "flexmeasures-db", "psql", "-U", "flexmeasures", "-d", "flexmeasures",
+    "-t", "-c", """
+    SELECT g.id, g.name, gt.name as type_name
+    FROM generic_asset g
+    JOIN generic_asset_type gt ON g.generic_asset_type_id = gt.id
+    ORDER BY gt.id, g.name;
+    """
+], capture_output=True, text=True)
+
+assets = []
+for line in result.stdout.strip().split('\n'):
+    parts = [p.strip() for p in line.split('|')]
+    if len(parts) == 3:
+        assets.append((int(parts[0]), parts[1], parts[2]))
+
+# Assign random locations per type (4 types, 10 assets each)
+type_groups = {}
+for aid, name, atype in assets:
+    if atype not in type_groups:
+        type_groups[atype] = []
+    type_groups[atype].append((aid, name))
+
+zone_idx = 0
+for atype, group in type_groups.items():
+    # Pick 10 random zones for this type (zones can repeat slightly for density)
+    type_zones = [ZONES[i % len(ZONES)] for i in range(zone_idx, zone_idx + 10)]
+    random.shuffle(type_zones)
+    zone_idx += 10
+    
+    for i, (aid, name) in enumerate(group):
+        lat, lon = type_zones[i]
+        # Add small random jitter (±0.005 degrees ≈ 500m)
+        lat += random.uniform(-0.005, 0.005)
+        lon += random.uniform(-0.005, 0.005)
+        
+        run_sql("UPDATE generic_asset SET latitude = {}, longitude = {} WHERE id = {};".format(
+            round(lat, 6), round(lon, 6), aid))
+        print("  {} ({}) -> {:.4f}, {:.4f}".format(name, atype[:3], lat, lon))
+
+print("\nDone!")