Initial commit: Energy test data generation pipeline

Add complete test data preparation system for energy trading strategy
demo. Includes configuration, data generation scripts, and validation
tools for 7 datasets covering electricity prices, battery capacity,
renewable/conventional generation, load profiles, data centers, and
mining data.

Excluded from git: Actual parquet data files (data/raw/, data/processed/)
can be regenerated using the provided scripts.

Datasets:
- electricity_prices: Day-ahead and real-time prices (5 regions)
- battery_capacity: Storage system charge/discharge cycles
- renewable_generation: Solar, wind, hydro with forecast errors
- conventional_generation: Gas, coal, nuclear plant outputs
- load_profiles: Regional demand with weather correlations
- data_centers: Power demand profiles including mining operations
- mining_data: Hashrate, price, profitability (mempool.space API)

data/metadata/generation_metadata.json

@@ -0,0 +1,89 @@
+{
+  "generated_at": "2026-02-10T16:10:43.522420",
+  "datasets": {
+    "battery_capacity": {
+      "rows": 144010,
+      "columns": [
+        "timestamp",
+        "battery_id",
+        "capacity_mwh",
+        "charge_level_mwh",
+        "charge_rate_mw",
+        "discharge_rate_mw",
+        "efficiency"
+      ],
+      "memory_usage_mb": 15.38205337524414,
+      "dtypes": {
+        "timestamp": "datetime64[ns]",
+        "battery_id": "object",
+        "capacity_mwh": "float64",
+        "charge_level_mwh": "float64",
+        "charge_rate_mw": "float64",
+        "discharge_rate_mw": "float64",
+        "efficiency": "float64"
+      }
+    },
+    "renewable_generation": {
+      "rows": 216015,
+      "columns": [
+        "timestamp",
+        "source",
+        "plant_id",
+        "generation_mw",
+        "forecast_mw",
+        "actual_mw",
+        "capacity_factor"
+      ],
+      "memory_usage_mb": 34.472124099731445,
+      "dtypes": {
+        "timestamp": "datetime64[ns]",
+        "source": "object",
+        "plant_id": "object",
+        "generation_mw": "float64",
+        "forecast_mw": "float64",
+        "actual_mw": "float64",
+        "capacity_factor": "float64"
+      }
+    },
+    "conventional_generation": {
+      "rows": 144010,
+      "columns": [
+        "timestamp",
+        "plant_id",
+        "fuel_type",
+        "generation_mw",
+        "marginal_cost",
+        "heat_rate"
+      ],
+      "memory_usage_mb": 26.149402618408203,
+      "dtypes": {
+        "timestamp": "datetime64[ns]",
+        "plant_id": "object",
+        "fuel_type": "object",
+        "generation_mw": "float64",
+        "marginal_cost": "float64",
+        "heat_rate": "float64"
+      }
+    },
+    "data_centers": {
+      "rows": 72005,
+      "columns": [
+        "timestamp",
+        "data_center_id",
+        "location",
+        "power_demand_mw",
+        "max_bid_price",
+        "client_type"
+      ],
+      "memory_usage_mb": 14.585489273071289,
+      "dtypes": {
+        "timestamp": "datetime64[ns]",
+        "data_center_id": "object",
+        "location": "object",
+        "power_demand_mw": "float64",
+        "max_bid_price": "float64",
+        "client_type": "object"
+      }
+    }
+  }
+}