Phase 1 - Data Format

Phase 1 of the WIA-BEMS standard establishes the foundational data formats and schemas that enable interoperability across all building energy management systems. This phase is the cornerstone upon which all other phases build, ensuring that energy data from any source can be understood, aggregated, and analyzed consistently.

In this chapter, we'll explore the comprehensive data models defined in Phase 1, examine practical implementation examples, and understand how standardized data formats solve the data quality and accessibility challenges discussed in Chapter 2.

The Importance of Data Standardization

Before diving into specific schemas, it's essential to understand why data standardization matters and what problems it solves in the context of building energy management.

Semantic Consistency

When different systems use different terms for the same concept, integration becomes a nightmare. One system might call it "energy consumption," another "power usage," and a third "electricity draw." Phase 1 establishes canonical terminology and data structures that ensure everyone speaks the same language.

Unit Consistency

Energy can be measured in kilowatt-hours, British Thermal Units, therms, joules, calories, and many other units. Temperature can be Celsius, Fahrenheit, or Kelvin. Without standardization, every system consuming data must handle unit conversion, introducing opportunities for errors and inconsistencies. Phase 1 specifies standard units while providing clear mechanisms for representing alternatives.

Temporal Accuracy

Time zones, daylight saving time, and timestamp formats create surprising complexity. A timestamp of "2025-03-09 02:30:00" might not exist (during spring forward) or might occur twice (during fall back). Phase 1 mandates ISO 8601 timestamps with UTC or explicit time zone offsets, eliminating ambiguity.

Metadata Richness

Raw numbers without context have limited value. Phase 1 schemas include comprehensive metadata: measurement accuracy, calibration dates, sensor identifiers, quality indicators, and contextual information that enables proper interpretation and validation of data.

Core Energy Data Schema

The energy measurement schema is the most fundamental data structure in WIA-BEMS. It captures all information about energy consumption, demand, generation, and related metrics.

Energy Consumption Schema

The energy consumption schema represents cumulative energy use over a time period:

{
  "$schema": "https://wia.org/bems/v1/schemas/energy-consumption.json",
  "measurement_id": "unique-measurement-identifier",
  "timestamp_start": "2025-01-15T00:00:00Z",
  "timestamp_end": "2025-01-15T01:00:00Z",
  "location": {
    "building_id": "BLDG-001",
    "floor": 3,
    "zone": "East-Wing",
    "meter_id": "METER-E-301"
  },
  "energy": {
    "consumption_kwh": 125.5,
    "unit": "kilowatt_hour",
    "measurement_type": "electrical",
    "accuracy_class": "0.5"
  },
  "cost": {
    "amount": 18.75,
    "currency": "USD",
    "rate_schedule": "commercial-tiered"
  },
  "quality": {
    "completeness": 100.0,
    "estimated": false,
    "validation_status": "verified"
  },
  "metadata": {
    "meter_calibration_date": "2024-12-01",
    "reporting_source": "automated-meter-reading",
    "data_aggregation": "sum"
  }
}

Power Demand Schema

Power demand represents instantaneous power draw at a point in time:

{
  "$schema": "https://wia.org/bems/v1/schemas/power-demand.json",
  "measurement_id": "unique-measurement-identifier",
  "timestamp": "2025-01-15T14:30:00Z",
  "location": {
    "building_id": "BLDG-001",
    "floor": 3,
    "zone": "East-Wing",
    "meter_id": "METER-E-301"
  },
  "power": {
    "demand_kw": 150.25,
    "unit": "kilowatt",
    "measurement_type": "electrical",
    "power_factor": 0.92
  },
  "electrical_details": {
    "voltage_v": 480,
    "current_a": 320,
    "frequency_hz": 60,
    "phases": 3
  },
  "quality": {
    "accuracy": 0.1,
    "sample_rate_hz": 1,
    "validation_status": "verified"
  }
}

Data Element	Type	Required	Description
measurement_id	String (UUID)	Yes	Unique identifier for this measurement
timestamp	ISO 8601	Yes	When measurement was taken
location	Object	Yes	Where measurement was taken
energy/power	Object	Yes	Measurement values and units
quality	Object	Yes	Data quality indicators
cost	Object	No	Associated costs if available
metadata	Object	No	Additional contextual information

Environmental Conditions Schema

Environmental data is crucial for understanding energy consumption patterns and optimizing HVAC systems. Phase 1 defines comprehensive schemas for all environmental parameters.

Temperature Measurement

{
  "$schema": "https://wia.org/bems/v1/schemas/temperature.json",
  "measurement_id": "temp-measurement-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "location": {
    "building_id": "BLDG-001",
    "floor": 3,
    "zone": "Conference-Room-A",
    "sensor_id": "TEMP-301-A",
    "sensor_type": "resistance_temperature_detector"
  },
  "temperature": {
    "value": 22.5,
    "unit": "celsius",
    "measurement_type": "ambient_air"
  },
  "quality": {
    "accuracy": 0.1,
    "resolution": 0.01,
    "sensor_calibration_date": "2024-12-01",
    "validation_status": "verified"
  }
}

Humidity and Air Quality

{
  "$schema": "https://wia.org/bems/v1/schemas/air-quality.json",
  "measurement_id": "aq-measurement-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "location": {
    "building_id": "BLDG-001",
    "floor": 3,
    "zone": "Open-Office-East"
  },
  "measurements": {
    "humidity": {
      "relative_humidity_percent": 45.0,
      "accuracy": 2.0
    },
    "co2": {
      "concentration_ppm": 650,
      "accuracy": 50,
      "threshold_warning": 1000,
      "threshold_critical": 1500
    },
    "particulate_matter": {
      "pm25_ugm3": 8.5,
      "pm10_ugm3": 15.2
    },
    "volatile_organic_compounds": {
      "tvoc_ppb": 125,
      "threshold_warning": 500
    }
  }
}

Occupancy and Space Utilization Schema

Understanding building occupancy is essential for optimizing energy use. Phase 1 defines schemas that capture occupancy data while respecting privacy requirements.

Occupancy Measurement

{
  "$schema": "https://wia.org/bems/v1/schemas/occupancy.json",
  "measurement_id": "occ-measurement-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "location": {
    "building_id": "BLDG-001",
    "floor": 3,
    "zone": "Conference-Room-A",
    "room_capacity": 20
  },
  "occupancy": {
    "count": 12,
    "detection_method": "infrared_sensor",
    "confidence": 0.95,
    "privacy_preserved": true
  },
  "utilization": {
    "percent": 60.0,
    "status": "occupied",
    "scheduled": true,
    "event_type": "meeting"
  }
}

Detection Method	Accuracy	Privacy Impact	Best Use Case
PIR (Passive Infrared)	Binary (occupied/vacant)	Very Low	Individual offices, restrooms
Ultrasonic	Binary with motion sensitivity	Very Low	Conference rooms, quiet spaces
CO2-based	Estimated count (±20%)	Very Low	Large spaces, auditoriums
Camera (computer vision)	Accurate count (±5%)	Medium-High	Public areas with consent
WiFi/BLE tracking	Device count (may differ from people)	Medium	General building usage trends

Equipment Status and Performance Schema

Monitoring equipment status enables predictive maintenance and performance optimization. Phase 1 schemas capture comprehensive equipment information.

HVAC Equipment Status

{
  "$schema": "https://wia.org/bems/v1/schemas/hvac-status.json",
  "measurement_id": "hvac-status-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "equipment": {
    "equipment_id": "AHU-301",
    "equipment_type": "air_handling_unit",
    "location": {
      "building_id": "BLDG-001",
      "floor": 3,
      "mechanical_room": "MR-3"
    }
  },
  "operational_status": {
    "status": "running",
    "mode": "cooling",
    "enabled": true,
    "alarm_status": "normal"
  },
  "performance": {
    "supply_air_temp_c": 13.5,
    "return_air_temp_c": 24.0,
    "supply_air_flow_cfm": 12000,
    "static_pressure_pa": 350,
    "fan_speed_percent": 75,
    "power_kw": 15.5
  },
  "setpoints": {
    "supply_air_temp_setpoint_c": 13.0,
    "static_pressure_setpoint_pa": 375
  },
  "maintenance": {
    "runtime_hours": 12450,
    "filter_pressure_drop_pa": 125,
    "filter_change_threshold_pa": 250,
    "last_maintenance_date": "2024-11-15"
  }
}

Lighting System Status

{
  "$schema": "https://wia.org/bems/v1/schemas/lighting-status.json",
  "measurement_id": "light-status-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "equipment": {
    "equipment_id": "LIGHT-ZONE-301-A",
    "equipment_type": "led_lighting_zone",
    "location": {
      "building_id": "BLDG-001",
      "floor": 3,
      "zone": "Open-Office-East"
    }
  },
  "operational_status": {
    "status": "on",
    "brightness_percent": 75,
    "color_temperature_k": 4000,
    "control_mode": "auto_occupancy"
  },
  "performance": {
    "power_w": 850,
    "fixture_count": 48,
    "operational_fixtures": 48,
    "ambient_light_lux": 320,
    "target_light_lux": 500
  },
  "occupancy_integration": {
    "occupancy_detected": true,
    "daylight_harvesting_active": true,
    "override_until": null
  }
}

Renewable Energy Generation Schema

As buildings increasingly incorporate renewable energy sources, tracking generation becomes essential for optimization and net-zero goals.

Solar PV Generation

{
  "$schema": "https://wia.org/bems/v1/schemas/solar-generation.json",
  "measurement_id": "solar-gen-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "system": {
    "system_id": "SOLAR-PV-ROOF",
    "system_type": "photovoltaic",
    "location": {
      "building_id": "BLDG-001",
      "array_location": "main_roof",
      "capacity_kw": 100
    }
  },
  "generation": {
    "power_kw": 75.5,
    "energy_kwh_today": 450.2,
    "performance_ratio": 0.82
  },
  "environmental": {
    "irradiance_wm2": 850,
    "module_temp_c": 45,
    "ambient_temp_c": 22
  },
  "electrical": {
    "dc_voltage_v": 680,
    "dc_current_a": 115,
    "ac_voltage_v": 480,
    "inverter_efficiency": 0.97
  }
}

Energy Storage Schema

Battery storage systems require specialized data schemas to track state of charge, performance, and integration with building energy systems.

{
  "$schema": "https://wia.org/bems/v1/schemas/energy-storage.json",
  "measurement_id": "battery-status-001",
  "timestamp": "2025-01-15T14:30:00Z",
  "system": {
    "system_id": "BESS-001",
    "system_type": "lithium_ion_battery",
    "location": {
      "building_id": "BLDG-001",
      "equipment_room": "Electrical-Room-1"
    },
    "capacity_kwh": 500
  },
  "state": {
    "state_of_charge_percent": 65,
    "state_of_health_percent": 95,
    "operating_mode": "self_consumption",
    "power_kw": -25.5,
    "charging": false,
    "discharging": true
  },
  "performance": {
    "round_trip_efficiency": 0.89,
    "cycles_total": 1250,
    "throughput_kwh_total": 625000
  },
  "thermal": {
    "temperature_c": 28,
    "temperature_max_c": 35,
    "cooling_active": true
  }
}

Data Quality and Validation

Phase 1 includes comprehensive data quality frameworks to ensure reliability and enable appropriate handling of imperfect data.

Quality Indicators

Every measurement includes quality indicators that help consuming systems understand data reliability:

Quality Indicator	Values	Meaning	Usage
validation_status	verified, estimated, questionable, invalid	Overall data quality assessment	Filter out invalid data before analysis
completeness	0-100%	Percentage of expected data points present	Assess whether aggregations are representative
accuracy	Numeric value	Expected measurement error	Uncertainty analysis, significant figures
estimated	true/false	Whether value is measured or estimated	Distinguish actual from filled data
confidence	0-1.0	Statistical confidence in measurement	Weight data in probabilistic models

Missing Data Handling

Phase 1 specifies how systems should represent and handle missing or unavailable data:

{
  "measurement_id": "temp-measurement-002",
  "timestamp": "2025-01-15T14:30:00Z",
  "location": {
    "building_id": "BLDG-001",
    "floor": 3,
    "zone": "Conference-Room-B",
    "sensor_id": "TEMP-301-B"
  },
  "temperature": {
    "value": null,
    "unit": "celsius",
    "measurement_type": "ambient_air"
  },
  "quality": {
    "validation_status": "sensor_failure",
    "error_code": "NO_RESPONSE",
    "error_description": "Sensor not responding to queries",
    "last_valid_measurement": "2025-01-15T12:45:00Z"
  }
}

Implementation Best Practices

Successfully implementing Phase 1 data formats requires attention to several key considerations.

Schema Validation

All data should be validated against official JSON schemas before storage or transmission. Most programming languages have libraries for JSON schema validation that make this straightforward:

// JavaScript/TypeScript example
import Ajv from 'ajv';
const ajv = new Ajv();

const schema = await fetch('https://wia.org/bems/v1/schemas/energy-consumption.json')
  .then(r => r.json());

const validate = ajv.compile(schema);
const isValid = validate(measurementData);

if (!isValid) {
  console.error('Validation errors:', validate.errors);
}

Time Zone Handling

Always store timestamps in UTC and convert to local time only for display. This prevents ambiguity during daylight saving time transitions and simplifies data aggregation across time zones.

Precision and Accuracy

Report values with appropriate precision based on actual measurement accuracy. Reporting temperature to 0.0001°C when the sensor accuracy is ±0.5°C creates false confidence. Phase 1 schemas include accuracy fields to document measurement uncertainty.

Performance Considerations

While comprehensive schemas provide rich information, they can create large data volumes. Implement efficient storage strategies:

• Use time-series databases optimized for measurement data
• Implement data retention policies (high resolution recent, aggregated historical)
• Compress JSON data for storage and transmission
• Index frequently queried fields (timestamp, location, equipment_id)
• Use binary formats like Protocol Buffers or MessagePack for high-volume scenarios