Kitchen Performance Tests

Kitchen Performance Tests (KPTs) are field-based procedures that measure and validate real-world fuel consumption in household cooking environments through direct observation. These tests follow strict methodological requirements to ensure accurate quantification of emission reductions and prevent over-crediting.

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Methodological Requirements

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Quick Start

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Components

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Required Parameters

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Optional Parameters

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Validation Rules

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Response Format

{
  "id": "kpt-123",
  "status": "verified",
  "credential": {
    "type": "KPTCredential",
    "issuer": "did:ixo:validator/456",
    "evidence": [
      "ipfs://QmevidenceformX12"
    ]
  }
}

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Error Codes

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Integration Examples

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Combining with IoT Data and Control Groups

# Get KPT baseline for both groups
reference_baseline = client.kpt.get_baseline("reference-group")
intervention_baseline = client.kpt.get_baseline("intervention-group")

# Compare with IoT readings
iot_data = client.devices.get_usage("device-456")
reduction = calculate_reduction(reference_baseline, intervention_baseline, iot_data)

# Validate seasonal factors
seasonal_impact = client.kpt.analyze_seasonal_variations(reduction)

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Next Steps

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Best Practices

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Test Design

• Document random selection process
• Ensure simultaneous testing of groups
• Validate group representativeness
• Monitor participant engagement

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Data Collection

• Maintain minimum 3-day duration
• Track external influencing factors
• Document seasonal variations
• Ensure continuous monitoring coverage

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Quality Control

• Validate measurement consistency
• Cross-reference with other data sources
• Monitor dropout rates
• Track data completeness

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Documentation

• Record selection methodology
• Document test period justification
• Track external factors
• Maintain compliance evidence