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Cross-Temporal Hierarchical Forecast Reconciliation of Natural Gas Demand

Author

Listed:
  • Colin O. Quinn

    (Department of Computer Science, Marquette University, 1313 W. Wisconsin Ave, Milwaukee, WI 53233, USA)

  • George F. Corliss

    (Department of Electrical and Computer Engineering, Marquette University, 1515 W. Wisconsin Ave, Milwaukee, WI 53233, USA)

  • Richard J. Povinelli

    (Department of Electrical and Computer Engineering, Marquette University, 1515 W. Wisconsin Ave, Milwaukee, WI 53233, USA)

Abstract

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction in hourly mean absolute scaled error and a 3% reduction in daily mean absolute scaled error.

Suggested Citation

  • Colin O. Quinn & George F. Corliss & Richard J. Povinelli, 2024. "Cross-Temporal Hierarchical Forecast Reconciliation of Natural Gas Demand," Energies, MDPI, vol. 17(13), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3077-:d:1419885
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    References listed on IDEAS

    as
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