Article detail · 2025
Developing a Multi-Region Stacking Ensemble Framework via Scenario-Based Digital Twin Simulation for Short-Term Household Energy Demand Forecasting
Journal
Applied SciencesISSN 2076-3417
The ISSN points to another catalog journal; the name is from the YÖKSİS record.
- Year
- 2025
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Applied Sciences
- Catalog match (ISSN) Applied Sciences (Switzerland)
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
English (OpenAlex)
Modern energy grids, with their regional diversity and complex consumption patterns, require accurate short-term forecasting for operational efficiency and reliability. This study introduces a Stacking Ensemble Forecasting (SEF) framework for multi-region household energy demand, utilizing an optimized stacking ensemble model tuned via Bayesian Optimization to achieve superior predictive accuracy. The framework significantly improved accuracy across Diyarbakır, Istanbul, and Odemis, with a final model demonstrating up to 16.47% RMSE reduction compared to the best baseline models. The final model’s real-world performance was validated through a Simulated Digital Twin (SDT) environment, where scenario-based testing demonstrated its robustness against behavioral changes, data quality issues, and device failures. The proposed SEF-SDT framework offers a generalizable solution for managing diverse regions and consumption profiles, contributing to efficient and sustainable energy management.
Topics
- Energy Load and Power Forecasting
- Energy Efficiency and Management
- Energy, Environment, and Transportation Policies
Primary topic Energy Load and Power Forecasting