Digital Twin-Enabled Smart Energy Management for Mega Sports Events
DOI:
https://doi.org/10.13052/dgaej2156-3306.4121Keywords:
Digital Twin, Smart Energy Management, Mega Sports Events, Energy Efficiency, Renewable Energy, OptimizationAbstract
Mega sports events pose major energy management challenges due to their scale, and varying energy requirements. This paper suggests and assesses a digital twin powered smart energy management system for minimizing energy consumption, and maximizing grid stability of such events. The approach employs real-time data collection, and multi-domain energy system modeling with sophisticated predictive analytics with load forecasting based on Long Short-Term Memory (LSTM), along with multi-objective optimization techniques. Based on the evaluation with simulated event data, the deployed system exhibited significant improvements by decreasing average energy consumption by 23.2%, and apeak demand by 28.3%, respectively. Subsequently it is also observed that the self-consumption energy rate increase to 72% compared to conventional methods. Additionally, the system was responsible for substantial operational cost savings of about 30% as well as an impressive 37.5% decrease in carbon footprints. The load forecasting model showed a Mean Absolute Percentage Error (MAPE) value of 4.8%. The findings emphasize the potential capabilities of digital twin technology toward effective, sustainable, and resilient energy management for temporary, large-scale events.
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