BQEB-Data v1 BIO-Quantum Energy Brain Benchmark Dataset for Smart Grid Intelligence, Renewable Forecasting, Storage Optimization, and Cyber Resilience

BQEB-Data v1 is a synthetic multimodal benchmark dataset developed to support research in next-generation intelligent energy systems. The dataset is inspired by the BIO-Quantum Energy Brain (BQEB) concept, which integrates artificial intelligence, bio-inspired adaptive control, quantum optimization, and secure autonomous decision-making for modern energy infrastructure. BQEB-Data v1 contains 10,512 time-series records sampled at 15-minute intervals and includes variables representing electricity demand, renewable generation, battery storage behavior, electric vehicle charging activity, weather conditions, electricity market pricing, grid health indicators, and cyber anomaly events.

The dataset is designed for benchmarking machine learning, forecasting, optimization, anomaly detection, reinforcement learning, and cyber-physical resilience methods. It enables use cases such as load prediction, renewable energy forecasting, dynamic pricing analysis, battery dispatch scheduling, EV charging orchestration, outage prediction, and security analytics. Chronological train, validation, and test splits are included to support reproducible experimentation. BQEB-Data v1 serves as an open research resource for academia, industry, and government researchers working on smart grids, sustainable energy systems, and autonomous infrastructure intelligence.