BQEB-OptiData v1: Benchmark Dataset for Intelligent Energy Dispatch and Optimization in Smart Grid Systems
Abstract
BQEB-OptiData v1 is a synthetic benchmark dataset designed to support research in intelligent energy dispatch optimization, renewable integration, battery scheduling, electric vehicle charging coordination, and autonomous smart-grid management. The dataset extends the BIO-Quantum Energy Brain (BQEB) ecosystem by providing optimization-ready operational variables, dispatch constraints, and energy scheduling targets suitable for benchmarking classical, bio-inspired, and quantum-inspired optimization algorithms. The dataset contains multimodal smart-grid operational data including load demand, renewable generation, battery state-of-charge dynamics, EV charging schedules, energy pricing, reserve margins, renewable curtailment indicators, and grid balancing metrics. Optimization-oriented variables such as dispatch cost, battery cycling stress, charging priorities, and carbon reduction estimates are additionally included to support energy management and operational decision optimization tasks. BQEB-OptiData v1 is intended to serve as a reproducible benchmark resource for research involving linear programming, genetic algorithms, particle swarm optimization, simulated annealing, reinforcement learning, and quantum-inspired optimization frameworks for intelligent energy systems.
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 20 May 2026
- Language
- EN
- Document type
- Dataset