BQEB-OptiData v1: Benchmark Dataset for Intelligent Energy Dispatch and Optimization in Smart Grid Systems

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.BQEB-OptiData v1是一款合成基准数据集，旨在为智能能源调度优化、可再生能源并网、电池调度、电动汽车充电协调以及自治智能电网管理领域的研究提供支撑。该数据集拓展了生物量子能源大脑（BIO-Quantum Energy Brain，BQEB）生态系统，提供了可直接用于优化的运行变量、调度约束与能源调度目标，可用于基准测试经典、仿生以及量子启发式优化算法。 该数据集包含多模态智能电网运行数据，涵盖负荷需求、可再生能源发电量、电池荷电状态动态、电动汽车充电计划、能源电价、备用裕度、可再生能源弃电指标以及电网平衡指标。此外还包含调度成本、电池循环应力、充电优先级、碳减排估算值等面向优化的变量，以支撑能源管理与运行决策优化任务。 BQEB-OptiData v1旨在作为可复现的基准资源，服务于涉及线性规划、遗传算法、粒子群优化、模拟退火、强化学习以及量子启发式优化框架的智能能源系统相关研究。