Reserve Provision from Electric Vehicles: Aggregate Boundaries and Stochastic Model Predictive Control

This dataset contains simulation results for the research article "Reserve Provision from Electric Vehicles: Aggregate Boundaries and Stochastic Model Predictive Control". Each CSV file corresponds to an experimental setup with a certain number of EVs included in the fleet and the risk-aversion determined by the risk-aversion factor Ω. Each CSV file contains ten columns that contain the following features: Penalty incurred, positive reserve commitment, negative reserve commitment, total cumulative energy trajectory, G2V charging, V2G charging, lower bound of the conceptual battery, upper bound of the conceptual battery, power boundary of the conceptual battery, electricity system price. Benchmark 1 shows the results for a naive algorithm that solely relies on deterministic predictions. Benchmark 2 is an algorithm that has perfect future knowledge and therefore does not need to rely on predictions.

本数据集包含研究论文《电动汽车备用容量提供：聚合边界与随机模型预测控制》的仿真结果。每个CSV文件对应一种实验设置，其车队包含特定数量的电动汽车（Electric Vehicles, EV），且风险厌恶程度由风险厌恶因子Ω确定。每个CSV文件包含十列数据字段，具体如下：惩罚成本、正向备用容量承诺、负向备用容量承诺、总累积能量轨迹、电网到车辆（Grid to Vehicle, G2V）充电、车辆到电网（Vehicle to Grid, V2G）充电、概念电池的下限、概念电池的上限、概念电池的功率边界、电力系统电价。基准1展示了仅依赖确定性预测的朴素算法的仿真结果；基准2则是一种拥有完美未来信息、无需依赖预测的算法。