虚拟电厂响应意愿度数据集
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本数据集为上海交通大学以及研究团队在虚拟电厂用户响应意愿刻画与行为模式分析研究过程中产生的仿真数据，旨在为虚拟电厂需求侧响应意愿度建模、激励机制评估与调控策略优化提供仿真数据基础与模型验证依据。 数据主要通过仿真平台生成，基于心理学行为决策模型构建虚拟电厂在不同激励电价下的响应电量意愿度曲线。模型同时考虑了随机性因素与二次函数特性，用于描述虚拟电厂在面对经济激励时的响应偏好与行为差异。数据集中共构建了 8 个虚拟电厂的响应意愿度模型，涵盖典型激励策略下的响应电量变化情况，可反映不同类型虚拟电厂群体在价格激励中的行为响应规律。主要用于构建资源层级的调节能力与外部因素相关性分析，并构建典型行为模式集合，从而建立精准的聚合调节潜力测算方法。 主要数据内容为响应意愿度数据，包括不同激励电价下各虚拟电厂的响应电量内容等。 数据集规模为169KB。
This dataset comprises simulation data generated by Shanghai Jiao Tong University and its research team during the study on characterizing user response willingness and analyzing behavioral patterns of virtual power plants (VPPs). It is intended to provide simulation data foundations and model validation support for demand-side response willingness modeling, incentive mechanism evaluation, and regulation strategy optimization of virtual power plants. The data is primarily generated via simulation platforms. Based on psychological behavioral decision-making models, it constructs response electricity willingness curves of VPPs under various incentive electricity prices. The model incorporates both random factors and quadratic function characteristics to describe the response preferences and behavioral discrepancies of VPPs when confronted with economic incentives. A total of 8 VPP response willingness models are developed in this dataset, covering the variations in response electricity volumes under typical incentive strategies, which can reflect the behavioral response patterns of different types of VPP groups under price incentives. This dataset is mainly used to conduct correlation analysis between resource-level regulation capabilities and external factors, establish a collection of typical behavioral patterns, and thus develop an accurate method for calculating aggregated regulation potential. The core data content consists of response willingness data, including the response electricity volumes of each VPP under different incentive electricity prices, and other relevant contents. The dataset has a size of 169 KB.
