Research on the Evaluation Method of Demand Response Potential of Virtual Power Plants under the New Power System
许建中 XU Jian-zhong；何作为 HE Zuo-wei；程鹏 CHENG Peng；吴非 WU Fei
（国网安徽省电力有限公司庐江县供电公司，庐江 231500）
（State Grid Anhui Electric Power Co.，Ltd. Lujiang County Power Supply Company，Lujiang 231500，China）
摘要：随着新型电力系统的建设，虚拟电厂（Virtual Power Plant，VPP）在整合分布式能源、可控负荷以及储能资源方面发挥着重要作用。评估虚拟电厂中不同用户的需求响应潜力对于优化电网调度、提升电网运行效率具有重要意义。本文提出了一种基于负荷时间弹性和价格弹性相结合的需求响应潜力评估方法，并结合熵权法确定各指标的权重，旨在实现对用户需求响应能力的全面量化评估。通过对浙江金华地区典型电力用户的实证分析，本文验证了所提出方法的有效性和实用性。研究结果表明，负荷时间弹性在评估中起到了关键作用，而价格弹性影响相对较小。此外，本文的方法能够通过数据驱动的聚类分析，识别不同用户的负荷特性，从而为虚拟电厂的优化调度提供依据。本文的研究为新型电力系统下虚拟电厂的需求响应管理提供了理论支持，并为未来研究指出了进一步改进的方向。
Abstract: With the construction of new power systems, Virtual Power Plants (VPPs) play an important role in integrating distributed energy, controllable loads, and energy storage resources. Evaluating the demand response potential of different users in virtual power plants is of great significance for optimizing power grid scheduling and improving power grid operation efficiency. This article proposes a demand response potential evaluation method based on the combination of load time elasticity and price elasticity, and uses entropy weight method to determine the weights of each indicator, aiming to achieve a comprehensive quantitative evaluation of user demand response capability.Through empirical analysis of typical power users in Jinhua, Zhejiang, this article verifies the effectiveness and practicality of the proposed method. The research results indicate that load time elasticity plays a key role in the evaluation, while price elasticity has a relatively small impact. In addition, the method proposed in this article can identify the load characteristics of different users through data-driven clustering analysis, providing a basis for optimizing the scheduling of virtual power plants. This study provides theoretical support for demand response management of virtual power plants under the new power system, and points out further improvement directions for future research.
关键词院：拟电厂；需求响应；负荷弹性；熵权法；潜力评估
Key words: virtual power plant；demand response；load elasticity；entropy weight method；potential assessment
中图分类号：TM62 文献标识码：A 文章编号：1006-4311（2024）29-051-04 doi:10.3969/j.issn.1006-4311.2024.29.016
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