Aggregated User Selection of Peak-regulation Virtual Power Plant Based on Cloud Model and Improved Evidence Theory

Jiang LIU; Yunpeng GUO; Bo ZHANG; Diqing ZHAI; Xiaofeng XU; Dunnan LIU

doi:10.7500/AEPS20220418006

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Aggregated User Selection of Peak-regulation Virtual Power Plant Based on Cloud Model and Improved Evidence Theory

Special Session on Virtual Power Plant with Enormous Flexible Resources | 更新时间：2025-06-16

- Aggregated User Selection of Peak-regulation Virtual Power Plant Based on Cloud Model and Improved Evidence Theory
- Automation of Electric Power Systems Vol. 46, Issue 18, Pages: 37-45(2022)
- 作者机构：
  
  1.内蒙古电力(集团)有限责任公司鄂尔多斯供电公司,内蒙古自治区鄂尔多斯市 017000
  2.国网浙江省电力有限公司,浙江省杭州市 310000
  3.国网浙江省电力有限公司金华供电公司,浙江省金华市 321000
  4.华北电力大学经济与管理学院,北京市 102206
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(72171082)
- DOI：10.7500/AEPS20220418006
  CLC：
- Received：18 April 2022，
  
  Revised：2022-07-08，
  
  Published Online：01 September 2022，
  
  Published：25 September 2022
- 稿件说明：
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刘江,郭云鹏,张波等.基于云模型和改进证据理论的调峰型虚拟电厂聚合用户优选[J].电力系统自动化,2022,46(18):37-45.

LIU Jiang,GUO Yunpeng,ZHANG Bo,et al.Aggregated User Selection of Peak-regulation Virtual Power Plant Based on Cloud Model and Improved Evidence Theory[J].Automation of Electric Power Systems,2022,46(18):37-45.
刘江,郭云鹏,张波等.基于云模型和改进证据理论的调峰型虚拟电厂聚合用户优选[J].电力系统自动化,2022,46(18):37-45. DOI： 10.7500/AEPS20220418006.

LIU Jiang,GUO Yunpeng,ZHANG Bo,et al.Aggregated User Selection of Peak-regulation Virtual Power Plant Based on Cloud Model and Improved Evidence Theory[J].Automation of Electric Power Systems,2022,46(18):37-45. DOI： 10.7500/AEPS20220418006.

摘要

在规模化需求侧资源接入电网背景下，为了提高调峰型虚拟电厂在海量异质负荷环境下用户调峰性能识别的精度，提出了基于云模型和改进证据理论的调峰型虚拟电厂聚合用户优选方法。首先，从负荷管理、调峰潜力和历史信用3个维度构建了用户优选指标体系。其次，针对用户在优选等级边界处的随机性与模糊性，采用云模型生成各指标在基准云中的隶属度，并引入不确定性焦元将其转化为证据理论中的基本概率分配。再次，针对传统证据理论中强冲突证据融合可能会产生悖论的问题，参考博弈思想将证据的静动态权重进行博弈组合，根据组合权重识别冲突证据并进行冲突修正和融合。同时，借鉴逼近理想解排序技术思想，比较各用户基本概率分配与正负理想云的贴近度以确定用户的聚合优先级。最后，通过算例分析验证了所提方法在解决证据冲突性以及虚拟电厂用户优选方面的有效性和优越性。

Abstract

In the background of large-scale demand-side resources connected to the power grid

in order to improve the identification accuracy of the peak-regulation performance of users in peak-regulation virtual power plants in the environment of massive heterogeneous loads

a method for the aggregated user selection of peak-regulation virtual power plants based on the cloud model and the improved evidence theory is proposed. Firstly

a user selection index system is constructed from three dimensions of load management

peak-regulation potentiality and historical credit. Secondly

aiming at the randomness and fuzziness of the users at the boundary of the selection level

the cloud model is used to generate the membership degree of each index in the benchmark cloud

and the uncertainty focal element is introduced to transform it into the basic probability distribution of evidence theory. Thirdly

in view of the paradox problems that may occur in the fusion of strong conflict evidences in the traditional evidence theory

the static and dynamic weights of the evidences are combined in the game with reference to the game idea

and the conflict evidences are identified

corrected and fused according to the combination weight. At the same time

based on the idea of technique for order preference by similarity to an ideal solution (TOPSIS)

the closeness between the basic probability distribution of each user and the positive and negative ideal cloud is compared to determine the aggregated priority of users. Finally

the numerical example analysis verifies the effectiveness and superiority of the proposed method in solving the evidence conflicts and user selection of virtual power plants.

关键词

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references

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