Review of Dynamic Aggregation and Coordinated Scheduling Technologies for Multi-type Energy Storage Oriented to Optimized Operation of Virtual Power Plants

GE Leijiao; WANG Yuning; LU Rubo; MENG Zhouyue; ZHUO Yue; WU Yuyang

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Review of Dynamic Aggregation and Coordinated Scheduling Technologies for Multi-type Energy Storage Oriented to Optimized Operation of Virtual Power Plants

更新时间：2026-08-26

- Review of Dynamic Aggregation and Coordinated Scheduling Technologies for Multi-type Energy Storage Oriented to Optimized Operation of Virtual Power Plants
- JOURNAL OF XI’AN JIAOTONG UNIVERSITY (2026)
- 作者机构：
  
  天津大学电气自动化与信息工程学院，300072，天津
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM763
- Received：31 May 2026，
  
  Revised：2026-08-11，
  
  Accepted：26 August 2026，
- 稿件说明：
移动端阅览
GE Leijiao, WANG Yuning, LU Rubo, et al. Review of Dynamic Aggregation and Coordinated Scheduling Technologies for Multi-type Energy Storage Oriented to Optimized Operation of Virtual Power Plants[J]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY,2026.
DOI：

GE Leijiao, WANG Yuning, LU Rubo, et al. Review of Dynamic Aggregation and Coordinated Scheduling Technologies for Multi-type Energy Storage Oriented to Optimized Operation of Virtual Power Plants[J]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY,2026. DOI：

摘要

运行特性各异的多类型储能是支撑虚拟电厂优化运行的关键和当前研究热点，种类多样的设备和多运行目标之间动态协同难、时间尺度差异大等技术瓶颈已成为共识。为此，本文系统梳理该领域研究进展，以虚拟电厂、多类型储能、动态聚合、不确定性建模、优化调度、协同调度和多市场交易等为主题，对2012—2026年国内外代表性文献进行归纳分析，并重点关注2019年以来虚拟电厂储能聚合建模、源荷储协同优化、多时间尺度调度及智能算法应用等方面的研究成果；主要遵循主题相关性、方法代表性、研究时效性和工程参考价值原则，并参考政策文件、综述论文、建模方法、优化调度和算法应用等相关成果。区别于已有侧重虚拟电厂运行调度、储能优化配置或新能源不确定性处理的综述，本文聚焦多类型储能“动态聚合—场景建模—协同调度—算法求解”的内在关联，系统分析了不同储能技术在运行特性和应用场景方面的差异，以及虚拟电厂中多类型储能动态聚合模型结构、机制和算法。进一步地，从确定性与不确定性两个层面总结了高比例新能源接入下虚拟电厂的典型场景建模方法，重点比较了随机规划、鲁棒优化、区间规划等不确定性建模技术的适用特点。同时，归纳总结了多类型储能支撑虚拟电厂优化调度的目标函数构建、约束条件设置及模型结构设计方法，并对现有求解算法进行了分类评述，以期为提高储能技术在以经济、灵活和低碳运行为目标的虚拟电厂应用提供一定的借鉴。

Abstract

Multi-type energy storage systems with heterogeneous operational characteristics are a key enabling technology and a current research focus for the optimized operation of virtual power plants. It has been widely recognized that technical bottlenecks

such as the difficulty of achieving dynamic coordination among diverse devices and multiple operational objectives

as well as significant differences in time scales

remain major challenges. To systematically review the research progress in this field

this paper summarizes and analyzes representative domestic and international studies published from 2012 to 2026

focusing on topics including virtual power plants

multi-type energy storage

dynamic aggregation

uncertainty modeling

optimal scheduling

coordinated scheduling

and multi-market trading. Particular attention is paid to studies published since 2019 on energy storage aggregation modeling in virtual power plants

source-load-storage coordinated optimization

multi-time-scale scheduling

and intelligent algorithm applications. The literature selection mainly follows the principles of thematic relevance

methodological representativeness

research timeliness

and engineering reference value

and includes policy documents

review papers

modeling methods

optimal scheduling studies

and algorithm application studies. Different from existing reviews that mainly focus on virtual power plant operation scheduling

energy storage optimal configuration

or renewable energy uncertainty handling

this paper further emphasizes the internal relationship among “dynamic aggregation - scenario modeling - coordinated scheduling - algorithmic solution” for multi-type energy storage. The differences among various energy storage technologies in terms of operational characteristics and application scenarios are systematically analyzed

together with the structures

mechanisms and algorithms of dynamic aggregation models for multi-type energy storage in virtual power plants. Furthermore

typical scenario modeling methods for virtual power plants under high-proportion renewable energy integration are summarized from both deterministic and uncertain perspectives

with emphasis on comparing the applicability of uncertainty modeling techniques such as stochastic programming

robust optimization

and interval programming. Meanwhile

the construction of objective functions

the formulation of constraints

and the design of model structures for optimal scheduling of virtual power plants supported by multi-type energy storage are summarized

and existing solution algorithms are classified and reviewed. This study is expected to provide useful references for promoting the application of energy storage technologies in virtual power plants oriented toward economic

flexible

and low-carbon operation.

关键词

Keywords

references

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