Fast climbing scheduling strategy for virtual power plants based on second order consistency algorithm

仇晨光; 于 斐; 喻 洁; 梁文腾; 李 杰

doi:10.3969/j.issn.1009-1831.2025.04.016

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Fast climbing scheduling strategy for virtual power plants based on second order consistency algorithm

更新时间：2026-03-05

- Fast climbing scheduling strategy for virtual power plants based on second order consistency algorithm
- Vol. 27, Issue 4, (2025)
- 作者机构：
  
  1. 国网江苏省电力有限公司调度控制中心,南京,210024
  2. 东南大学电气工程学院,南京,210096
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2025.04.016
  CLC：
- Published：2025
- 稿件说明：
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仇晨光, 于斐, 喻洁, et al. Fast climbing scheduling strategy for virtual power plants based on second order consistency algorithm[J]. 2025, 27(4).
DOI：

仇晨光, 于斐, 喻洁, et al. Fast climbing scheduling strategy for virtual power plants based on second order consistency algorithm[J]. 2025, 27(4). DOI： 10.3969/j.issn.1009-1831.2025.04.016.

摘要

随着风力、光伏等新能源发电的大规模普及

其本身由于天气等原因带来的波动性和不确定性严重威胁电网的安全可靠运行

而虚拟电厂作为分布式资源聚合商

同时也是新型市场主体

能够利用先进信息通信技术和软件系统实现分布式资源的聚合和协调优化

进而提供快速爬坡服务。为实现电网灵活性爬坡的需求

故提出一种基于二阶一致性算法的虚拟电厂快速爬坡调度策略

根据虚拟电厂内部资源集群的现有条件

使资源集群的爬坡速率在一定条件下趋于一致

控制虚拟电厂内多个资源集群爬坡容量之和满足爬坡容量需求。构建二阶一致性的虚拟电厂控制数学模型

以爬坡速率与当前最大爬坡速率比值作为一致性算子

通过算例分析验证方法的有效性。

Abstract

With the large-scale adoption of renewable energy generation such as wind and photovoltaic power

their inherent volatility and uncertainty caused by weather conditions pose significant threats to the safe and reliable operation of power grids. As an aggregator of distributed resources and a new market entity

virtual power plants can utilize advanced information communication technologies and software systems to achieve aggregation and coordinated optimization of distributed resources

thereby providing fast ramping services. To address the flexibility ramping requirements of power grids

this paper proposes a VPP fast ramping dispatch strategy based on a second-order consensus algorithm. According to the existing conditions of resource clusters within the VPP

the strategy enables the ramping rates of resource clusters to converge to a consensus under specific constraints

ensuring that the total ramping capacity of multiple resource clusters meets the ramping demand. A second-order consensus-based mathematical control model for VPPs is established

employing the ratio of current ramping rate to maximum ramping rate as the consensus operator. Case studies are conducted to verify the effectiveness of the pro?posed method.

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