基于目标级联法的虚拟电厂日前调频容量计算方法

doi:10.11930/j.issn.1004-9649.202303003

中国电力 ›› 2024, Vol. 57 ›› Issue (1): 82-90.DOI: 10.11930/j.issn.1004-9649.202303003

基于目标级联法的虚拟电厂日前调频容量计算方法

张颖¹(), 文艳²(), 季宇¹(), 左娟¹, 王文博¹

1. 国网上海能源互联网研究院有限公司，上海　200120
2. 国网山东省电力公司，山东济南　250001

收稿日期:2023-02-28 录用日期:2023-05-29 发布日期:2024-01-23 出版日期:2024-01-28
作者简介:张颖（1994—），女，硕士，工程师，从事分布式电源优化调度及虚拟电厂技术研究，E-mail：zhangying@epri.sgcc.com.cn
文艳（1975—），女，硕士，高级工程师（教授级），从事电力系统自动化研究，E-mail：wenyan023@163.com
季宇（1982—），男，通信作者，博士，高级工程师（教授级），从事分布式电源、微电网及虚拟电厂技术研究，E-mail：jiyu@epri.sgcc.com.cn
基金资助:
国家电网有限公司总部科技项目（支撑高比例分布式资源的配电网形态与管控体系构建技术研究，5100-202155291A-0-0-00 ）。

Calculation of Day-Ahead Frequency Regulation Capacity for Virtual Power Plants Based on Analytical Target Cascading Method

Ying ZHANG¹(), Yan WEN²(), Yu JI¹(), Juan ZUO¹, Wenbo WANG¹

1. State Grid Shanghai Energy Interconnection Research Institute Co., Ltd., Shanghai 200120, China
2. State Grid Shandong Electric Power Company, Jinan 250001, China

Received:2023-02-28 Accepted:2023-05-29 Online:2024-01-23 Published:2024-01-28
Supported by:
This work is supported by Science and Technology Project of SGCC (Research on Distribution Network Configuration and Control System Construction Technology Supporting High Proportion of Distributed Resources, No.5100-202155291A-0-0-00).

摘要/Abstract

摘要：

光伏、风电等清洁能源的大规模并网加重了系统调频负担，同时，微型燃气轮机、储能等调频性能稳定良好的分布式资源的接入为减小系统调频负担提供了新的思路。为此提出一种基于目标级联分析的优化调度模型，旨在通过虚拟电厂聚合分布式资源以参与调频辅助服务市场。首先，建立了配电网层和虚拟电厂层的双层优化调度模型，通过配电网协调虚拟电厂的协调互补来提高资源的利用效率；然后，虚拟电厂对内部成员进行优化调度，采用机会约束规划对调频信号不确定性进行约束；最后，通过目标级联分析法对所建立的模型进行求解，并通过仿真算例验证优化调度模型的有效性和可行性。结果表明，虚拟电厂参与调频辅助服务能够有效降低其运行成本。

关键词: 虚拟电厂, 调频辅助服务, 目标级联分析法, 优化调度, 机会约束

Abstract:

In recent years, with the large-scale integration of clean energy such as photovoltaic and wind power, the power grid is under growing stress from the demand of the system's frequency regulation. Meanwhile, the access of distributed resources such as micro gas turbines and energy storage with stable frequency regulation performance has provided new ideas to improve the system's frequency regulation capability. Therefore, an optimized scheduling model based on target cascade analysis is proposed in this paper, which aims to aggregate distributed resources through virtual power plants to participate in the frequency regulation ancillary service market. Specifically, a bi-level optimization scheduling model is established for both the distribution network layer and the virtual power plant layer. The distribution network coordinates the complementary resources of the virtual power plant to improve resource utilization efficiency. Then, the virtual power plant conducts optimization scheduling among internal participants, and the chance-constrained programming is applied to constrain the uncertainty of the frequency regulation signal. Finally, the target cascade analysis method is used to solve the established model, and the effectiveness and feasibility of the optimization scheduling model are verified through simulation examples. The results has demonstrated the effectiveness of the proposed day-ahead dispatching model. Moreover, the virtual power plant can effectively reduce its operating cost by participating in the regulation auxiliary service.

Key words: virtual power plant, regulation auxiliary service, analysis target cascading, optimal scheduling, chance constrained

张颖, 文艳, 季宇, 左娟, 王文博. 基于目标级联法的虚拟电厂日前调频容量计算方法[J]. 中国电力, 2024, 57(1): 82-90.

Ying ZHANG, Yan WEN, Yu JI, Juan ZUO, Wenbo WANG. Calculation of Day-Ahead Frequency Regulation Capacity for Virtual Power Plants Based on Analytical Target Cascading Method[J]. Electric Power, 2024, 57(1): 82-90.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303003

https://www.electricpower.com.cn/CN/Y2024/V57/I1/82

图/表 11

图 1 虚拟电厂控制架构

Fig.1 VPP control architecture

图 2 虚拟电厂接入架构

Fig.2 VPP connectional architecture

图 3 ATC计算框架

Fig.3 ATC computational framework

图 4 ATC优化流程

Fig.4 ATC optimization process

图 5 改进的IEEE 33 节点配电网络

Fig.5 Improved IEEE 33 bus distribution network

图 6 配电网调度结果

Fig.6 Distribution network dispatch results

图 7 虚拟电厂层调度结果

Fig.7 VPP dispatch results

图 8 配电网总成本

Fig.8 Total cost of distribution network

表 1 不同收敛容差下的配电网成本

Table 1 Distribution network cost under different convergence tolerances

收敛容差	配电网成本/元	收敛容差	配电网成本/元
0.005	38553	0.5	38557
0.050	38554	5.0	38572

图 9 不同置信水平下的ES荷电状态

Fig.9 Energy storage charge state at different confidence levels

表 2 不同置信水平下的ES收益

Table 2 Energy storage benefits at different confidence levels

置信水平	收益/元	置信水平	收益/元
0.95	680.0	0.70	791.1
0.90	761.1	0.60	798.1
0.80	780.9

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基于目标级联法的虚拟电厂日前调频容量计算方法

Calculation of Day-Ahead Frequency Regulation Capacity for Virtual Power Plants Based on Analytical Target Cascading Method

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基于目标级联法的虚拟电厂日前调频容量计算方法

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