基于分层分区调控的虚拟电厂市场多时间尺度竞价策略

doi:10.11930/j.issn.1004-9649.202506053

中国电力 ›› 2026, Vol. 59 ›› Issue (2): 138-147.DOI: 10.11930/j.issn.1004-9649.202506053

基于分层分区调控的虚拟电厂市场多时间尺度竞价策略

高峰¹(), 黄丽丽¹(), 陈洁²(), 卢松³, 李明南¹

1. 国能长源能源销售有限公司，湖北武汉　430040
2. 国家能源集团长源电力股份有限公司，湖北武汉　430077
3. 国能长源恩施水电开发有限公司，湖北恩施　445000

收稿日期:2025-06-18 修回日期:2026-01-13 发布日期:2026-03-04 出版日期:2026-02-28
作者简介:
高峰（1974），男，通信作者，工程师，从事工业电气自动化、市场营销研究，E-mail：12010317@ceic.com
黄丽丽（1978），女，高级工程师，从事电力营销研究，E-mail：12111486@ceic.com
陈洁（1971），女，工程师，从事电力营销研究，E-mail：12112389@ceic.com
基金资助:
国家能源集团长源电力股份有限公司科技项目（CYDL-2024-14）。

Multi-time scale bidding strategy for virtual power plant markets based on hierarchical partition control

GAO Feng¹(), HUANG Lili¹(), CHEN Jie²(), LU Song³, LI Mingnan¹

1. Chn Energy Changyuan Energy Sales Co., Ltd., Wuhan 430040, China
2. Chn Energy Changyuan Electric Power Co., Ltd., Wuhan 430077, China
3. Guoneng Changyuan Enshi Hydropower Development Co., Ltd., Enshi 445000, China

Received:2025-06-18 Revised:2026-01-13 Online:2026-03-04 Published:2026-02-28
Supported by:
This work is supported by Science and Technology Project of Chn Energy Changyuan Electric Power Co., Ltd. (No.CYDL-2024-14).

摘要/Abstract

摘要：

为提升虚拟电厂（virtual power plant，VPP）参与电力市场的经济性与调控协调性，提出一种基于分层分区调控的虚拟电厂市场多时间尺度竞价策略。首先，定义虚拟机组作为调度与交易统一建模单元，依据电网拓扑结构与过载风险构建分区聚合策略，进一步构建其外特性表征模型以反映虚拟电厂可调节能力。其次，建立涵盖日前与实时市场的多时间尺度竞价模型，并利用库恩-塔克（Karush-Kuhn-Tucker，KKT）条件将其转化为单层优化问题以降低求解复杂度。最后，通过算例验证所提模型的有效性。结果表明，该策略可在保障网络安全与隐私保护的基础上，有效降低建模维度；可实现VPP在多时间尺度市场中的协调竞价，与采用固定报价和仅考虑日前市场相比，VPP收益分别提升了15.8%和17.2%，增强了VPP的市场适应能力与收益水平。

关键词: 虚拟电厂, 分层分区, 多时间尺度

Abstract:

To enhance the economic efficiency and coordination capability of virtual power plant (VPP) in electricity markets, this paper proposes a multi-timescale bidding strategy based on hierarchical and zonal regulation. Firstly, virtual power units are defined as unified modeling units for dispatch and trading. A zonal aggregation strategy is developed based on grid topology and overload risk, and external characteristic models of virtual power units are constructed to represent the regulation capability of VPP. Secondly, a multi-timescale bidding model covering both day-ahead and real-time markets is established, and the bi-level optimization problem is transformed into a single-level model via Karush-Kuhn-Tucker (KKT) conditions to reduce computational complexity. Finally, case studies are conducted to validate the effectiveness of the proposed model. Results demonstrate that the proposed strategy can effectively reduce modeling complexity while ensuring network security and privacy protection. It enables VPP to coordinate bidding in multi-time scale markets, with VPP revenue increasing by 15.8% and 17.2% compared to fixed bidding and the day-ahead market, respectively, thus enhancing its market adaptability and profitability.

Key words: virtual power plant, hierarchical and zonal regulation, multi-timescale

高峰, 黄丽丽, 陈洁, 卢松, 李明南. 基于分层分区调控的虚拟电厂市场多时间尺度竞价策略[J]. 中国电力, 2026, 59(2): 138-147.

GAO Feng, HUANG Lili, CHEN Jie, LU Song, LI Mingnan. Multi-time scale bidding strategy for virtual power plant markets based on hierarchical partition control[J]. Electric Power, 2026, 59(2): 138-147.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202506053

https://www.electricpower.com.cn/CN/Y2026/V59/I2/138

图/表 16

图 1 VPU分区聚合原则

Fig.1 Principle of VPU zonal aggregation

图 2 虚拟电厂分层调控架构

Fig.2 Hierarchical regulation architecture of virtual power plant

表 2 配变参数

Table 2 Parameters of distribution transformers 单位：MW

配变	功率	功率限值	上、下可调能力
b1	10	15	—
b2	20	25	—
b3	–6	10	—
b4	6	10	—
b5	–13	20	—
b6	–8	15	—
b7	–15	20	—
b8	–5	10	—
b9	–6	10	—

图 3 测试电力系统拓扑

Fig.3 Topology of the test power system

表 1 灵活性资源参数

Table 1 Parameters of flexible resources 单位：MW

灵活性资源	功率	功率限值	上、下可调能力
U1	10	—	–5~5
U2	20	—	–6~6
U3	–6	—	–2~2
U4	6	—	–2~2
U5	–13	—	–3~3
U6	–8	—	–1~1
U7	–15	—	–2~2

表 3 馈线参数

Table 3 Parameters of feeders 单位：MW

馈线	功率	功率限值	上、下可调能力
F1	–10	15	—
F2	–10	15	—
F3	10	15	—
F4	–15	20	—
F5	14	20	—
F6	6	10	—
F7	–13	20	—
F8	–11	15	—
F9	23	25	—

表 4 线路参数

Table 4 Parameters of transmission lines 单位：MW

线路	功率	功率限值	上、下可调能力
L1	–50	100	—
L2	–30	50	—

表 5 主变参数

Table 5 Parameters of Main Transformers 单位：MW

主变	功率	功率限值	上、下可调能力
B1	43	100	—
B2	43	100	—
B3	–91	90	—
B4	–7	20	—
B5	12	20	—
B6	–31	50	—
B7	–7	20	—
B8	12	20	—
B9	–1	20	—

表 6 VPU划分

Table 6 VPU partitioning

CVPP	VPU编号	灵活性资源
CVPP1	VPU1	U1
	VPU2	U2
	VPU3	U3
CVPP2	VPU4	U4、U5
CVPP2	VPU5	U6、U7

图 4 报价曲线

Fig.4 Bidding curve

图 5 CVPP1可行域

Fig.5 Feasible region of CVPP1

图 6 CVPP1爬坡率

Fig.6 Ramp rate of CVPP1

图 7 日前市场出清结果

Fig.7 Day-ahead market clearing results

图 8 CVPP1日前市场和实时市场报价

Fig.8 Day-ahead and real-time market bidding of CVPP1

图 9 实时市场中各机组功率调整量

Fig.9 Power adjustment of each unit in the real-time market

表 7 不同场景下CVPP1的收益情况

Table 7 Revenue of CVPP1 under different scenarios 单位：美元

场景	市场总收益	日前市场收益	实时市场收益	总运行成本
1	14 614.78	14 038.02	576.76	4 059.73
2	12 616.35	12 247.56	368.79	4 032.77
3	14 038.02	14 038.02	—	4 759.49
4	9 908.49	9 566.18	342.31	5 546.49

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基于分层分区调控的虚拟电厂市场多时间尺度竞价策略

Multi-time scale bidding strategy for virtual power plant markets based on hierarchical partition control

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基于分层分区调控的虚拟电厂市场多时间尺度竞价策略

Multi-time scale bidding strategy for virtual power plant markets based on hierarchical partition control

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摘要/Abstract

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