Robust optimization scheduling strategy for virtual power plants considering demand response and leasing shared energy storage under the green certificate-electricity- carbon coupled market

doi:10.3969/j.issn.2097-0706.2025.05.004

Abstract

Abstract:

The Virtual Power Plant （VPP） is a key focus for energy management optimization and green， low-carbon operations. With the increasing participation of VPPs in green certificate and carbon trading markets， the volatility of distributed renewable energy and emerging business models have a significant impact on VPPs' optimization scheduling and trading strategies. To enhance the overall profitability of VPPs and further explore the scheduling potential of distributed resources， this paper proposed a robust optimization scheduling strategy for VPPs considering demand response and leasing shared energy storage in the green certificate-electricity-carbon coupled market. First， a price difference factor between green certificates and carbon quotas was introduced， and a coupled market operation framework was constructed. Second， considering the interest balance between VPPs and flexible loads under demand response， as well as the capacity leasing model of energy storage， a two-layer deterministic optimization scheduling model based on a leader-follower game was proposed. On this basis， a two-stage robust optimization model was further developed to account for the uncertainties of wind and photovoltaic power generation. Finally， the KKT conditions and column-and-constraint generation algorithm were applied to solve the model. Simulation results showed that the proposed strategy effectively addressed the uncertainties of wind and photovoltaic power， and through the integration of the green certificate-electricity-carbon coupled market， demand response， and leasing shared energy storage model， the potential for distributed resource scheduling was further explored， significantly enhancing the overall profitability of VPPs.

Key words: virtual power plant, distributed renewable energy, green certificate, carbon trading, green certificate-electricity-carbon coupled market, demand response, leasing shared energy storage, flexible load, leader-follower game, robust optimization

CLC Number:

TK01：TM73

ZHANG Wenbo, QIN Wenping, LIU Jiaxin, CHEN Yumei, LIU Boyang, ZHAO Anting. Robust optimization scheduling strategy for virtual power plants considering demand response and leasing shared energy storage under the green certificate-electricity- carbon coupled market[J]. Integrated Intelligent Energy, 2025, 47(5): 31-40.

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项目	数值	范围
绿证交易价格/(元·个^-1)	50
可再生能源消纳权责比例	0.1
碳配额交易价格/(元·kg^-1)	57
碳排放配额/[kg·(kW·h)^-1]	0.392
碳排放因子/[kg·(kW·h)^-1]	0.841
调频补偿/[元·(kW·h)^-1]	0.75
弃风光惩罚成本/[元·(kW·h)^-1]		1.50倍日前电价
租赁价格/[元·(kW·d)^-1]	0.27
需求响应电价/[元·(kW·h)^-1]		0.95~1.05倍日前电价
FL功率/kW		0.95~1.05倍初始负荷
GT发电功率/kW		1 000~3 000
GT爬坡功率/kW		-600~600
GT发电成本/[元·(kW·h)^-1]	0.25
ES充放电功率/kW		0~500
ES电量/（kW·h）	1 800	300~3 000
ES调频容量/kW		0~50
ES充放电成本/[元·(kW·h)^-1]	0.10
LES租赁容量比例		0~1
M	1.0×10⁴

向上波动/次	向下波动/次	VPP市场收益/元
0	0	4 814
1	1	4 745
2	2	4 680
3	3	4 614
4	4	4 560
5	5	4 509

向上波动/次	向下波动/次	容量租赁比例/%
2	2	16.51
3	3	24.68
4	4	32.01