Optimization Strategy for Virtual Power Plant Combined Electric Energy and Peak Regulation Market Considering Differentiated Quotation of Power Supply Equipment

doi:10.11930/j.issn.1004-9649.202412113

Abstract

Abstract:

As an effective carrier for new energy to participate in the electric energy market, the advanced market mechanism and the strategy of controlling flexible resources have become the key problems that need to be solved. Based on this, this paper proposes the joint market optimization strategy of virtual power plant energy and peak regulation considering the differentiated quotation mechanism of power supply equipment, and carries out the participation market behavior of virtual power plants including new energy. Firstly, based on carbon trading, green certificate trading and demand response, a differentiated quotation mechanism for different power supply equipment in virtual power plant is proposed to reasonably guide virtual power plant to participate in the market optimization; secondly, to realize the privacy of the quotation information of each equipment; finally, double-layer model with joint optimization formula and CPLEX solver to verify the effectiveness and practicability of the proposed method and model in different environments. The simulation results show that the proposed differentiated quotation mechanism reduces the joint operation cost, with a maximum reduction of 50.34%, and effectively coordinates the interest relationship between the virtual power plant and the joint market.

Key words: virtual power plant, encryption model, differentiated quotation mechanism

CLC Number:

TM734

SHEN Yunwei, CEN Wenyu, ZHOU Bo. Optimization Strategy for Virtual Power Plant Combined Electric Energy and Peak Regulation Market Considering Differentiated Quotation of Power Supply Equipment[J]. Electric Power, 2025, 58(7): 115-127.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202412113

https://www.electricpower.com.cn/EN/Y2025/V58/I7/115

Figures/Tables 22

Fig.1 Dual-layer frame work of VPP transaction

Fig.2 The quotation process for VPP participating in electric energy-peak regulating joint market

Fig.3 The Joint optimal solution process

Fig.4 Flowchart of double-layer model

Fig.5 Electricity market and peak shaving demand

Fig.6 Basic data of VPP1

Fig.7 Basic data of VPP2 and VPP3

Fig.8 Iteration results of double-layer model

Fig.9 Optimal quotation for each equipment in VPP1

Fig.10 The optimal operation plan for VPP1

Fig.11 Optimal quotation for each equipment in VPP2

Fig.12 Optimal operation plan for VPP2

Fig.13 The optimal quotation for each equipment in VPP3

Fig.14 The optimal operation plan for VPP3

Fig.15 The optimal operation plan for thermal power unit

Fig.16 The optimal clearing plan

Fig.17 The optimal peak shaving quotation

Fig.18 The optimal peak shaving power allocation plan

Fig.19 The correctness of the VPP clearing power

Fig.20 Average quotation value of each equipment in different scenarios

Fig.21 Clear revenue of each equipment under different scenarios

Table 1 Feasibility analysis of the bi-level model

VPP数量/台	参与报价设备数量	最优报价生成时间/s	模型求解时间/s	报价成功率/%
3	11	0.1201	1.67	100.00
9	33	0.1274	2.81	100.00
27	99	0.1349	6.03	98.99
81	297	0.2087	10.35	97.95
243	891	0.2763	20.96	97.47

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