Coordinated Optimization Method for Virtual Power Plants and Distribution Networks Considering Distributed Energy Storage and Photovoltaics

doi:10.11930/j.issn.1004-9649.202407022

Abstract

Abstract:

With the continuous increase in photovoltaic penetration and user electricity consumption, serious upper and lower voltage limit violations often occur at partial nodes of distribution networks due to significant power imbalances between the source side and the user side, which not only increases the power and energy loss of the grid, but also affects the normal electricity consumption of users. This study developed a coordinated dispatch models between virtual power plants (VPPs) and distribution networks from the perspective of supply-demand balance in power distribution systems. By leveraging the capability of VPPs to aggregate diverse distributed energy resources (DERs), the models enable VPPs to actively participate in distribution market operations through the provision of active and reactive power support. This approach effectively mitigates both the upper and lower voltage limit violations, thereby enhancing power quality and the security/reliability of the distribution systems, while simultaneously reducing the total operational costs of the grid. Simulation results demonstrate that the coordinated dispatch models developed in this paper effectively alleviate the upper and lower voltage limit violations in distribution networks by utilizing the flexibility of VPPs, reduce the total operating cost and enhance the overall safety and stability performance of the distribution networks.

Key words: distributed energy storage, distributed photovoltaic, distribution network, virtual power plant, voltage limit violation

LIU Junhui, GONG Jian, TONG Bingshen, LI Songjie, ZHANG Yihan, CUI Shichang, TIAN Chunzheng, ZHANG Yongbin. Coordinated Optimization Method for Virtual Power Plants and Distribution Networks Considering Distributed Energy Storage and Photovoltaics[J]. Electric Power, 2025, 58(6): 1-9.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202407022

https://www.electricpower.com.cn/EN/Y2025/V58/I6/1

Figures/Tables 10

Fig.1 VPP and distribution network collaborative dispatching framework

Fig.2 Topology of the IEEE 33-bus distribution system

Table 1 Aggregation parameters for distributed ES and PV

对象	聚合物理量	聚合值
ES	$ {P}_{j,t}^{\rm ES,C,max}、{P}_{j,t}^{\rm ES,D,max} $/MW	0.02、0.02
	$ E_j^{\rm R} $/(MW·h)	0.4
	$ {S}_{j}^{\text{ES},\mathrm{min}}、{S}_{j}^{\text{ES},\mathrm{max}} $	0.2, 0.8
PV	$ P_{j,t}^{{\rm PV,pre}} $/MW	0.02
PV	$ {\alpha _j} $	0.95

Fig.3 Result of case 1.1

Fig.4 MT output of case 1.2

Fig.5 Output of PV before and after scheduling

Fig.6 Output of ES before and after scheduling

Table 2 Various costs of distribution network 单位：欧元

算例	上级电网购电成本	VPP成本		MT成本	总成本
算例	上级电网购电成本	PV成本	ES成本	MT成本	总成本
1.1	6858.948	0	0	78.8680	6937.8160
1.2	6713.011	18.0554	8.9131	4.7385	6744.6874
2	–513.307	1350.1760	9.3928	0	846.2619

Fig.7 Output of PV before ad after scheduling (case 2)

Fig.8 Output of ES before and after scheduling (case 2)

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