Optimal Scheduling Strategy of Park-level Virtual Power Plant for Demand Response

doi:10.11930/j.issn.1004-9649.202410059

Abstract

Abstract:

The park-level virtual power plant (PVPP) can aggregate diversified and flexible resources with the industrial parks to fully explore demand response potential, thus improving the profits of the PVPP. In order to optimize the demand response strategy of the PVPP in the electricity carbon joint market, a two-stage optimal scheduling model of the PVPP is developed here, in which, carbon emission costs are included in the optimization objects. The developed model includes two stages, i.e., a day-ahead stage and a real-time stage, and can be solved by the GAMS software. In the day-ahead stage, photovoltaic (PV) generation power is predicted by the improved radial basis function neural network, and the demand response bidding capacities are determined aiming to maximize the net benefits of the PVPP resulted from the demand response. In the real-time stage, the day-ahead schedules are revised according to real PV generation power, thus minimizing the negative effects of the PV power generation forecasting errors on the net benefits of the PVPP resulted from the demand response. Finally, the simulation analysis based on a PVPP is carried out. The results demonstrate that the strategy developed in this paper can maximize the net benefits of the PVPP resulted from the demand response in the context of considering the carbon emission costs.

Key words: park-level virtual power plant, flexible resources, demand response, optimal schedule, carbon emission

WEI Chunhui, SHAN Linsen, HU Dadong, GAO Qianheng, ZHANG Xinsong, XUE Xiaocen. Optimal Scheduling Strategy of Park-level Virtual Power Plant for Demand Response[J]. Electric Power, 2025, 58(6): 112-121.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202410059

https://www.electricpower.com.cn/EN/Y2025/V58/I6/112

Figures/Tables 9

Fig.1 Basic structure of the PVPP

Fig.2 Flow chart of demand response of the PVPP

Fig.3 Two-stage optimal scheduling strategy of the PVPP

Table 1 Operational parameters of units within the PVPP

可调节资源		参数
PV/MW		17
GT/MW		10
BESS/(MW·(MW·h)⁻¹)		1.2/2.4

Table 2 Local peak and valley electricity price

时段		电价/(元·(kW·h)^–1)
尖峰（09:00—11:00、15:00—17:00）		1.2840
高峰（08:00—09:00、17:00—23:00）		1.0701
平段（13:00—15:00、23:00—24:00）		0.6485
低谷（00:00—08:00、11:00—13:00）		0.2918

Fig.4 Prediction and actual values of the PV output

Fig.5 Day-ahead electricity consumption optimization curves in three scenarios

Fig.6 Day-ahead and intra-day real-time optimization results in scenario 2

Table 3 Operating revenue of PVPP in three scenarios

需求响应收入/元			净收益/元
场景1	场景2	场景3	场景1	场景2	场景3
58 206	54 387	58 206	49 168	36 858	35 735

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