Virtual power plant bidding optimization control method based on IGDT and demand response
A virtual power plant and optimal control technology, applied in the field of optimal control of virtual power plant bidding, can solve problems such as economic decline, increased problem complexity, and difficulty in accurately describing the output probability of wind and rain
Active Publication Date: 2020-08-11
SHANGHAI JIAO TONG UNIV +1
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However, probability-based chance-constrained programming and stochastic programming and other analysis methods are difficult to accurately describe the probability of wind and rain output, and need to generate a large number of scene samples to improve the reliability of the model, which will inevitably increase the complexity of the problem sharply; robust optimization Although the reliability of the system is improved, it leads to a decline in economy. Therefore, the results of robust optimization often have a certain degree of conservatism.
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[0069] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings to make the technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned herein.
[0070] The invention studies the bidding problem of the virtual power plant participating in the day-ahead market (DAM) and the real-time market (RM). First, with the goal of maximizing the revenue of the virtual power plant, a joint bidding model for the virtual power plant in the day-ahead market and the real-time market is established. After that, IGDT is used to deal with the uncertainty of wind power output and the day-ahead market clearing electricity price, so as to build a virtual power plant joint market bidding model based on information gap decision theory, and determine the virtual power plant's part...
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The invention discloses a virtual power plant bidding optimization control method based on IGDT and demand response. The method comprises the steps: establishing and solving a virtual power plant deterministic bidding model; establishing a system model by utilizing an information gap decision theory; utilizing an information gap decision theory to establish an uncertainty model; according to different risk management strategies, selecting corresponding decision strategies in the information gap decision theory model according to the required performance requirements; solving an optimization result of the system model according to the selected decision strategy; and determining the optimal planned output of the virtual power plant. Demand response resources can be integrated, a virtual power plant joint market bidding model based on IGDT is constructed, internal resources are coordinated and dispatched to participate in the power market, and therefore economic optimization is achieved.
Description
technical field [0001] The invention relates to the technical field of virtual power plant bidding optimization control technology, in particular to an optimal control method of virtual power plant bidding based on IGDT and demand response. Background technique [0002] With the large-scale development and utilization of distributed energy and the gradual liberalization of the electricity market, the participation of distributed energy in the electricity market has become a major focus of future electricity market research. However, due to the strong uncertainty of distributed energy output and the small individual capacity, the unit cost of power generation is higher than that of traditional power generation resources. Therefore, distributed energy is less competitive when it participates in power market bidding alone. Virtual power plant (virtual power plant, VPP) is a new form of energy aggregation that can achieve reliable aggregation of distributed energy. It can not on...
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IPC IPC(8): G06Q10/04G06Q10/06G06Q30/02G06Q50/06
CPCG06Q10/04G06Q10/0635G06Q30/0206G06Q50/06Y02E40/70Y04S10/50Y04S50/14Y04S50/16
Inventor 李嘉媚艾芊孙东磊李雪亮李文升王男
Owner SHANGHAI JIAO TONG UNIV