面向系统灵活性提升的大用户激励型需求响应优化策略

doi:10.19595/j.cnki.1000-6753.tces.240822

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Abstract

With the increasing scale of renewable energy such as wind and solar energy into the power system, its generation power volatility and uncertainty make the system net load curve steeper. Independent system operators (ISO) needs to introduce more flexible resources to cope with the surge in flexibility ramping products (FRP) demand. Implementing demand response (DR) for large-scale users has become an important way to improve system flexibility. How to design reasonable incentive compensation measures to guide large-scale users to provide DR services and participate in the FRP market is of great significance to improve the flexibility of the system. Existing studies have proposed reasonable incentive compensation mechanisms and DR strategies under the market environment, but have not considered the relationship between the difference of large-scale users' response willingness and response cost. Therefore, this paper proposed a DR optimization strategy that adapts to the joint clearing of electric energy and FRP, and realized differentiated compensation according to the response willingness of large-scale users.
First, the customer demand management behavior model (CDMBM) was used to estimate the response cost function of users by using the historical DR participation data of large- scale users. Characterizing the differences in user response costs by introducing a response willingness parameter in the cost function. The higher the willingness of large-scale users to respond, the lower the cost of response. CDMBM provided a basis for the accurate modeling of large-scale users' decision behaviors of reduction-type DR and absorption-type DR.
Secondly, an incentive DR master-slave game model was constructed between ISO and multiple large-scale users. The upper level model was the optimization model of joint clearing of electric energy and FRP with ISO as the decision-making body, and the lower level model was the optimization model of DR decision-making with large-scale users participating in the joint market. ISO aimed to minimize incentive compensation costs with the goal of meeting the flexibility requirements, while large-scale users aimed to maximize the benefits of providing DR services. Both parties are interdependent.
Finally, by taking the KKT condition of the lower model as the constraint condition of the upper model, the master-slave game problem was transformed into a mathematical optimization problem with linear equilibrium constraint for solving. The game behavior between ISO and large-scale users was described by the master-slave game equilibrium. The DR unit incentive compensation cost considering user differentiation was obtained according to the equilibrium result of the game between both parties.
The results show that differentiated compensation is carried out according to the response willingness of large-scale users. Large-scale users are effectively encouraged to participate in the joint clearing market of electric energy and FRP market. The unit incentive compensation cost not only meets the needs of large-scale users and ISO, but also effectively alleviates the sharp increase in incentive compensation costs when there is a lack of flexible ramping capability. Large-scale users reserve flexible ramping capacity in the FRP market to provide flexible climbing capacity, which reduce the pressure of thermal power units. The cost of FRP accounts for only 0.31% of the total system cost. The proposed DR optimization strategy enhances the system's flexibility while considering economic efficiency.

Key words： Demand response Flexible ramping products(FRP) market master-slave game equilibrium constraints unit incentive compensation cost

Received: 21 May 2024

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	Huang Dawei
	Guo Niankang
	Yu Na
	Kong Lingguo

Cite this article:

Huang Dawei,Guo Niankang,Yu Na等. Optimization Strategy for Enhancing System Flexibility Through Incentive Demand Response of Large-Scale Users[J]. Transactions of China Electrotechnical Society, 0, (): 240822-240822.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.240822 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/240822

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