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| Game Optimization Scheduling of High Proportion Wind Power and Multiple Flexible Resources Considering Flexibility Compensation |
| Pan Zhengnan1, Deng Changhong2, Xu Huihui3, Liang Ning1, He Xiyu1 |
1. Faculty of Electric Power Engineering Kunming University of Science and Technology Kunming 650000 China;
2. School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China;
3. Institute of Economic Technology State Grid Gansu Electric Power Company Lanzhou 730000 China |
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Abstract The large scale grid connection of new energy sources, mainly wind power, has led to increasing uncertainty and anti-peak characteristics of the system, and the system is facing a huge challenge in terms of power balance. At present, scholars have explored the flexibility regulation potential of the system from multiple levels of "source-load-storage", which has improved the flexibility of system operation to a certain extent, but there are problems such as the lack of incentive mechanisms for flexibility regulation, the lack of reasonable compensation for the flexibility value of flexibility resources, and the lack of enthusiasm of flexibility resources to participate in regulation. This paper proposed an optimal dispatching method taking into account the game between a high proportion of wind power and multiple flexibility resources. On the basis of the individual profit-seeking properties of wind power and each flexibility resource subject, it used the idea of Stackelberg game to establish a multi-object game optimal dispatching model for supply and demand of flexibility regulation services, so as to achieve the optimization of supply and demand of flexibility resources and reasonable compensation of flexibility value.
Firstly, considering the spatial and temporal coupling characteristics of wind power volatility and load volatility, the evaluation index of wind power volatility was defined, and based on this, a method for quantifying the demand for wind power flexibility regulation was proposed. Secondly, considering the differences and tendency of each flexibility resource's decisions, a method of equilibrium analysis of flexibility supply and demand based on Stackelberg game was proposed, and an optimization model of flexibility resource supply and demand game was established with the objective of maximizing the interests of each subject. Finally, the proposed method was verified through simulation cases that the proposed method can effectively improve the enthusiasm of multiple flexibility resources to participate in regulation and promote the online consumption of a high proportion of wind power.
The simulation results of the new power system with high percentage of wind power show that the proposed model effectively improves the depth of thermal power peaking and the enthusiasm of energy storage and demand response to participate in flexibility regulation during the high time of wind power at night. And it achieves the full consumption of wind power. Meanwhile, in terms of economics, the proposed model improves the net benefits of thermal power, energy storage, and demand response, so that the individual value of each flexibility resource subject converges with the system's flexible operation goal. The experimental results under different flexibility resource adequacy show that the higher the flexibility resource adequacy of the system, the lower the flexibility regulation cost of wind power, and the more economical and efficient the consumption of wind power. The sensitivity analysis results of the volatility assessment index parameters show that the larger the R is, the gradually less volatility balancing responsibility the wind power operator needs to bear, and the volatility of the residual load gradually rises, and setting a reasonable R value can realize a reasonable division of the volatility balancing responsibility and effectively protect the interests of each subject.
The following conclusions can be drawn from the simulation analysis: (1) The flexibility compensation mechanism can effectively increase the enthusiasm of flexibility resources to participate in regulation, fully exploit the flexibility regulation potential of source-load-storage, and promote the online consumption of a high proportion of wind power. (2) After adopting the Stackelberg game strategy proposed in this paper to optimize the supply and demand of flexibility resources, it effectively reflects the supply and demand of flexibility resources, and the flexibility values of thermal power operators, energy storage operators and demand response aggregators are reasonably compensated. (3) The volatility assessment index can realize the management of wind power feed-in volatility and effectively reduce the difficulties caused by high percentage of wind power volatility on power balance.
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Received: 09 January 2023
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2023, Vol. 38 
