Abstract
Today, wind power is becoming an important energy source for the future development of electric energy due to its clean and environmentally friendly characteristics. However, due to the uncertainty of incoming wind, the utilization efficiency of wind energy is extremely low, which means the problem of wind curtailment becomes more and more serious. To solve the issue of wind power large-scale consumption, a two-stage stochastic optimization model is established in this paper. Different from other research frameworks, a novel two-side reserve capacity mechanism, which simultaneously takes into account supply side and demand side, is designed to ensure the stable consumption of wind power in the real-time market stage. Specifically, the reserve capacity of thermal power units is considered on the supply side, and the demand response is introduced as the reserve capacity on the demand side. At the same time, the compensation mechanism of reserve capacity is introduced to encourage generation companies (GENCOs) to actively participate in the power balance process of the real-time market. In terms of solution method, compared with the traditional k-means clustering method, this paper uses the K-means classification based on numerical weather prediction (K-means-NWP) scenario clustering method to better describe the fluctuation of wind power output. Finally, an example simulation is conducted to analyze the influence of reserve capacity compensation mechanism and system parameters on wind power consumption results. The results demonstrate that with the introduction of reserve capacity compensation mechanism, the wind curtailment quantity of the power system has a significant reduction. Besides, the income of GENCOs is gradually increasing, which motivates their enthusiasm to provide reserve capacity. Furthermore, the reserve capacity mechanism designed in this paper promotes the consumption of wind power and the sustainable development of renewable energy.
Highlights
We introduce a reserve capacity compensation mechanism and propose a two-stage stochastic optimization model based on demand response and wind power consumption on the basis of considering the total cost of the day-ahead stage and the real-time stage
The wind power output is divided into three scenarios—high, medium, and low—and the actual unit data and market data are used to analyze the system operation result and wind power consumption situation with or without a reserve capacity compensation mechanism and to compare the influence of different parameters in the system on the wind power consumption result
The conclusions are as follows: (1) Operating results in a variety of wind power output combination scenarios all prove that after the introduction of reserve capacity compensation mechanism, the system’s wind abandoning capacity is significantly reduced, and thermal units and interruptible loads are significantly more active in providing reserve capacity, which is conducive to maintaining system balance and promoting wind power consumption
Summary
With the excessive consumption of fossil energy, energy transformation has been paid attention by all countries worldwide. Renewable energy generation will become the main method of electric energy production in the future. These clean energy sources have some disadvantages. With their large-scale penetration, the uncertainty of market balance will increase, resulting in the power system operation facing serious challenges. For this reason, countries around the world have not been very effective in large-scale use of clean energy. How to use renewable energy such as wind energy efficiently and reduce spillage of wind power is the main problem to be solved in this paper. The establishment of a compensation mechanism for reserve capacity will encourage more and more power generation manufacturers to provide more reserve capacity in the real-time stage, offer sufficient reserve space for wind power, and promote wind power consumption
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