scholarly journals Wind Power Consumption Research Based on Green Economic Indicators

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2829 ◽  
Author(s):  
Xiuyun Wang ◽  
Yibing Zhou ◽  
Junyu Tian ◽  
Jian Wang ◽  
Yang Cui

As a representative form of new energy generation, wind power has effectively alleviated environmental pollution and energy shortages. This paper constructs a green economic indicator to measure the degree of coordinated development of environmental and social benefits. To increase the amount of wind power consumption, an economic dispatch model based on the coordinated operation of cogeneration units and electric boilers was established; we also introduced the green certificate transaction cost, which effectively meets the strategic needs of China’s energy low-carbon transformation top-level system design. Wind power output has instability and volatility, so it puts higher requirements on the stable operation of thermal power units. To solve the stability problem, this paper introduces the output index of the thermal power unit and rationally plans the unit combination strategy, as well as introducing the concept of chance-constrained programming due to the uncertainty of load and wind power in the model. Uncertainty factors are transformed into load forecasting errors and wind power prediction errors for processing. Based on the normal distribution theory, the uncertainty model is transformed into a certain equivalence class model, and the improved disturbance mutated particle swarm optimization algorithm is used to solve the problem. Finally, the validity and feasibility of the proposed model are verified based on the IEEE30 node system.

Wind Energy ◽  
2012 ◽  
Vol 16 (7) ◽  
pp. 999-1012 ◽  
Author(s):  
Robin Girard ◽  
Denis Allard

2013 ◽  
Vol 392 ◽  
pp. 656-659
Author(s):  
Ting Yu ◽  
Zhao Yu Jin ◽  
Ying Yun Sun ◽  
Jing Huai Lin ◽  
Tian Jiao Pu

Large-scale wind power integrates in the grid to provide clean energy; however, it has a negative impact on the stable operation of the grid. To analysis the effect of wind power on frequency control, we need the help of simulation software. But, there has no frequency control mathematical model of wind farm in simulation software available for the user to choose. So this paper designs and establishes a frequency simulation platform, which provides the frequency control mathematical model of wind farms, hydroelectric power plants and thermal power plants. It can not only evaluate the impact of wind power fluctuations on frequency control, but also can quantitatively analysis of the system reserve capacity, as well as AGC performance monitoring function.


2022 ◽  
Vol 9 ◽  
Author(s):  
Bingbing Xia ◽  
Qiyue Huang ◽  
Hao Wang ◽  
Liheng Ying

Wind energy has been connected to the power system on a large scale with the advantage of little pollution and large reserves. While ramping events under the influence of extreme weather will cause damage to the safe and stable operation of power system. It is significant to promote the consumption of renewable energy by improving the power prediction accuracy of ramping events. This paper presents a wind power prediction model of ramping events based on classified spatiotemporal network. Firstly, the spinning door algorithm builds parallelograms to identify ramping events from historical data. Due to the rarity of ramping events, the serious shortage of samples restricts the accuracy of the prediction model. By using generative adversarial network for training, simulated ramping data are generated to expand the database. After obtaining sufficient data, classification and type prediction of ramping events are carried out, and the type probability is calculated. Combined with the probability weight, the spatiotemporal neural network considering numerical weather prediction data is used to realize power prediction. Finally, the effectiveness of the model is verified by the actual measurement data of a wind farm in Northeast China.


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