Abstract
This article explores and establishes comprehensive evaluation index system of wind power accommodation ability considering microscopic index and macroscopic index, and the index system includes conventional evaluation indexes such as forecast deviation, simultaneity factor and anti-peak rate, also newly introduced evaluation indexes such as installed capacity, power adequacy and accommodation space. Bayesian weight modified method is used for solving index weights of 8 wind power accommodation indexes. The paper puts forward a comprehensive evaluation model of wind power accommodation ability based on improved radar chart method, and this model changes traditional radar chart fan-shaped sector to quadrilateral evaluation region, and increasing angle bisector can solve the problem that evaluation results are not unique. It constructs new area and perimeter vectors of radar chart, which make the evaluation results give consideration to level of aggregation and balance degree of evaluation objectives, and case study results show that this model has a certain practical value.
Highlights
Wind power has volatility, intermittent and randomness characteristics, and it is different from thermal power, hydro-power and nuclear power
In power grid planning and construction, wind farms are often located in remote areas with weak grid construction, and wind power accommodation ability is very limited
How to evaluate wind power accommodation ability has already become one of the most important content of electric power researchers, and this problem for power grid operation and wind power development is of far-reaching significance
Summary
Intermittent and randomness characteristics, and it is different from thermal power, hydro-power and nuclear power. It introduces Bayesian weight modified method to solve index weight coefficients, and adopts improved radar chart method for the comprehensive assessment of wind power accommodation ability This method is intuitive and convenient, which can be effectively applied in actual operation of power grid. Forecast deviation index IFD is a statistical indicator in different time scales, which reflects the level of wind power forecasting technology, and its accuracy will affect the power grid day-ahead planning and scheduling [25] When this index value is too large, regular power supply needs to make corresponding power adjustment for the deviation, and it will affect wind power accommodation level in severe cases. The improved method in this paper is close to actual wind power accommodation ability evaluation index. The results may be slightly different from actual wind power
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