Wind speed modeling for cascade clusters of wind turbines Part 2: Wind speed reduction and aggregation superposition

Highlights: • Based on the characteristics of cascading coupling, the algorithm of "CE" and "AE" in the CCWT is proposed. • The WSR calculation model with the WT location distribution and WT performance parameters is established. • The WSR unified parameter model of the WTs in CE is obtained; 4. The WSAS algorithm for the WTs of AE is improved;. • The wind speed calculation model of the cascade coupling WTs is put forward. Wind speed calculation is not only the core problem of the wind energy conversion, but also the key to improve the WT conversion efficiency. Wind speed is affected by many factors, so it is difficult to model. The influencing factors of the wind speed and relationship between wind speed are contained in big data of the WTs' historical monitoring. In this paper, the "coupling element" (CE) and "aggregation element" (AE) of cascade clusters of wind turbines (CCWT) at different wind speeds are taken as the research objects to study the characteristics of the wind speed reduction (WSR) and aggregation superposition. We analyze and calculate the numerical relations in the historical data of the WTs, and obtain the WSR model of CE including the WTs distribution and state parameters. This paper further analyzes the distribution characteristics of the AE, studies the aggregation distribution and convergence form of multiple incoming streams, and puts forward the wind speed aggregation superposition (WSAS) model of AE which considers the friction energy dissipation between the different incoming streams. The WSR and aggregation model of the WTs in CCWT proposed in this paper has been verified by the examples with high accuracy and robustness.