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Power fluctuation and allocation of hybrid energy storage system based on optimal exponential smoothing method and energy entropy

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AbstractIn order to solve the problems of power quality reduction and power fluctuation caused by large‐scale wind power grid‐connected, an advanced control strategy to smooth the power fluctuation and allocation of hybrid energy storage system is proposed. Based on theoretical researches, the mathematical model of hybrid energy storage system is adopted to well analyse the fluctuation and smoothing strategy of wind power. Compared with the traditional filtering algorithms, the study proposes a method combined optimal exponential smoothing with complete ensemble empirical mode decomposition with adaptive noise and normalized energy entropy to improve the accuracy of grid‐connected output power and power allocation. Furthermore, the fuzzy control theory is used to improve the reliability of the algorithm after obtaining the smoothed power output and initial power allocation instructions. To prove the validity of the algorithm, case studies are constructed to demonstrate the performance in this paper. Experiments and example simulations show that the proposed method can effectively realize adaptive power allocation and improve the accuracy of identification. After effectively improving the efficiency and service life of the energy storage system, it provides a basis for large‐scale grid operation.
Institution of Engineering and Technology (IET)
Title: Power fluctuation and allocation of hybrid energy storage system based on optimal exponential smoothing method and energy entropy
Description:
AbstractIn order to solve the problems of power quality reduction and power fluctuation caused by large‐scale wind power grid‐connected, an advanced control strategy to smooth the power fluctuation and allocation of hybrid energy storage system is proposed.
Based on theoretical researches, the mathematical model of hybrid energy storage system is adopted to well analyse the fluctuation and smoothing strategy of wind power.
Compared with the traditional filtering algorithms, the study proposes a method combined optimal exponential smoothing with complete ensemble empirical mode decomposition with adaptive noise and normalized energy entropy to improve the accuracy of grid‐connected output power and power allocation.
Furthermore, the fuzzy control theory is used to improve the reliability of the algorithm after obtaining the smoothed power output and initial power allocation instructions.
To prove the validity of the algorithm, case studies are constructed to demonstrate the performance in this paper.
Experiments and example simulations show that the proposed method can effectively realize adaptive power allocation and improve the accuracy of identification.
After effectively improving the efficiency and service life of the energy storage system, it provides a basis for large‐scale grid operation.

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