Abstract:  ABSTRACT： The energy storage system is widely used because of the role of power smoothing of renewable energy generation. But the nonlinear, non Gauss and fast dynamic characteristics of energy storage system make the real-time monitoring and accurate identification of typical working conditions become the key and difficulty of ensuring the stable operation of the system. In view of the large number of estimation parameters in the traditional nonlinear autoregressive （NAR） model, this paper proposes the Laguerre expansion analysis method to improve the accuracy of bispectrum estimation, and designs a new identification method for typical operating conditions of energy storage system based on Laguerre-NAR bispectrum estimation, which can extracts the signal phase information accurately and realizes the fast recognition of high frequency resolution. Simulation analysis is carried out on the measured data of energy storage system for wind power integration power smoothing. The simulation results verify the effectiveness and feasibility of the proposed Laguerre-NAR bispectrum estimation method.

Key words:  KEYWORDS：  , Laguerre expansion, bispectrum estimation, energy storage system, regime recognition