Capacity configuration method of hybrid energy storage system for stabilizing wind power fluctuation

Abstract

The invention provides a capacity configuration method of a hybrid energy storage system for stabilizing wind power fluctuation. The hybrid energy storage system comprises a power type energy storage system and an energy type energy storage system. The method includes the steps that (1) the grid connection active power of wind power and the active power P (t) of the hybrid energy storage system are acquired, and a wavelet packet decomposition method is utilized to acquire power type energy storage power and energy type energy storage power respectively; (2) the hybrid energy storage system at different rated power P and under different capacities is configured, and the stabilizing effect of the hybrid energy storage system is analyzed; (3) according to the stabilizing effect and an improved particle swarm algorithm, the capacity of the hybrid energy storage system is configured. Compared with the prior art, according to the capacity configuration method of the hybrid energy storage system for stabilizing wind power fluctuation, a control policy is built according to the current electric quantity conditions, power magnitude required to be exerted and the rated power of the power type energy storage system and the energy type energy storage system and the improved particle swarm algorithm, and wind power fluctuation is stabilized and effectively controlled.

Description

technical field [0001] The invention relates to a capacity configuration method of a hybrid energy storage system, in particular to a hybrid energy storage capacity configuration method for smoothing intermittent power fluctuations. Background technique [0002] Wind power generation has been widely used due to its high efficiency and cleanliness. However, the large randomness and fluctuation of wind speed affect the safety and stability of wind power grid-connected operation, resulting in a serious waste of wind power station power. According to the current wind power grid connection standard GB / T19963-2011 "Technical Regulations for Wind Farm Connected to Power System", the limit value of wind power active power change ΔP limit Refer to Table 1: [0003] Table 1 Recommended list of active power change limits [0004] [0005] The energy storage system is considered to be an effective means to stabilize wind power fluctuations and improve the ability of the grid to acc...

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Problems solved by technology

However, the energy distribution principle of the hybrid energy storage system composed of power type and energy type has become a limiting factor for the use of hybrid energy storage systems to stabilize wind power fluctuations

[0006] The literature "Research on the Probability Distribution of Wind Power Fluctuation Characteristics" discloses the method of obtaining the continuous component and the fluctuating component of the active power signal of wind power, but it does not disclose the selection principle of the window length and the influence of the window length on the decomposition effect, and it is impossible to judge whether the continuous component can Meet the requirements of wind power grid connection; the document "Wavelet Transform-Based Decomposition of Hydrological Time Series" discloses the method of wavelet transform for time series decomposition, and the document "Review and Development Research of Wind Power Forecasting Methods" discloses that wavelet analysis can be used for wind power forecasting However, the specific wavelet analysis method is not disclosed; the document "Optimized Configuration of Power and Capacity of Energy Storage System in Wind Farm" discloses the improved particle swarm optimization algorithm to optimize capacity configuration, but only from the perspective of engineering indicators, after satisfying the constraints Optimizing the engineering objective function does not analyze economically. Under the condition of satisfying the determined engineering indicators and constraints, configure the most economical and most suitable hybrid energy storage system configuration method; "Configuration Research" proposes an economical-oriented improved particle swarm optimization algorithm for the capacity optimization of photovoltaic power generation hybrid energy storage systems, but this algorithm only changes the learning factor linearly, and cannot effectively jump out of the local optimum and seek the global optimum

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