Research On Smoothing Control Based On Wind Power Trend Forecast Information

With the emphasis on energy security and environmental protection issues in various countries,wind power generation technology is developing rapidly,and the installed capacity of wind power is increasing.However,wind power has significant randomness and volatility,which will have a non-negligible impact on the safe and stable operation of the power grid and the quality of power supply.Improving the stability and controllability of the grid-connected power of the wind power generation system is of great significance for improving the utilization of wind resources and implementing a green sustainable development strategy.Configuring a battery energy storage system is one of the effective technical means to smooth wind power fluctuations and improve its grid-connection friendliness.However,the economy of existing battery energy storage has not yet met the requirements for large-scale applications.Therefore,while ensuring the effect of the energy storage system,improving the control method to increase the energy storage utilization rate and thereby reducing the energy storage configuration requirements has bright application prospects and great economic value.In view of the above,this paper aims at smoothing wind power fluctuations,and on the basis of sorting out the existing research results,a new battery energy storage system control method incorporating wind power prediction information is proposed,which significantly reduces the energy storage capacity configuration requirements.On this basis,a battery energy management strategy was further designed to maintain the battery in a reasonable state to ensure its service life.Finally,the impact of the actual operating characteristics of the battery energy storage system on the energy storage effect is discussed,and a control method that considers the detailed characteristics of the battery is designed to fully tap the potential of battery energy storage applications.Specifically,the research work of this paper mainly includes:1.Summarize the structure of wind storage combined power generation system and the basic principles and evaluation indicators of energy storage to smooth wind power fluctuations and energy storage configuration methods.Based on the characteristics of the wind power generation system,the method of generating wind power operation data based on NASA meteorological data is summarized,and the mathematical foundation of wind power spectrum composition and fluctuation smoothing is analyzed using Fourier transform as a tool.Subsequently,taking the first-order low-pass filter algorithm commonly used in scientific research and demonstration projects as an example,the basic idea of a typical control method for a battery energy storage system for fluctuation smoothing,that is,a smooth control method based on signal decomposition,is described.It can be summarized into two aspects:the extraction of fluctuating components to complete the smoothing task and the state-of-charge management to maintain the state of the energy storage system.2.In terms of extraction of fluctuation components,firstly,through the analysis of the time-frequency characteristics of the conventional moving average filter algorithm,it is proved that the phase lag caused by the low-pass filter delay is the main reason for reducing the utilization rate of energy storage capacity.Then,from the perspective of eliminating filter delay,a new quasi-zero phase filter incorporating trend prediction information into the central moving average filtering algorithm is proposed.Finally,the proposed filter is used to extract the wind power fluctuation component and design a wind power trend information prediction method adapted to it,thereby significantly reducing the trend component in the charge and discharge power of the energy storage system and reducing the energy storage capacity configuration requirements.3.In terms of energy storage energy management,first of all,through a comparative analysis of the principles of the first-order low-pass filter algorithm and the moving average algorithm,the shortcomings of the time window step in the energy storage energy management strategy based on slope control are explained.Then,from the perspective of eliminating time window steps,on the basis of slope control,an energy storage energy management strategy based on charge and discharge signs is proposed.By pre-judging the direction of energy storage charging and discharging,and correspondingly changing the time window,the goal of ensuring the smoothness of the grid-connected power after the extraction of the wind power fluctuation component based on the moving average is maintained on the basis of maintaining the energy storage operating in a reasonable interval.And the existing wind power fluctuation smoothing method based on the model predictive control method is described as a comparison based on the filter component extraction method.4.Based on the actual battery charge and discharge experimental data,construct a detailed model that reflects the battery energy storage operating characteristics,and discuss the impact of the battery's actual operating characteristics on the smoothing control effect.First,based on the charge and discharge experimental platform,HPPC test tests were carried out on the ternary and lithium iron phosphate cells commonly used in battery energy storage,and the parameters were identified by modeling the cells with a second-order RC equivalent circuit.Then,combined with the battery operating characteristics in the wind power smoothing application scenario,the second-order RC model is simplified to an internal resistance model to analyze the battery efficiency characteristics and power characteristics.Finally,through simulation examples,the difference between the smoothing effect of the battery energy storage system when using the simplified model and the detailed model is compared.