基于电池储能系统的综合自适应一次调频策略

doi:10.19595/j.cnki.1000-6753.tces.240456

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摘要

由于传统的电池储能系统控制策略抑制电网频率恶化效果较差,进而限制了电池储能系统参与一次调频时的性能。因此,该文提出基于电池储能系统的综合自适应一次调频策略。首先,为了减少电网频率偏差,将趋势控制策略和惯性与下垂控制策略相结合,抑制电网频率恶化;其次,自适应控制储能系统出力系数,趋势系数随着电网频率加速度自适应变化,惯性系数随着电网频率变化率自适应变化,下垂系数随着电网频率偏差自适应变化,提高储能系统自适应能力;最后,为了防止储能电池过充过放,提高荷电状态（SOC）估算精度,提出多元自适应估算SOC方法,减少SOC估算误差。通过仿真实验验证了所提控制策略的有效性。该研究成果可为储能系统参与一次调频方面的研究提供有益参考。

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	梁继业
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关键词 ：一次调频, 惯性与下垂控制策略, 趋势控制策略, 自适应, SOC估算

Abstract：

The primary frequency control of thermal power units has low energy efficiency and negative impact on the environment. The energy storage battery has the characteristic of fast response speed, but the control strategy of the energy storage system only considers the State of Charge (SOC) near the minimum value in the discharge state, or the adaptive control when SOC is near the maximum value in the charging state, which has poor adaptability and does not consider the SOC estimation accuracy. As a result, the control strategy of the energy storage system has poor effect on inhibiting the deterioration of the power grid frequency, and then limits the performance of the energy storage system when it participates in the primary frequency control. To solve this problem, this paper proposes a comprehensive adaptive primary frequency control strategy based on battery energy storage system.
Firstly, the trend control strategy and the inertia and sag control strategy are combined to define the trend output of the battery energy storage system and the frequency acceleration of the power grid, and explain the relationship among the frequency acceleration, frequency change rate and frequency deviation of the power grid. Secondly, the output coefficient of the battery energy storage system is adaptive control, and the trend coefficient is determined according to the frequency acceleration of the power grid, the inertia coefficient is determined according to the frequency change rate of the power grid, and the sag coefficient is determined according to the frequency deviation of the power grid, so as to improve the adaptive ability of the energy storage system. Finally, in order to prevent the energy storage battery from overcharging and over discharging and improve the SOC estimation accuracy, a multi-element adaptive SOC estimation method is proposed.
Simulation results show that in the step load disturbance, the maximum frequency deviation and steady-state frequency deviation of the proposed method are the smallest, which are -0.061 Hz and -0.049 Hz respectively. Compared with the adaptive method, the maximum frequency deviation and steady-state frequency deviation are reduced by 20.7% and 40.0% respectively. SOC has the highest accuracy, with a maximum error of 0.09% and an average error of 0.01%. In the short-time continuous load disturbance, the grid frequency deviation of the proposed method is 0.038 Hz, the peak-to-peak value is 0.126 Hz, the average SOC is 0.474, the peak-to-peak value is 0.052, and the grid frequency deviation is the smallest, and the SOC fluctuation is large. In the case of long-term continuous load disturbance, the frequency deviation and peak-to-peak value of the proposed method are 0.035 Hz and 0.126 Hz respectively, and the single frequency control effect is the best. Compared with the adaptive method, the average frequency difference deviation and frequency peak-to-peak value are reduced by 50.0% and 21.5% respectively.
The following conclusions are drawn: (1) The trend control strategy can slow down the frequency deterioration, speed up the frequency recovery and reduce the maximum frequency deviation of the power grid. (2) Adaptive determination of output coefficient effectively reduces the maximum steady-state frequency deviation of the power grid and improves the adaptability of the energy storage system. (3) The multi-component adaptive humic acid SOC method is mainly based on ampere-hour integration method, and gradually transitions to Kalman filter method, which effectively reduces the maximum and average estimation errors.

Key words： Primary frequency control inertia and sag control strategy trend control strategy self-adaptation SOC estimation

收稿日期: 2024-03-22

PACS:

TM614

基金资助:

新疆维吾尔自治区重大科技专项项目（2022A01004-1）和国家自然科学基金项目（52067020）资助

通讯作者: 袁至男,1984年生,副教授,研究生生导师,研究方向为可再生能源发电与并网控制。E-mail：yzisthecure@163.com

作者简介: 梁继业男,1999年生,硕士研究生,研究方向储能技术应用。E-mail：2267599319@qq.com

引用本文:

梁继业, 袁至, 王维庆, 李骥. 基于电池储能系统的综合自适应一次调频策略[J]. 电工技术学报, 0, (): 240456-240456. Liang Jiye, Yuan Zhi, Wang Weiqing, Li Ji. Comprehensive Adaptive Primary Frequency Control Strategy Based on Battery Energy Storage System. Transactions of China Electrotechnical Society, 0, (): 240456-240456.

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