周坤, 许云飞, 崔昊杨, 李树林. 基于预测控制的多种新能源互补电力系统动态调度模型[J]. 现代电力, 2021, 38(3): 248-257. DOI: 10.19725/j.cnki.1007-2322.2020.0435
引用本文: 周坤, 许云飞, 崔昊杨, 李树林. 基于预测控制的多种新能源互补电力系统动态调度模型[J]. 现代电力, 2021, 38(3): 248-257. DOI: 10.19725/j.cnki.1007-2322.2020.0435
ZHOU Kun, XU Yunfei, CUI Haoyang, LI Shulin. A Predictive Control Based Dynamic Dispatch Model for Complementary Power System Containing Multi-Renewable Energy Sources[J]. Modern Electric Power, 2021, 38(3): 248-257. DOI: 10.19725/j.cnki.1007-2322.2020.0435
Citation: ZHOU Kun, XU Yunfei, CUI Haoyang, LI Shulin. A Predictive Control Based Dynamic Dispatch Model for Complementary Power System Containing Multi-Renewable Energy Sources[J]. Modern Electric Power, 2021, 38(3): 248-257. DOI: 10.19725/j.cnki.1007-2322.2020.0435

基于预测控制的多种新能源互补电力系统动态调度模型

A Predictive Control Based Dynamic Dispatch Model for Complementary Power System Containing Multi-Renewable Energy Sources

  • 摘要: 为了解决多种新能源互补运行时的消纳困难,以及降低新能源夜间波动造成电压频繁越限的问题,提出了一种基于预测控制的多种新能源互补电力系统动态调度模型。首先分析了光伏发电和风力发电的时间性,以及用户生活和生产用电短期内环比波动较小的特征,利用改进自适应阈值隶属度的小波滤波方法对光伏、风力发电历史数据进行去噪,以实现数据真实性还原;然后将去噪后的数据输入到改进的差分整合移动平均自回归模型中,对未来一段时间的发电量和用电量进行预测;将预测发电量、用电量作为分解原函数和扩增函数,改进同步型交替方向乘子法(synchronous alternating direction method of multipliers,SADMM);最后,通过将各时段预测的新能源发电量作为下一次迭代计算值的固定值,对SADMM进行迭代值修正,达到动态经济调度的目的。实验结果表明,该模型有效降低了91%的电压越限告警,并且经济性较传统方法提高了5%。

     

    Abstract: To cope with the difficulty of accommodation during complementary operation of multi-renewable energy sources and mitigate the frequent voltage out-of-limit caused by the fluctuation of renewable energy sources in the night, a predictive control based dynamic dispatching model for the power system containing complementary multi-renewable energy sources was proposed. Firstly, the timeliness of both photovoltaic (abbr. PV) power generation and wind power generation as well as the feature of slightly fluctuation of chain relative ratio of household demand and production demand of electricity in a short term were analyzed, and the wavelet filtering method with improved adaptive threshold membership was utilized to denoise the historical data of PV generation and wind generation to restore the data authenticity. Secondly, the denoised data was input into the improved autoregressive integrated moving average model (abbr. ARIMA) to predict the generated energy and electricity consumption in a future time period, and taking the predicted generated energy and electricity consumption as the decomposition function and the augmented function the synchronous alternating direction method of multipliers (abbr. SADMM) was improved. Finally, using the predicted generated energy of renewable energy sources in all time intervals as the fixed value of next iterative computation, the iterated value of SADMM was modified to achieve the purpose of dynamic economic dispatching. Experimental results show that using the proposed model the times of alarm of voltage out-of-limit is reduced by 91%, besides, the economy of the power system is improved by 5% than traditional method.

     

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