多场景下光伏-双单元储能系统协同平抑功率波动控制策略

光伏发电的间歇性和随机性是制约其大规模发展的主要因素,由此文章提出一种适用于多场景的光伏-双单元储能系统协同平抑功率波动控制策略。首先,针对光伏电站多个典型出力场景,并结合并网限制要求,对光伏原始功率信号进行变分模态分解,求得并网目标功率和储能需求功率,并利用阈值补偿方法缩短计算时长;然后,通过协调互补的双单元储能系统对储能需求功率进行消纳,使得各储能单元能够在标准充、放循环深度内独立承担任务;最后,在Matlab平台上对所提信号分析算法的平抑效果,以及光伏-双单元储能系统协同平抑功率波动控制策略的普适性进行仿真验证。仿真结果表明,在多个典型场景下,所测得的并网目标功率均满足并网限制要求,所选的分析算法可有效平抑光伏出力的波动,该协同控制策略能够保证双单元储能系统的长期稳定运行,大幅度提高了光伏并网的可靠性。

Photovoltaic-dual units energy storage system cooperative smoothing power fluctuation control strategy in different scenes

The intermittent randomness of photovoltaic power generation is the main factor restricting its large-scale development.Aiming at the above situation,a collaborative optimization control strategy based on the smoothing of photovoltaic output fluctuations in dual units energy storage system is proposed.Firstly,aiming at the different typical scenes of original photovoltaic power,the original photovoltaic power are subjected to variational mode decomposition in combination with the power fluctuation standards,and the grid-connected target power and energy storage demand power are obtained,use the method of threshold compensation to shorten the calculation time;then using the coordinated and complementary dual units energy storage system to absorb the energy demand of the energy storage,so that the energy storage unit can take tasks independently within the standard charge and discharge cycle depth;finally,the smoothing effect of the signal analysis algorithm and the universality of the collaborative optimization control strategy of the dual units energy storage system are simulated and verified on the Matlab platform.The simulation results show that in different typical scenes,the grid-connected target power satisfies the grid-connected fluctuation standard,and the analysis algorithm can effectively smooth the photovoltaic output fluctuation,the proposed cooperative optimization control strategy not only ensure the long-term stable operation of the dual units energy storage system,but also can greatly improve the reliability of photovoltaic grid-connected.