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Stochastic power management strategy for hybrid energy storage systems to enhance large scale wind energy integration
Journal of Energy Storage ( IF 8.9 ) Pub Date : 2020-07-08 , DOI: 10.1016/j.est.2020.101650
Linda Barelli , Dana-Alexandra Ciupageanu , Andrea Ottaviano , Dario Pelosi , Gheorghe Lazaroiu

The strong variability of renewable energy sources (RES) often hinders their integration in power systems. Hybrid energy storage systems (HESS), based on complementary storage technologies, enable high RES penetration towards modern and sustainable power generation, improving energy systems performances and stability, while reducing CO2 emission. This paper introduces a novel power management strategy for a HESS consisting of a flywheel and a LiFePO4 battery coupled to a 2 MW wind turbine operating in interconnected mode. The power management strategy is based on the simultaneous perturbation stochastic approximation (SPSA) principle and targets a smoother power profile at the point of interface to the grid and, at the same time, a reduced solicitation of the battery. The underlying algorithm falls within the gradient-based optimization category, being able to pursue the envisaged goals without requiring a detailed model of the objective function. The main and novel contribution of this research aims to extend the SPSA recognized advantages, demonstrated in control applications, in the field of real-time HESS power management. Real datasets are employed to size an economic storage section and define representative simulation scenarios in order to validate the suitability of the proposed approach. Simulations are performed over one day timeframe in Matlab/Simulink for the most representative days extracted from the wind turbine yearly generation profile, employing a 1 s timestep. Results obtained prove that the proposed strategy ensures a substantially reduction of the power profile fluctuations at the point of interface to the grid, by more than 80% compared to the wind profile. Moreover, a power ramp mitigation of 65% on average towards the battery if compared to the flywheel.



中文翻译:

混合动力储能系统的随机功率管理策略可增强大规模风能集成

可再生能源(RES)的强大可变性通常会阻碍其在电力系统中的集成。基于互补存储技术的混合能源存储系统(HESS)使RES渗透到现代和可持续的发电中,提高了能源系统的性能和稳定性,同时减少了CO 2排放。本文介绍了一种由飞轮和LiFePO 4组成的HESS的新型电源管理策略电池耦合到以互连模式运行的2兆瓦风力涡轮机。功率管理策略基于同时扰动随机逼近(SPSA)原理,并且目标是在与电网的接口点处具有更平滑的功率分布,同时减少了对电池的需求。底层算法属于基于梯度的优化类别,能够实现设想的目标,而无需目标函数的详细模型。这项研究的主要创新成果旨在扩展SPSA在实时HESS功率管理领域在控制应用中展示的公认优势。实际数据集用于确定经济存储区的大小并定义代表性的模拟方案,以验证所提出方法的适用性。在Matlab / Simulink的一天时间范围内,使用1 s的时间步,对从风力涡轮机年发电量曲线中提取的最具代表性的日期进行了模拟。所获得的结果证明,所提出的策略可确保与风电接口相比,在与电网接口处的功率曲线波动大幅降低80%以上。此外,与飞轮相比,电池的平均功率缓和率降低了65%。所获得的结果证明,所提出的策略可确保与风电接口相比,在电网接口处的功率曲线波动大幅降低80%以上。此外,与飞轮相比,电池的平均功率缓和率降低了65%。所获得的结果证明,所提出的策略可确保与风电接口相比,在电网接口处的功率曲线波动大幅降低80%以上。此外,与飞轮相比,电池平均降低了65%的功率斜坡。

更新日期:2020-07-08
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