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Aggregated BESS Dynamic Models for Active Distribution Network Studies
IEEE Transactions on Smart Grid ( IF 8.6 ) Pub Date : 2020-12-31 , DOI: 10.1109/tsg.2020.3048648
Fabian Calero 1 , Claudio A. Canizares 1 , Kankar Bhattacharya 1
Affiliation  

This article proposes a transmission-system-level aggregated model of Battery Energy Storage Systems (BESSs) distributed through Active Distribution Networks (ADNs), to study the dynamic performance and services provided by these systems to power grids. ADNs comprise intelligent loads, local generation, particularly solar PV, and BESSs, which can provide different services to transmission grids, including voltage control, oscillation damping, frequency regulation, and active and reactive power injections. Proper equivalent models of the ADN components allow to evaluate the impact and integration of these networks on power grids. In this article, ADN’s measurements of the aggregated response of the BESSs at the boundary bus with the transmission system are used to develop an aggregated black-box model based on two Neural Networks (NNs), one for active power and another for reactive power, with their optimal topology obtained using a Genetic Algorithm (GA). Detailed simulations are performed, using a commercial-grade software for power system analysis, of multiple BESSs connected to a CIGRE benchmark ADN connected to a bus of the 9-bus WSCC benchmark transmission network; the test ADN is then replaced by the proposed black-box model, with aggregated models of the loads and PV generation, demonstrating that the proposed model can accurately reproduce the results obtained.

中文翻译:

用于主动配电网络研究的聚合BESS动态模型

本文提出了一种通过主动分配网络(ADN)分配的电池储能系统(BESS)的传输系统级聚合模型,以研究这些系统向电网提供的动态性能和服务。ADN包括智能负载,本地发电(尤其是太阳能PV)和BESS,它们可以为输电网提供不同的服务,包括电压控制,振荡阻尼,频率调节以及有功和无功注入。ADN组件的适当等效模型可以评估这些网络对电网的影响和集成。在本文中,ADN对带有传输系统的边界总线上的BESS聚合响应的测量被用于开发基于两个神经网络(NN)的聚合黑匣子模型,一种用于有功功率,另一种用于无功功率,其最佳拓扑是使用遗传算法(GA)获得的。使用用于商业电力系统分析的商业级软件,对连接到CIGRE基准ADN的多个BESS(连接到9总线WSCC基准传输网络的总线)进行详细的仿真;然后,将测试ADN替换为建议的黑匣子模型,以及负载和PV生成的汇总模型,这表明建议的模型可以准确地重现所获得的结果。连接到CIGRE基准ADN的多个BESS,连接到9总线WSCC基准传输网络的总线;然后,将测试ADN替换为建议的黑匣子模型,以及负载和PV生成的汇总模型,这表明建议的模型可以准确地重现所获得的结果。连接到CIGRE基准ADN的多个BESS,连接到9总线WSCC基准传输网络的总线;然后,将测试ADN替换为建议的黑匣子模型,以及负载和PV生成的汇总模型,这表明建议的模型可以准确地重现所获得的结果。
更新日期:2020-12-31
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