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AI-Aided Region-Based Active Stabilization in Autonomous DC Microgrids

机译:基于AI辅助区域的自主DC微电网中的主动稳定

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Creating DC microgrids (MGs) to achieve local source and load balance is becoming a grand possibility with the introduction of inverter-based resources (IBR), e.g. photovoltaics (PV), energy storage systems (ESS), etc. Autonomous DC MGs can be implemented to reduce fossil fuel consumption and energize remote communities. This paper begins with the mathematical modeling of DC-DC source converters, then proceeds to apply a virtual impedance loop to increase autonomous stability of DC MGs. The concept of a stability region boundary (SRB) based on two system parameters is introduced and then determined by the artificial intelligence (AI) aided Kernel Ridge Regression (KRR) approach. The SRB is verified by a four-converter DC MG through time-domain simulation in MATLAB/Simulink.
机译:创建DC Microgrids(MGS)以实现当地来源和负载余额正在成为引入基于逆变器的资源(IBR)的隆重可能性,例如, 光伏(PV),储能系统(ESS)等。可以实施自主DC MGS,以减少化石燃料消耗和激励远程社区。 本文从DC-DC源转换器的数学建模开始,然后继续应用虚拟阻抗环以增加DC MGS的自主稳定性。 介绍了基于两个系统参数的稳定区域边界(SRB)的概念,然后由人工智能(AI)辅助核RIGE回归(KRR)方法确定。 通过MATLAB / Simulink中的时域模拟,通过四转换器DC MG验证SRB。

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