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Power Quality in Smart Distribution Systems with Electric Battery, Large Loads and PV Generation

机译:电气电池智能配电系统中电能质量,大负载和光伏发电

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A change in the electricity consumption is taking place, where one of the main reasons is the large increase in Distributed Generation, as photovoltaic (PV) systems and electric batteries in the low voltage (LV) distribution grid. This could translate in specific cases into a situation of increased peak load and bigger voltage fluctuation. Therefore, an effective control of the grid voltage is necessary to achieve a stable energy supply from renewable sources. What services can a battery provide? The authors present an analysis of voltage control and other battery services in a LV grid. A flexible model based on Python is developed and used to solve a multi-period optimal power flow problem. They propose an optimised distributed voltage regulation. The power flow equations are linearised around a stable operation point, which allows high feasibility and computation speed. Then a receding horizon framework is described, including 24h and 1h updated forecasts. The analysis is performed on a LV network with large loads of a stadium, large PV generation (690kWp) and with a 1MWh battery. The new method provides an optimization of the grid operation (reduced voltage variation and cost of energy imported from the grid) under different seasonal weeks.
机译:正在发生电力消耗的变化,其中主要原因之一是分布式发电的大幅增加,作为低电压(LV)分布网的光伏(PV)系统和电池。这可以在特定情况下转化为增加峰值负荷和更大电压波动的情况。因此,需要有效地控制电网电压,以实现来自可再生源的稳定能量供应。电池可以提供哪些服务?作者呈现了LV网格中的电压控制和其他电池服务的分析。开发了一种基于Python的灵活模型,并用于解决多周期最佳功率流问题。它们提出了优化的分布式电压调节。电流方程在稳定的操作点周围线性化,这允许高可行性和计算速度。然后描述了后退地平线框架,包括24h和1h更新的预测。该分析在具有大负载体育场,大型光伏发电(690kWP)和1MWH电池的LV网络上进行分析。新方法在不同的季节性周内提供了网格操作的优化(降低了从电网导入的电压的电压成本)。

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