电池、大负荷和光伏发电智能配电系统的电能质量。

M. Ortiz, Idar Petersen, R. Mikut, Henrik Landsverk, S. Simonsen
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引用次数: 1

摘要

电力消费正在发生变化,其中一个主要原因是分布式发电的大量增加,如光伏(PV)系统和低压(LV)配电网中的电池。在特定情况下,这可能会导致峰值负载增加和电压波动更大。因此,有效控制电网电压是实现可再生能源稳定供电的必要条件。电池能提供什么服务?作者对低压电网中的电压控制和其他电池服务进行了分析。基于Python开发了一个灵活的模型,并将其用于求解多周期最优潮流问题。他们提出了一种优化的分布式电压调节。功率流方程在稳定运行点附近线性化,具有较高的可行性和计算速度。然后描述了一个后退地平线框架,包括24h和1h更新的预测。该分析是在一个低压网络上进行的,该网络具有体育场的大负载,大型光伏发电(690kWp)和1MWh电池。该方法在不同的季节周提供了电网运行的优化(减少电压变化和从电网进口的能源成本)。
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Power Quality in Smart Distribution Systems with Electric Battery, Large Loads and PV Generation.
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.
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