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Economical optimization of grid power factor using predictive data

机译:使用预测数据对电网功率因数进行经济优化

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We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an on-load tapchanger (OLTC) and transmission lines. The system power factor (PF) regulation and reactive power dispatching are indispensable to improve power quality. Our control method uses predictive weather and load data to decide engaging or tripping the shunt capacitor, or reactive power injection by the photovoltaic-inverter system, ultimately to keep the system PF in a good range. From the perspective of economics, the economical model is considered as a decision maker in our predictive data control method. Capacitor-only control strategy is a common photovoltaic (PV) regulation method, which is treated as a baseline case. Simulations with GridLAB-D on profiled loads and residential loads have been carried out. The comparison results with baseline control strategy and our predictive data control method show the appreciable economical benefit of our method.
机译:为了经济利益,我们提出了一种电网优化方法。在简化了IEEE馈线图之后,我们构建了一个紧凑的智能电网系统,包括光伏逆变器系统,并联电容器,有载分接开关(OLTC)和传输线。系统功率因数(PF)调节和无功功率分配对于提高电能质量必不可少。我们的控制方法使用预测性的天气和负载数据来确定并联电容器的接合或跳闸,或光伏逆变器系统注入的无功功率,最终将系统PF保持在良好的范围内。从经济学的角度来看,在我们的预测数据控制方法中,经济模型被视为决策者。仅电容器的控制策略是一种常见的光伏(PV)调节方法,被视为基准情况。已经使用GridLAB-D对轮廓荷载和住宅荷载进行了仿真。与基线控制策略和我们的预测数据控制方法的比较结果表明,该方法具有明显的经济效益。

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