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MPC-Based Voltage/Var Optimization for Distribution Circuits With Distributed Generators and Exponential Load Models

机译:基于MPC的带有分布式发电机和指数负载模型的配电电路电压/电压优化

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摘要

This paper proposes a model predictive control (MPC)-based voltage/var optimization (VVO) technique considering the integration of distributed generators and load-to-voltage sensitivities. The paper schedules optimal tap positions of on-load tap changer and switch statuses of capacitor banks based on predictive outputs of wind turbines and photovoltaic generators. Compared with previous efforts on VVO which used constant-power load model, the exponential load model is used to capture the various load behaviors in this paper. Different customer types such as industrial, residential, and commercial loads are also considered. The uncertainties of model prediction errors are taken into account in the proposed model. A scenario reduction technique is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. The MPC-based VVO problem is formulated as a mixed-integer nonlinear program with reduced scenarios. Case studies show the effectiveness of the proposed method.
机译:本文提出了一种基于模型预测控制(MPC)的电压/无功优化(VVO)技术,该技术考虑了分布式发电机的集成以及负载对电压的敏感性。本文基于风力涡轮机和光伏发电机的预测输出,调度有载分接开关的最佳分接位置和电容器组的开关状态。与以前使用恒功率负载模型的VVO相比,本文采用指数负载模型来捕获各种负载行为。还考虑了不同的客户类型,例如工业,住宅和商业负载。在模型中考虑了模型预测误差的不确定性。应用场景减少技术来增强解决方案的准确性和计算负担之间的权衡。基于MPC的VVO问题被公式化为具有减少场景的混合整数非线性程序。案例研究表明了该方法的有效性。

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