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Design of Hybrid System Power Management Based on Load Demand Using Operational Control System

机译:使用操作控制系统基于负载需求的混合系统电源管理设计

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Renewable energy is a limited energy source that involves of sunshine, wind, and water. It's normally used as sources of renewable power plants. Despite of its advantages, these power plants also contribute some disadvantages, such as high generation costs, highly dynamic behavior, etc. The disadvantages are being raised due to instability of the energy sources (RER). This study is aimed to design power management of a hybrid system based on operational control system based Artificial Neural Network (ANN) based on load demand. In this study, Power Management of Hybrid System used 3 power plants: Photovoltaic (PV), Wind Power, and Micro Hydro Power Plant (MHPP), while Battery was employed as storage system. Main focus of the work was to determine the activation of each plant using ANN method to fulfill the load demand. Matlab Simulink was employed to develop and simulate the ANN on the system. From results of simulation it can be concluded that ANN can reach target accuracy level in around 80%. When the entire plant was interconnected, the ANN experienced a misreading due to the voltage drop in each generator that affected input of the ANN.
机译:可再生能源是一种有限的能源,涉及阳光,风和水。它通常用作可再生电厂的来源。尽管其优势,这些电厂也有助于一些缺点,例如高代成本,高度动态行为等。由于能量来源的不稳定性(RER),因此正在提高缺点。本研究旨在基于负载需求的基于操作控制系统的混合系统的电力管理设计。在本研究中,混合系统的电源管理使用了3个发电厂:光伏(PV),风电和微水力发电厂(MHPP),电池用作储存系统。工作的主要重点是使用ANN方法确定每种植物的激活,以满足负载需求。 Matlab Simulink被用来在系统上开发和模拟ANN。从模拟结果中可以得出结论,ANN可以在约80%左右达到目标精度水平。当整个工厂互连时,ANN由于每个发电机中的电压降,因此由于每个发电机的电压降而受到误读。

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