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Charging optimization due to a fuzzy feedback controlled charging algorithm

机译:充电优化由于模糊反馈控制充电算法

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A part of the worldwide CO2 Emission can be reduced by changing the mobility to electric vehicles and charge them with renewable energy. Renewable energy sources are often decentralized and local and can be a part of smart buildings. To maximize the efficiency a self-consumption of this energy is desirable. The main focus of this paper is to find a controlling algorithm for charging stations, which balance the renewable feed in and the charging power under respecting the EV-user habits. A fuzzy-based control algorithm shows good results in a simulation. To evaluate the fuzzy algorithm for controlling charging algorithm it is implemented on a charging algorithm development environment. After a measurement of an uncontrolled (UC) and a controlled (CC) charging cycle, a changed charging curve is evaluated. The founded data show also positive impact of the charging controller to the power grid.
机译:通过将移动性改变为电动车辆,可以减少全球二氧化碳排放的一部分,并用可再生能源充电。 可再生能源往往是分散的和本地的,并且可以成为智能建筑的一部分。 为了最大限度地提高这种能量的效率是可取的。 本文的主要焦点是寻找用于充电站的控制算法,其平衡了EV-USE习惯下的可再生饲料和充电功率。 基于模糊的控制算法在模拟中显示出良好的结果。 为了评估控制充电算法的模糊算法,它在充电算法开发环境中实现。 在测量不受控制的(UC)和受控(CC)充电循环之后,评估改变的充电曲线。 建立的数据显示了充电控制器对电网的正面影响。

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