来自风能-太阳能混合热电厂的电能

Hassan Aliyu, J. Agee
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引用次数: 9

摘要

本文提出了大型风力发电厂和太阳能热电厂的电力预测与调度。风电场中的涡轮机应按类型、功率输出和地理位置进行分组。采用神经网络方法对每组和整个风电场的输出功率进行预测。每组的输出通过电加热系统连接到太阳能热电厂(CSP)系统。在该模型中,风力发电厂将具有灵活性和可重构性,以满足联合供暖系统的特定能源需求。风力电加热系统应与太阳能热加热系统一起运行,以补充风力不足的时期。该模型将缓解由于风能供应的可变性和间歇性而导致的电网电力稳定性问题。
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Electric energy from the hybrid wind-solar thermal power plants
In this paper prediction and dispatch of electric energy from a large wind power plant and a solar thermal plant is proposed. The turbines in the wind power plant shall be grouped according to types, power output and geographic location. Neural Network methods shall be employed to predict the power output from each group and the entire wind farm. The output from each group is connected through an electric heating system to a solar thermal power plant (CSP) system. In this model the wind power plant would be flexible and reconfigurable to meet specific energy requirements of the combined heating system. The wind electric heating system shall operate alongside solar thermal heating system to compliment for periods when wind is insufficient. This model shall mitigate issues of power stability on the grid due to variability and intermittency of wind energy supply.
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