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Effects of Connecting a Micro-Hydro Turbine to an Existing Power System Grid

机译:将微型水力涡轮机连接到现有电力系统网格的影响

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As the world's supply of fossil fuels is now becoming scarce and depleting, an alternative means of energy production should be explored further. In this case, alternative sources of energy will play a vital role in future energy production. There are many kinds of alternative energy sources of which we are particularly interested on clean energy sources such as wind, solar and micro-hydro generation. This paper deals on the utilization of water for electricity production wherein it aims to determine the amount of water that can be impounded in a dam from a stream or river. The forecasting of water is done with the aid of an Artificial Neural Network (ANN). ANN is a versatile tool that predicts a certain output given previous inputs. The Radial Basis Function Network (RBFN) is used to predict the level of water in the dam. With the forecasted result from ANN, a schedule of power generation from a micro-hydro turbine (MHT) is done. An MHT is a machine which can generate power of up to 100 kW. The effect of connecting an MHT to an existing power system grid is also investigated.
机译:随着世界性化石燃料的供应现已变得稀缺和消耗,应进一步探索替代能源生产手段。在这种情况下,替代能源来源将在未来的能源生产中发挥重要作用。有许多各种各样的能源,我们特别感兴趣的清洁能源,如风,太阳能和微水流等。本文涉及用于电力生产的水,其目的是确定可以在溪流或河流中扣押的水量。借助于人工神经网络(ANN)来完成水的预测。 ANN是一个多功能工具,可预测先前输入给定的某个输出。径向基函数网络(RBFN)用于预测大坝中的水平。随着ANN的预测结果,完成了微水涡轮机(MHT)的发电时间表。 MHT是一种机器,可以产生高达100 kW的功率。还研究了将MHT连接到现有电力系统网格的效果。

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