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Estimation of Hourly Solar Radiation on Horizontal Surface Using GAMF(Genetic Algorithm Modified Fuzzy)(Case Study in Surabaya)

机译:采用GAMF(遗传算法修饰模糊)水平表面对水平表面的每小时太阳辐射(泗水案例研究)

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The biggest renewable energy sources in Indonesia is solar energy.The installed capacity of Solar Power System in 2017 is still very far from the target.Solar radiation is very infulental on the photovoltaic performance in generating energy.The need for solar radiation estimation has become important in the design of photovoltaic system.Previous research has been done using Extreme Learning Machine(ELM)and Adaptive Neuro Fuzzy(ANFIS)methods.In this research,Genetic Algorithm Modified Fuzzy(GAMF)method used to estimate the solar radiation.Meteorogical dates used in this research are temperature,humidity,wind velocity and wind direction.There are 2 types of datas that are BMKG data and measurement data.Three experimental variations of input variation were performed for each data.For BMKG data the best estimation result is obtained when using humidity,temperature and wind velocity as variation inputs with RMSE and MAE of 145.19 and 72.While for the best result estimation result data obtained when applying humidity,temperature,wind speed and wind direction as variation inputs with values of RMSE and MAE were 1.44 and 0.65.
机译:印尼最大的可再生能源是太阳能energy.The在2017年安装的太阳能发电系统的容量仍然是来自target.Solar辐射很远,是在生成energy.The需要太阳辐射估计的光伏性能非常infulental已成为重要光伏system.Previous研究的设计一直采用极限学习机(ELM)和自适应模糊神经(ANFIS)methods.In这项研究,遗传算法改进的模糊(GAMF)方法来估计使用的太阳能radiation.Meteorogical完成日期在本研究是温度,湿度,风速和风向direction.There 2种类型的DATAS的是BMKG数据和测量用于获得最佳估计结果当每个data.For BMKG数据进行输入变化data.Three实验变化使用湿度,温度和风速与RMSE和145.19 MAE和72.While变动输入,用于最好的结果估计结果数据obtai奈德与RMSE和MAE的值施加湿度,温度,风速和风向的变化作为输入时,分别为1.44和0.65。

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