Monthly Electricity Generatıon Forecast in Solar Power Plants with LSTM
نویسندگان
چکیده
Today, with the intensive use of electrical devices, need for electricity has increased. Fossil fuels are generally used to meet this need. However, considering damage caused by fossil environment, governments make various incentives renewable energy sources. The countries solar power plants quite large. Recently, there many investors who want build plants. sunshine duration our country is high. And fact that climatic conditions efficient generation attracts investors. installation these costly. It possible predict amortization periods costs ever-developing artificial intelligence technology. In study, data be produced in future estimated using real plant machine learning algorithms. Data, take from owned Humartaş Energy company. predictions and analyses were made LSTM (Long Short-Term Memory) method, which one neural networks. error rate study between 1% 15%. foreseen studies will also implemented other sources such as wind, geothermal, hydraulic coming stages.
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ژورنال
عنوان ژورنال: Düzce Üniversitesi bilim ve teknoloji dergisi
سال: 2021
ISSN: ['2148-2446']
DOI: https://doi.org/10.29130/dubited.1015251