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Long Term Annual Electricity Demand Forecasting in Sri Lanka by Artificial Neural Networks

机译:基于人工神经网络的斯里兰卡长期年电力需求预测。

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Electricity has become a major form of end use energy in present complex society. The influence of electricity is tremendous and has been recognized as a basic human need. It is an important element of infrastructure on which the socio economic development of the country heavily depends. Electricity demand forecasting is very important and crucial for a utility, in order to make right decisions regarding future power plant and network development. Accurate electricity demand forecasting is one of the challenges and several techniques are used in forecasting demand based on the availability of data in each country. Electricity utility of Sri Lanka in their long term generation expansion planning studies use three long term demand forecasting methodologies namely econometric approach, time trend approach and end user approach. New application for long term demand forecasting based on Artificial Intelligence has identified as important due to its ability in mapping complex non-linear relationships. Therefore under this study, the use AI method based on Artificial Neural Networks for long term annual electricity demand forecasting in Sri Lanka is discussed and modeled including Socio-Economic Indicators and Climatic Conditions.
机译:电力已成为当前复杂社会中的最终使用能源的主要形式。电力的影响是巨大的,已被认为是基本的人类需求。这是该国社会经济发展大量取决于的基础设施的重要因素。电力需求预测对效用非常重要,至关重要,以便做出关于未来电厂和网络发展的正确决策。准确的电气需求预测是基于每个国家数据的数据的可用性预测需求的挑战之一。斯里兰卡的电力效用在他们长期一代扩张规划研究中使用三个长期需求预测方法,即计量计量的方法,时间趋势方法和最终用户方法。基于人工智能的长期需求预测新申请已被确定为绘制复杂非线性关系的能力。因此,在这项研究下,讨论了基于人工神经网络的使用AI方法,为斯里兰卡的长期年电力需求预测,并建模,包括社会经济指标和气候条件。

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