ANN based electric load forecasting applied to real time data
ANN based electric load forecasting applied to real time data
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基于 ANN 的电力负荷预测应用于实时数据
DOI：
10.1109/indicon.2015.7443392
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Priti
中科院分区：
文献类型：
--
作者：
S. Khatoon;Ibraheem;A. Singh;Priti
电力负荷预测的准确性直接影响到电力系统的整体性能。有时由于负荷模式复杂，预测变得困难。本研究的目的是开发更有效的预测模型等。本文比较了基于人工神经网络技术的电力负荷预测精度。本研究探讨了用于电力负荷预测的时间序列技术，如MA、线性趋势、指数和抛物线趋势。本文以小时电力负荷数据为基础，建立了基于人工神经网络的时间序列预测模型。用于预测的数据是从位于北方邦诺伊达的一家分销公司获得的。对这些基于人工神经网络技术的预测误差进行了评估。
The accuracy of electric load forecasts significantly affects the overall performance of power system. Some time due to complicated load pattern, forecasting becomes difficult. The object of this study is to develop more effective forecasting models, among others. This paper compares the electric load forecasting accuracy of ANN based techniques. This study investigates the time series techniques used to forecasts electric load, e.g. MA, linear trend, the exponential and parabolic trend. In the present study ANN based time series forecasting model has been developed, on hourly electric load consumption data. Data used to forecast is acquired from a distribution company located in Noida, Uttar Pradesh. These ANN based techniques are evaluated for the forecasting errors.