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Long-term electric load forecast in Kuwaiti and Egyptian power systems

机译:科威特和埃及电力系统的长期电力负荷预测

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This paper presents an efficient methodology for forecasting annual peak demands in electrical power systems. The proposed approach is developed as an accurate alternative forecasting method to other existing methods. The method is based on cuckoo search algorithm. It is used to minimize the error associated with the estimated model parameters in order for the forecasted demands to follow the real load data. Real data from Kuwaiti and Egyptian networks are used to perform this study. Three long-term forecasting models have been used in this research work to measure the robustness of the developed estimation tool. Durbin-Watson statistical test is conducted to validate selected models’ adequacy, and model transformation is applied as a remedial measure to ill-conditioned time series data when needed. Forecasting outcomes are reported and compared to those obtained using other forecasting techniques. The performance of the proposed method is examined and evaluated. Results reveal that cuckoo search algorithm has is a promising potential as a viable tool for parameter estimation.
机译:本文提出了一种预测电力系统年度峰值需求的有效方法。提出的方法是作为其他现有方法的准确替代预测方法而开发的。该方法基于杜鹃搜索算法。它用于最小化与估计的模型参数相关的误差,以使预测的需求遵循实际负载数据。来自科威特和埃及网络的真实数据用于进行这项研究。在这项研究工作中,使用了三种长期预测模型来衡量已开发估计工具的鲁棒性。进行了Durbin-Watson统计测试以验证所选模型的充分性,并在需要时将模型转换作为对病态时间序列数据的补救措施。报告预测结果,并将其与使用其他预测技术获得的结果进行比较。对所提出方法的性能进行了检查和评估。结果表明,布谷鸟搜索算法作为一种可行的参数估计工具具有广阔的前景。

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