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首页> 外文期刊>International Journal of Electrical Power & Energy Systems >Long term distribution demand forecasting using neuro fuzzy computations
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Long term distribution demand forecasting using neuro fuzzy computations

机译：使用神经模糊计算的长期配电需求预测

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This article describes the application and validation of forecasting results of a hybrid fuzzy neural technique which combines neural network and fuzzy logic modelling for long term land use based distribution load forecasting. The strength of this technique lies in its ability to reduce appreciable computational time and its comparable accuracy with other modelling techniques. The use of fuzzy logic effectively handles the load distribution in a small area with future demand of consumer class. The fuzzy neural network was extensively tested on actual data obtained from a small power distribution system. Impressive results with a low error was obtained for the global model and load model. Radial Basis function Network (RBFN) was used for both global and load modelling and this approach avoids complex mathematical calculations and is simple to implement on a personal computer. The heuristic approach used for spatical modelling is replaced by fuzzy system.
机译：本文介绍了结合神经网络和模糊逻辑模型的混合模糊神经技术在基于土地利用的长期负荷预测中的应用和验证。该技术的优势在于它可以减少可观的计算时间，并具有与其他建模技术相当的准确性。模糊逻辑的使用有效地处理了小范围的负荷分配，满足了未来消费者的需求。在从小型配电系统获得的实际数据上对模糊神经网络进行了广泛的测试。对于全局模型和负载模型，获得了令人印象深刻的结果，且误差很低。径向基函数网络（RBFN）用于全局和负载建模，这种方法避免了复杂的数学计算，并且很容易在个人计算机上实现。用于空间建模的启发式方法已被模糊系统取代。

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