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The proposed work aimed to forecasting the load by using Artificial Neural Networks (ANN). Short term load forecasting plays an important role for the planning, economic and reliable operation of power systems. Therefore, many statistical methods have been conventionally used for such forecasting, but it has been difficult to construct a proper functional model. This difficulty can be reduced by using...
The conventional Generation Scheduling (GS) is a day ahead activity, aiming at minimizing operating cost subject to system as well as device constraints. The anticipated load, generation and network availability are inputs to GS problem. The new attribute added to conventional GS problem is frequency. Under Availability Based Tariff (ABT), frequency plays important role in deciding the real time generation...
A new hybrid technique using support vector machines (SVM) to forecast the next `24' hours load is proposed in this paper. Four modules consisting of the basic SVM, peak and valley SVM, averager and forecaster and adaptive combiner form the integrated method for load forecasting. The proposed architecture can forecast the next `24' hours load. The basic SVM uses the historical data of load and temperature...
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