Scientific Khyber ISSN:1017-3471 (2014)Volume 4(1):PP 48-60 Comparison of Stochastic Modelling With Artificial Intelligence Based Approach to Forecast the Electrical Load

Accurate load forecasting is very important for electric utilities in planning for new plants. Also it is very significant for the routine of maintaining, scheduling daily, electrical generation, and loads. In this study, emphasis was considered on short-term load forecasting which is important for real time operation and control of power systems. Artificial intelligence and stochastic forecasting models were examined. The performance of these models is dependent on the characteristics of electric loads and is based on the assumption that electric load patterns are basically invariant with time. Two different models were considered and a new stochastic model (called REGARIMA) was introduced and compared with ANFIS model. Both models were tested and shown to be the best one that represents the available data. The results obtained using the two approaches are very accurate and mutually competitive. Furthermore, they are very promising in short term forecasting techniques, which could be applied as well on wind speed forecasting.

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