Modeling and Forecasting Short-Term Electricity Demand for Libyan Electric Network
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Abstract
Electrical load forecasting is a method of guessing the future of the electricity demand. Load forecast is an essential factor for power system planners and demand controllers. This is to ensure that would be an adequate amount of the electricity meeting the increasing demands. Therefore, an accurate load forecasting model can effectively lead to reduction of power system cost, better budget planning, and maintenance scheduling. The future load on a power system is predicted by extrapolating a predetermined relationship between the load and its influential variables. Determination of this relationship involves modeling and estimation the coefficient of the model through the use of an efficient parameter estimation technique. This paper presents a short term forecasting model for Libyan electric network using multi parameter regression method. The proposed method shows a result with small deviation between the actual and expected load, which means Multi parameter regression emerged as a suitable model for forecasting electricity demand in Libya.
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National Control Center of the General Electricity Company Of Libya (GECOL), Libya, Tripoli
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