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An Efficient Regression Based Demand Forecasting Model including temperature with Fuzzy Ideology for Assam

Rashmi Rekha Borgohain, Barnali Goswami

Forecasting of load demand is a very fundamental task and is mandatory in operational planning of power system .At present in the prevailing deregulated scenario load forecasting has become immensely important. Here, in this paper a suitable time series based Auto-Regressive (AR) model of order two has been proposed wherein the influence of temperature has also been included for the purpose of meticulous forecasting. This paper suggests a simple algorithm to forecast short- term load for Assam using the regression based time series method with temperature and then using fuzzy ideology an effort has been made to minimize the error between actual load and predicted load.

Отказ от ответственности: Этот реферат был переведен с помощью инструментов искусственного интеллекта и еще не прошел проверку или верификацию

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Космос ЕСЛИ
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Университет Хамдарда
научный руководитель
Импакт-фактор Международного инновационного журнала (IIJIF)
Международный институт организованных исследований (I2OR)
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