Estimation of Electricity demand structural model in the agricultural sector using Underlying Trend concept and Kalman filter algorithm

In recent years demand for electricity in Iranian agricultural sector has been increased. Therefore accuratemodeling of the electricity demand in order to adoptionenergy saving policies and predictionof future consumption as well as to provide timely and cost-effectiveness، is important. In this paper using underlying trend concept and creating a state - space model and kalman filter algorithms، the structural model of electricity demand in agricultural sector was estimated. The data used in this study are annuallytime series in period 1353-1389. The results of the process as smooth and being upside is underlying trend. According tolikelihood ratio statistic، most appropriate structure for hyper parameters، were random state level and fixed slopetrend. Income and price elasticity of electricity demand in the short-run and long-run was less than unity. Therefor،price policies are not efficient enough to reduce electricity consumption and it is suggested Change from flood irrigation to drip and sprinkler. Besides electricity consumptionpredictiojn showed an increasing trend in electricity demand. Based on this paper results policy makers should adopt effective nonpricepolicies to reduce electricity consumtion in agri sector and also should pay attention to electricity supply in this sector.