Climate Parameter Based Electric Power Requirement Forecasting by Fish Genetic Algorithm

Abstract

Electric power requirement of household and industries depends on geographical location as climate parameter directly increase or decrease the power requirements. Balancing of power in industries need some power forecasting. algorithm for which can learn pattern of load balancing and calculate the power requirement. This paper has resolved this issue of electric power requirement estimation for big infrastructure like Industries, company, plants, etc. Paper has proposed Fish Schooling Genetic algorithm for climate feature ratio estimation as per geographical location. Once feature ration for a geographical location was identified then power will be forecast. Experiment was done on real dataset of Industries in Ahmednagar Maharastra, India. Comparison of proposed model was done with existing algorithm and result shows that proposed model has improved various evaluation parameter values for different season of whole year.