Forecasting Energy Demand of India Using Integrated Grey Wolf Optimizer

Abstract

In this paper we provide a new methodology for estimating the future primary energy demands of India. Firstly, we propose a new algorithm known as Integrated Grey wolf Optimizer. This new algorithm is an improvement over Grey wolf optimizer to deal with multimodal functions. Economic factors such as GDP (Gross Domestic Product), Population, Coal production and Petroleum production are used as mathematical parameters for our objective function. The coefficients of this two-form model (i.e., Linear and Quadratic) are optimized using the new Integrated Grey wolf optimizer. The highlight of this extract is the new Integrated version of grey wolf optimizer, which improves the exploration capability of the algorithm to deal with local minima stagnation. The results of this modified version are better than traditional Grey wolf optimizer and provides better accuracy and less errors. The last 14 years of historical information of India are used as datasets for the respective parameters. Coefficients obtained after the optimization are used for forecasting in three different cases which are Rapid (7.5% rise in GDP), Moderate (6.5%) and (5.5%) Slow growth of country.