Model of Global Renewable Energy Acceptance Demand Based on MAGICC Integrated with Artificial Bee Colony Algorithm

Abstract

Currently resource constraints, environmental pollution, and climate change has become hard constraints on energy development. The transformation of energy is of critical importance. The fundamental approach is to achieve clean alternatives on the energy supply side and energy alternatives on the energy consumption side. However, the demand of renewable energy acceptance has not been analyzed and confirmed. In this paper, the global renewable energy demand model has been built and simulated based on the artificial bee colony optimization algorithm in order to analyze the demand of renewable energy acceptance, integrated with the Model for the assessment of greenhouse gas induced climate change, which is also called the MAGICC. The calculation performs the optimization of the object function, which takes the generation performance standard and human development index into consideration, with the proportion of installed capacity of different generator units in Asia, Europe, Africa, North America, South America and Oceania as the variable quantity. As the result of the simulation, the empirical analysis of global demand acceptance of the year 2030 and 2050 were carried out, which shows the green electricity demand acceptance demonstrated by the installed capacity in six continents.