Model of Regional Renewable Energy Acceptance Capacity Based on Artificial Bee Colony Algorithm

In recent years, the development of global economy is facing the dual constraints of resources and the environment. It has become a global consensus to reduce the amount of fossil fuel power consumption and promote the development of renewable energy. At the same time, renewable energy is rapidly developing, which is gradually meeting more and more energy needs. Electricity is one of the most important ways to make largescale use of renewable energy. However, because of the intermittent and volatility of renewable energy, regardless of the high proportion of wind power or solar power generation, it will be sure to cause an impact on the operation of the power system. In this paper, a global renewable energy acceptance capacity prediction model has been proposed. And the empirically studies were analyzed to provide a basis for global energy conservation and emission reduction. In this paper, the development of power in typical regions of the world was summarized, and artificial bee colony algorithm integrated with production simulation was introduced to build a renewable energy acceptance capacity model based on the principle of maximizing the acceptance of renewable energy while maintaining stable operation of the grid. The ability to accept regional renewable energy generation in 2030 was also assessed.