Reliability evaluation of generation system with micro-grid based on glowworm swarm optimization

Because of emissions of carbon dioxide from consumption of fossil fuels and consideration of the security of energy supply, renewable energy sources such as wind power generation and solar power generation have increased significantly in recent years and are expected to play more important role in electric power system in the near future. However, their drawbacks such as intermittence and unpredictable variability are likely to result in negative effects on the reliability of the power system. This study proposed a hybrid power generation system (HPGS) composed of wind power generation and solar power generation systems and established its model based on Monte Carlo sampling. In order to demonstrate the reliability promotion resulted from the HPGS, with introduction of Glowworm Swarm Optimization (GSO) algorithm, indices including loss of load expectation, loss of energy expectation, and loss of load probability of the micro grid are evaluated. Simulation results based on proposed method indicated that the proposed HPGS can effectively improve the adequacy of the micro grid. Compared with the results that generated by sequential Monte Carlo, the GSO algorithm outperforms with less computation time and higher convergence accuracy.