Renewable energy utilizing and fluctuation stabilizing using optimal dynamic grid connection factor strategy and artificial intelligence-based solution method

As a crucial aspect of pollution emissions, the transformation and upgrading of the power industry urgently require attention. Utilizing renewable energy generation techniques is an effective means to promote energy conservation and emission reduction within the power industry. However, the utilization rates of renewable energy generation are hindered by significant randomness and uncertainty associated with renewable energy power. In light of these challenges, this study constructed a hybrid economic emission dispatch (HDEED) model to explore the establishment of effective regulation mechanism under renewable energy grid connection. First, taking into account dynamic constraints, the wind-solar-thermal-storage HDEED model was constructed with operation costs and pollution emissions as objective functions. Second, an optimal dynamic grid connection factor strategy and the GWOH-based solution method were proposed. Finally, the proposed strategy and algorithm were verified using an improved IEEE-39 bus test system. The results revealed that under the same test conditions, the Pareto optimal frontiers obtained by the GWOH algorithm demonstrated the most competitive performance. Furthermore, the system cost achieved by GWOH was 4.52% lower than that without renewable energy access, while emissions were reduced by 11.84% under the optimal dynamic factor grid connection strategy. This study significantly contributes to the improvement of energy management efficiency and the enhancement of renewable energy utilization rates in the power industry.