Energy Optimization Scheduling Problem At The Airport

Strengthening energy management is one of the important means of energy-saving and emission-reduction adopted by airport energy policymakers in recent years.In this context,airport energy forecasting and scheduling research work are carried out,and experimental results have illustrated the effectiveness of the algorithm in airport energy management.First,correlation analysis and multiple regression analysis of the key factors of energy consumption are conducted,such as passenger and cargo traffic,climatic conditions and energy prices,so that the impact of various factors on energy consumption are obtained,establishing the forecasting model of airport energy consumption.Taking the Tianjin airport power energy demand as an example,simulation and analysis are completed.Experimental results show that the accuracy of the gray neural network prediction model obtained through the improved drosophila optimization algorithm is 1.18% higher than that of the model without considering the main influencing factors.Second,the mathematical description of the energy optimization problem in the airport area is accomplished and the scheduling problem is transformed into the optimization problem.Moreover,the operation constraint condition of each energy consuming equipment and energy storage equipment is established.Taking the typical energy consumption of the airport area as an example,an airport energy scheduling model based on multi-objective optimization and a scheduling model based on energy consumption prediction are set up,respectively,so that the simulation of typical energy load,cooling load and warm load are completed.Finally,the scheduling scheme based on unit model and prediction model are evaluated along with the unscheduled scheme,and the integrated evaluation result will be adopted as the judgment principle of optimal scheduling scheme.The fuzzy hierarchical comprehensive analysis method is used to evaluate the two scheduling schemes and the unscheduled scheme,and the evaluation results are analyzed.