Dynamic energy consumption modeling and multi-objective optimal scheduling technology of wind farm

Aiming at the dynamic change of energy consumption caused by intermittence, equipment degradation and environmental coupling in wind farm operation, a dynamic energy consumption modeling and multi-objective optimal scheduling method of wind farm based on "mechanism-data" integration is proposed. Firstly, a three-dimensional dynamic power curve model considering equipment health, environmental temperature and humidity and operating conditions is constructed, and a temperature-sensitive cable resistance model is introduced to realize the real-time estimation of line loss of current collector system, which significantly improves the prediction accuracy of net output. On this basis, a multi-objective optimization framework with economy, environmental protection and reliability as the core is established, and the improved NSGA-III algorithm is used to realize the rapid solution of Pareto frontier, and the agent model technology is introduced to meet the real-time demand of minute-level scheduling. Taking a 100 MW wind farm in northern China as an example, comparing the traditional static model with the proposed method, the results show that the prediction error of the dynamic model is reduced from 5.06% to 0.92%, and the multi-objective scheduling scheme achieves collaborative optimization among revenue, emission reduction and equipment balance, which verifies the effectiveness of the proposed method in improving the operation efficiency and sustainability of wind farms.