Research on Application of Digital Twin Technology in Optimal Control of Distributed New Energy System

With the transformation of global energy structure and the increasing demand for sustainable development, distributed new energy system (DNES) has attracted much attention because of its flexibility, high efficiency and environmental protection. However, the complexity of the system and changeable environmental conditions bring great challenges to its optimal control. In order to meet these challenges, this paper introduces the digital twin (DT) technology, which aims to monitor and predict the running state of the system in real time by constructing an accurate digital model of the system, and then put forward an optimal control strategy. Firstly, a multi-dimensional, multi-spatial and multi-scale DT model is constructed, which integrates time dimension, space dimension and energy dimension, and can fully reflect the dynamic change and energy flow of DNES. The model covers the start/stop time of equipment, the distance between equipment, energy generation, energy consumption and energy storage, etc., and is modeled from micro, meso and macro scales to ensure the accuracy and comprehensiveness of the model. In order to realize the real-time performance of DT model, this paper designs an efficient data acquisition and transmission system based on advanced sensors and 5G communication technology, which ensures the real-time performance and accuracy of all data in the system. On this basis, the DT model can monitor the running state of the system in real time, and find and diagnose the problems in the system in time through synchronous comparison with the actual data. Through the simulation analysis of DT model and the formulation of optimal control strategy, this paper puts forward an optimal control scheme for DNES. Taking the distributed wind power generation system as an example, the research shows that the power generation efficiency of the system can be significantly improved and energy consumption can be reduced by adjusting the control strategies such as fan speed and blade angle. After optimization, the energy consumption of the system is reduced by more than 20% in each month, which shows the remarkable effect of DT technology in improving the operation efficiency and stability of DNES.