Research on Regional Flexible Load Low Carbon Dispatching Based on Cloud Model

With the widespread deployment of renewable energy generation devices and the continuous access of demand side resources in the new microgrid system, power system operations are gradually moving away from the traditional top-down hierarchy. The uncertainty it brings to the system is becoming increasingly unconditional, making it difficult for optimal power system dispatching to operate effectively. Based on the above problems, this paper proposes a novel dispatching scheme to achieve the optimal operation of the system using an iterative coordination method of the supply demand interaction. On the supply side, the peak-flat-valley time division rules are proposed to develop a dynamic electricity price based on fuzzy C-means clustering. Furthermore, the system carbon and economic costs are integrated and modeled as minimization objectives. On the demand side, the power consumption behavior of flexible loads is evaluated considering demand response uncertainty based on the cloud model theory. Case studies demonstrate the validity of proposed model and adopted method including reducing the peak-to-valley difference and CO2 emission. Moreover, cloud model has a significant effect in dealing with the uncertainty of load demand response.