Sensors (Basel, Switzerland)
With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control module and a lower-level optimal control module. The purpose of the two-layer optimization modules is to optimize the cost of the power distribution of microgrids. The function of the upper-level optimal control module is to set decision variables for the lower-level module, while the function of the lower-level module is to find the optimal solution by mathematical methods on the basis of the upper-level and then feed back the optimal solution to the upper-layer. The upper-level and lower-level modules affect system decisions together. Finally, the feasibility of the bilevel optimization model is demonstrated by experiments.
cost, edge computing, microgrid, optimization, power distribution
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Applied Data Science
Yi Chen, Kadhim Hayawi, Meikai Fan, Shih Yu Chang, Jie Tang, Ling Yang, Rui Zhao, Zhongqi Mao, and Hong Wen. "A Bilevel Optimization Model Based on Edge Computing for Microgrid" Sensors (Basel, Switzerland) (2022). https://doi.org/10.3390/s22207710