Modeling and optimization of collaborative computing in regional multi-energy systems for energy Internet

Abstract

Multi-energy systems (MES) exploit advanced physical information technology and innovative management pattern to achieve collaborative control of multiple heterogeneous energy. The refined control of MES bursts massive delay-sensitive computing tasks, requiring precise system modeling and collaborative computing strategies. However, the unbalanced spatial and temporal distribution of resources and real-time requirements of tasks further increase the difficulty of computing. To address these challenges, a precise modeling and optimization method of collaborative computing in MES is proposed. First, an integrated system framework for regional multi-energy systems (RMES) in northeastern China is designed. Then, the collaborative computing problem with energy and delay constraints in RMES is modeled. It is proved that the problem can be transformed into a joint convex and nonconvex optimization problem. Moreover, an improved simulated annealing-based joint resources optimization (ISA-JRO) scheme is proposed. Finally, extensive simulation results show that ISA-JRO significantly improves the computational resource utilization ratio and reduces the total cost in MES. ISA-JRO reduces at least 25 % of the total cost compared with the traditional methods.