Research on Optimization Strategy of Distributed Data Center and Energy Integration System

As a key infrastructure supporting the development of the digital economy, data centers have attracted attention due to their increasing energy consumption and operational costs. This article proposes a distributed data center and energy integration system that includes a data subsystem, an energy subsystem, and a data-energy integrated management and scheduling platform. It constructs an integrated operational dispatching model and proposes an optimization strategy based on data flow-energy flow collaborative scheduling. Taking the comprehensive energy cost including electricity cost and carbon trading cost as the optimization objective, a particle swarm optimization algorithm is used to find the optimal solution. Experimental results demonstrate that the operational optimization strategy proposed in this article can effectively reduce the overall energy consumption and operational costs of the system while ensuring system reliability.