Design Method for Distributed Database Storage Architecture of Power Grid Based on Efficiency-Cost Optimization Model

Power grid dispatching operations have high performance requirements for distributed data storage architectures, yet existing design methods often rely on the engineering experience of technicians. The computer science field has accumulated significant theories and techniques in this area, such as using genetic algorithms to obtain optimal data allocation schemes, which can provide references for the design of data architectures. This paper comprehensively considers practical constraints such as storage costs, storage efficiency, and retrieval efficiency, proposing a distributed data storage architecture design method based on heterogeneous data organization optimization. For the unknown time functions, empirical data fitting is used for identification, and the Particle Swarm Optimization algorithm is employed to solve the mathematical model for data organization optimization. Finally, the proposed design method was validated in the design of an actual dispatching operations system. Test results indicate that the method can derive optimal data organization schemes while satisfying cost and efficiency constraints, providing a reference for performance evaluation and solution selection in power grid distributed data storage architectures.