As a large improving country, my country has serious problems in energy utilization. Vigorously promoting energy conservation and emission reduction is an undisputed choice for my country and even the world. Energy data storage based on data warehouse can effectively assist energy consumption supervision departments to monitor changes in local energy consumption and predict energy consumption trends. The purpose of this paper is to store energy data based on improved particle swarm algorithm. This paper studies the concept and origin of particle swarm optimization, analyzes the cloud storage system and its characteristics, and the relationship between energy big data and cloud storage. In the experiment, the basic particle swarm algorithm is used to investigate and analyze the three modules of energy cost management, index analysis and energy prediction and performance realization.

Guobin Si. Energy Data Storage Based on Improved Particle Swarm Algorithm. Academic Journal of Energy (2020), Vol. 1, Issue 3: 25-33. https://doi.org/10.38007/RE.2020.010304.

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