Research And Implementation Of Energy Consumption Optimization Method Based On New Energy-driven Storage System

With the rapid development of information technology and the advent of the Big Data era,the data centers that play an important role have witnessed a substantial increase both in number and in size.While accelerating the global informationization,the data center faces the problems of excessive energy consumption and high carbon emissions.In order to solve this problem,the introduction of economical and environmental friendly new energy has become one of the most important solutions.Solar energy and wind energy are currently the two most promising new energy sources.They are not only simple to obtain,but also exist in most parts of the world,and they are environmentally friendly and non-polluting.However,because of the intermittency,instability and mutation of new energy,data centers cannot effectively adapt to new energy sources.To this end,major data centers propose energy management strategies and load scheduling algorithms and other solutions,but most of the existing research results are for computational energy consumption optimization,cannot adapt to the storage aspect.Therefore,an energy consumption optimization scheme for the new energy-driven storage system is proposed.By using the characteristics of different storage media and onlineoffline load model,the write request is divided into two stages,online and offline.Moreover,the matching of load energy demand and new energy supply can be realized through the offline request scheduling.In order to adapt the storage system to the volatility of new energy sources,a new energy-friendly data distribution strategy and virtualization consolidation technology are proposed,and a dual-driven and fine-grained energy management strategy is adopted,that is,the number of active nodes is adjusted according to the supply of new energy and the intensity of the load to achieve the purpose of improving the energy efficiency of the system.In addition,an offline load optimization-scheduling algorithm is designed and implemented to improve the utilization of new energy.According to the optimization scheme of energy consumption,the prototype of storage system was implemented and the system performance,energy consumption and new energy utilization rate were tested and evaluated in detail.Experimental results show that optimizing the energy consumption scheme can make the utilization of new energy sources reach 95% while ensuring that the performance degradation rate of the storage system is less than 9.8%.