Research On Optimal Allocation Of Energy Storage Capacity In Zero-carbon Big Data Industrial Parks With Multi-source Collaboration

The Big Data Industrial Park has gathered a large number of industrial enterprises,and in order to meet their electricity demand,it is necessary to continuously supply power and maintain a good level of power supply quality.If traditional energy is used for power supply,it will generate a large amount of carbon emissions,bringing enormous pressure to the environment and climate.North Hebei Province is rich in wind and light resources,and the establishment of a complementary system for clean energy power generation such as wind and light can reduce carbon emissions from the source.However,wind and light have intermittent and unstable characteristics,making it difficult to meet the demand of the load side at all times.Energy storage plays an important role in suppressing fluctuations,peak shaving,and valley filling.Therefore,reasonable and economical allocation of energy storage capacity in big data industrial parks is a key issue.Based on this,the research content of this article is as follows:This paper first studied the factors of carbon emissions in the park,calculated carbon emissions based on the carbon emission source selection inventory analysis method,and then sought a zero-carbon path for big data industrial parks;Secondly,the characteristics of the source,network,load,and storage of the zero carbon big data park were analyzed,and wind power generation models and photovoltaic power generation models were constructed.The problems of multiple power supply forms,multiple industrial user loads,and interaction with the power grid were comprehensively considered.Back Propagation neural networks were also used to predict load requirements;In addition,based on the goal of zero carbon,a configuration model for energy storage capacity with the goal of minimizing cost is constructed.Considering the charging and discharging states of energy storage batteries and the interaction with the power grid,a method for optimizing the configuration of energy storage capacity in a zero carbon big data park with multiple sources,grid,load,and storage coordination is proposed.Finally,taking the Zhengfei Miata Big Data Industrial Park as an example,using MATLAB to conduct simulation analysis and comparative analysis,it is concluded that when multiple sources,networks,loads,and storage are coordinated,only234.88 MWh of energy storage power station capacity and 53.97 MW of power need to be configured.While meeting the power demand on the load side of the Big Data Industrial Park,the most economical configuration of energy storage capacity can be obtained.The optimization scheme proposed in this paper is superior to traditional energy storage capacity allocation methods in terms of energy storage capacity and power,and provides a reference for the energy storage capacity allocation of the zero carbon big data industrial park’s source network load storage collaboration.