{"title":"A Carbon Emission Reduction Method for Distribution Network with Data Centers","authors":"Z. Cui, Jian Chen, Haoran Zhao","doi":"10.1109/ICCSIE55183.2023.10175280","DOIUrl":null,"url":null,"abstract":"With a large number of renewable energy connected to the grid, the inherent constraints of node voltage, line power flow upper limit and so on in the distribution network make it impossible for surplus renewable energy to be completely transmitted to the transmission network, resulting in a waste of renewable energy and increasing the overall carbon emissions of the system. In view of this phenomenon, this paper first models the distribution network and data center, embeds the economic optimization of the data centers into the carbon emission reduction optimization problem through KKT conditions. The data load distribution of the data center is guided by the electricity price information, and the data load is transferred in space, so that the renewable energy of the distribution network can be fully utilized and the total carbon emissions of multiple distribution networks can be reduced. Finally, an example is given to verify the effectiveness of the proposed method.","PeriodicalId":391372,"journal":{"name":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSIE55183.2023.10175280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With a large number of renewable energy connected to the grid, the inherent constraints of node voltage, line power flow upper limit and so on in the distribution network make it impossible for surplus renewable energy to be completely transmitted to the transmission network, resulting in a waste of renewable energy and increasing the overall carbon emissions of the system. In view of this phenomenon, this paper first models the distribution network and data center, embeds the economic optimization of the data centers into the carbon emission reduction optimization problem through KKT conditions. The data load distribution of the data center is guided by the electricity price information, and the data load is transferred in space, so that the renewable energy of the distribution network can be fully utilized and the total carbon emissions of multiple distribution networks can be reduced. Finally, an example is given to verify the effectiveness of the proposed method.