Gujing Lin, Ciwei Gao, Meng Song, Chaoliang Wang, L. Li, Wei Liu
{"title":"Multi-objective Cooperative Optimal Control Strategy for Virtual Power Plant with Information and Communication Infrastructure","authors":"Gujing Lin, Ciwei Gao, Meng Song, Chaoliang Wang, L. Li, Wei Liu","doi":"10.1109/ICPET55165.2022.9918197","DOIUrl":null,"url":null,"abstract":"Under the two-carbon target, the large-scale access of renewable energy brings great challenges to the peak modulation, frequency modulation and fault recovery of the system. With the rapid development of information and communication technology, a large number of adjustable loads based on information and communication infrastructure, including communication base station backup energy storage (BSES) and internet data center (IDC), broaden the path of the power system to achieve the balance of power supply and demand, and can solve the prominent problems brought by renewable energy power generation. First, in order to make full use of BSESs and IDCs to consume the renewable energy, this paper studies the adjustable potential of BSESs and IDCs under different load levels, and constructs the BSESs and IDCs encapsulation model. Secondly, the virtual power plant (VPP) is considered as an effective way of distributed resource aggregation, so on the basis of ensuring the backup demand of BSESs and the normal operation of IDCs, this paper designs a multi-objective collaborative optimization control strategy of VPP to achieve the maximum consumption of renewable energy and the optimal operation economy of VPPs. Finally, the case study verifies the low carbon and operation economy under the contrast of single objective and multi-objective scenarios.","PeriodicalId":355634,"journal":{"name":"2022 4th International Conference on Power and Energy Technology (ICPET)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Power and Energy Technology (ICPET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPET55165.2022.9918197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Under the two-carbon target, the large-scale access of renewable energy brings great challenges to the peak modulation, frequency modulation and fault recovery of the system. With the rapid development of information and communication technology, a large number of adjustable loads based on information and communication infrastructure, including communication base station backup energy storage (BSES) and internet data center (IDC), broaden the path of the power system to achieve the balance of power supply and demand, and can solve the prominent problems brought by renewable energy power generation. First, in order to make full use of BSESs and IDCs to consume the renewable energy, this paper studies the adjustable potential of BSESs and IDCs under different load levels, and constructs the BSESs and IDCs encapsulation model. Secondly, the virtual power plant (VPP) is considered as an effective way of distributed resource aggregation, so on the basis of ensuring the backup demand of BSESs and the normal operation of IDCs, this paper designs a multi-objective collaborative optimization control strategy of VPP to achieve the maximum consumption of renewable energy and the optimal operation economy of VPPs. Finally, the case study verifies the low carbon and operation economy under the contrast of single objective and multi-objective scenarios.