{"title":"Mechanism and Influencing Factor Analysis of High Frequency Oscillation in PMSG-Based Wind Farm With Grid-Connected System","authors":"Chao Luo, Yihua Zhu, Libin Huang, Jiawei Yu","doi":"10.1109/ICEI57064.2022.00020","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00020","url":null,"abstract":"Under the background of vigorously developing wind power, permanent magnet synchronous generator (PMSG)-based wind turbines have been widely used in offshore wind farms. However, the high frequency oscillations (HFOs) of PMSG-based wind farms with grid-connected system have occurred frequently in recent years, which have a bad impact on the safe and stable operation of the power system. And current researches only preliminarily reveal the mechanism, which are lacking in discussion on the key factors involved in HFOs. This paper establishes the high frequency impedance model of PMSG-based wind farm with grid-connected system. To identify the key factors involved in HFO, the impedance sensitivity method is used to obtain the quantitative relationship of the influence of each parameter on HFO. It can be concluded that the control delay, LCL filter parameters, collector lines parameters have the greatest influence on the HFO of the wind farm, but the characteristic of negative resistance caused by control delay is the root cause of HFO. Finally, this paper establishes the model of PMSG-based wind farm with grid-connected system on the PSCAD/EMTDC and verifies the correctness of the theoretical analysis. The conclusions of this paper can provide a reference basis for the mitigation strategies of HFOs.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131285901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Distributionally Robust Decision-Dependent Generation and Transmission Expansion Planning for 100% Renewable Energy Utilization","authors":"Yangqing Dan, L. Qiu, Yalong Li","doi":"10.1109/ICEI57064.2022.00036","DOIUrl":"https://doi.org/10.1109/ICEI57064.2022.00036","url":null,"abstract":"Renewable energy is the fundamental approach to reducing the carbon emission of power systems. To fully utilize renewable energy sources in the planning stage, a co-optimization of generation and transmission expansion planning (G&TEP) strategy is proposed, where the system security is guaranteed under uncertainties. To address the long-term uncertainties of loads, renewable energy output, and component failures across the planning horizon, a novel decision-dependent ambiguity set is proposed using total variation distance, where the renewable energy output and component failures are affected by planning. A multi-year G&TEP problem is formulated as a two-stage distributionally robust optimization problem with decision-dependent ambiguity sets, where the renewable energy, energy storage systems (ESSs), and transmission lines are jointly optimized. Using Lagrange duality, this problem is further reformulated as a mixed-integer linear programming problem, which can be solved by the off-the-shelf solvers. The simulations are performed on a modified Garver 6 test system. The effectiveness of the proposed strategy is verified by the numerical results.","PeriodicalId":174749,"journal":{"name":"2022 IEEE International Conference on Energy Internet (ICEI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132355031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}