In this study,a novel energy-efficient single-phase induction motor with three stator windings is proposed as shown in Fig 1.The winding A constitutes the first branch.The series connection of the capacitor C and the ...In this study,a novel energy-efficient single-phase induction motor with three stator windings is proposed as shown in Fig 1.The winding A constitutes the first branch.The series connection of the capacitor C and the winding B constitute the second branch,and the series connection of the capacitor C2 and the winding C constitute the third one.The above three branches are connected in parallel as shown in Fig.2.展开更多
Photovoltaic(PV)generation always exhibits strong uncertainty and variability;therefore,its excessive integration brings huge risks to the safe operation of power systems.In this letter,a two-stage robust optimization...Photovoltaic(PV)generation always exhibits strong uncertainty and variability;therefore,its excessive integration brings huge risks to the safe operation of power systems.In this letter,a two-stage robust optimization approach based on decision-dependent uncertainty is devised to identify the Pv hosting capacity that can be accepted to ensure the effective consumption of PV generation under uncertainty.The proposed approach is validated by numerical experiments for a microgrid and a distribution network.展开更多
文摘In this study,a novel energy-efficient single-phase induction motor with three stator windings is proposed as shown in Fig 1.The winding A constitutes the first branch.The series connection of the capacitor C and the winding B constitute the second branch,and the series connection of the capacitor C2 and the winding C constitute the third one.The above three branches are connected in parallel as shown in Fig.2.
基金This work was supported by the National Research Foundation Singapore,Intra-CREATE REQ0393291(No.NRF2022-ITS010-0005)the National Research Foundation Singapore,Energy Market Authority under its Energy Programme(EP Award EMA-EP004-EKJGC-0003).
文摘Photovoltaic(PV)generation always exhibits strong uncertainty and variability;therefore,its excessive integration brings huge risks to the safe operation of power systems.In this letter,a two-stage robust optimization approach based on decision-dependent uncertainty is devised to identify the Pv hosting capacity that can be accepted to ensure the effective consumption of PV generation under uncertainty.The proposed approach is validated by numerical experiments for a microgrid and a distribution network.
