In renewable penetrated power systems, frequency instability arises due to the volatile nature of renewable energy sources (RES) and load disturbances. The traditional load frequency control (LFC) strategy from conven...In renewable penetrated power systems, frequency instability arises due to the volatile nature of renewable energy sources (RES) and load disturbances. The traditional load frequency control (LFC) strategy from conventional power sources (CPS) alone unable to control the frequency deviations caused by the aforementioned disturbances. Therefore, it is essential to modify the structure of LFC, to handle the disturbances caused by the RES and load. With regards to the above problem, this work proposes a novel coordinated LFC strategy with modified control signal to have Plug-in Hybrid Electric Vehicles (PHEVs) for frequency stability enhancement of the Japanese power system. Where, the coordinated control strategy is based on the PID controller, which is optimally tuned by the recently developed JAYA Algorithm (JA). Numerous simulations are performed with the proposed methodology and, the results have confirmed the effectiveness of a proposed approach over some recent and well-known techniques in literature. Furthermore, simulation results reveal that the proposed coordinated approach significantly minimizing the frequency deviations compared to the JAYA optimized LFC without PHEVs & with PHEVs but no coordination.展开更多
Plug-in hybrid electric vehicles(PHEVs) unite the advantages of the engine and electric motor which could provide great potential in saving energy. However, the fuel economy performance of the PHEVs is highly associat...Plug-in hybrid electric vehicles(PHEVs) unite the advantages of the engine and electric motor which could provide great potential in saving energy. However, the fuel economy performance of the PHEVs is highly associated with the driving condition, especially for parallel PHEVs because they could not decouple the engine work status from the driving condition. Meanwhile, fuel economy performance is not only a longitudinal issue but also related to lane selection. Lane selection is an important driving behavior and the algorithm of lane selection is necessary for the development progress of intelligent connected vehicles. Energy consumption cost is an important part of the vehicle’s using consumption cost. Therefore, lane selection strategies must consider this point.With the development of intelligent connected vehicle technology, such as V2X(Vehicle to Everything), the potential of energy consumption performance of intelligent connected PHEVs could be improved by taking environment information from V2X and smart sensors into lane selection. In this paper, a neural network(NN) based method is proposed to predict the future status of the local vehicle using the information from V2X, and then another network is used to estimate the future energy consumption of each lane. The lane selection is decided on energy consumption estimation. Lastly, the effectiveness of the method is validated by simulation using Matlab combined with SUMO(Simulation of Urban MObility).展开更多
Coronaviruses(CoVs)are a large family of human and animal pathogens that cause significant health and economic burdens worldwide.Thapsigargin(Tg)is a plant-derived sesquiterpene lactone with potent antiviral effects;h...Coronaviruses(CoVs)are a large family of human and animal pathogens that cause significant health and economic burdens worldwide.Thapsigargin(Tg)is a plant-derived sesquiterpene lactone with potent antiviral effects;however,the underlying mechanism remains unclear.Here,we show that Tg exhibited strong antiviral activity against the neurotropic swine CoV porcine hemagglutinating encephalomyelitis virus(PHEV)both in vivo and in vitro.Tg also exhibited inhibitory activity against other three swine coronaviruses in cell lines.Specifically,Tg treatment significantly inhibited the replication and transcription of genomic RNA in the viral life cycle but did not directly inactivate PHEV.Transcriptome analysis and glycolysis/mitochondrial stress testing confirmed that Tg alters intracellular metabolic flux,and suppresses glycolysis and oxidative phosphorylation(OXPHOS).Furthermore,metabolic reprogramming is associated with the antiviral effect of Tg and is required for productive PHEV infection.Overall,our findings highlight that Tg plays a crucial role in combating viral infections by targeting host energy metabolism shared by pathogenic microorganisms,suggesting that targeting key nodes of host metabolic processes may be a strategy for designing antiviral drugs against coronaviruses.展开更多
文摘In renewable penetrated power systems, frequency instability arises due to the volatile nature of renewable energy sources (RES) and load disturbances. The traditional load frequency control (LFC) strategy from conventional power sources (CPS) alone unable to control the frequency deviations caused by the aforementioned disturbances. Therefore, it is essential to modify the structure of LFC, to handle the disturbances caused by the RES and load. With regards to the above problem, this work proposes a novel coordinated LFC strategy with modified control signal to have Plug-in Hybrid Electric Vehicles (PHEVs) for frequency stability enhancement of the Japanese power system. Where, the coordinated control strategy is based on the PID controller, which is optimally tuned by the recently developed JAYA Algorithm (JA). Numerous simulations are performed with the proposed methodology and, the results have confirmed the effectiveness of a proposed approach over some recent and well-known techniques in literature. Furthermore, simulation results reveal that the proposed coordinated approach significantly minimizing the frequency deviations compared to the JAYA optimized LFC without PHEVs & with PHEVs but no coordination.
基金the National Key Research and Development Program of China(Grant No.2017YFB0103502)the National Natural Science Fundation of China(Grant No.51805290)+1 种基金the Zhejiang Provincial Natural Science Foundation of China(Grant No.LY18E050015)the Ningbo Natural Science Foundation(Grant No.2018A610124)。
文摘Plug-in hybrid electric vehicles(PHEVs) unite the advantages of the engine and electric motor which could provide great potential in saving energy. However, the fuel economy performance of the PHEVs is highly associated with the driving condition, especially for parallel PHEVs because they could not decouple the engine work status from the driving condition. Meanwhile, fuel economy performance is not only a longitudinal issue but also related to lane selection. Lane selection is an important driving behavior and the algorithm of lane selection is necessary for the development progress of intelligent connected vehicles. Energy consumption cost is an important part of the vehicle’s using consumption cost. Therefore, lane selection strategies must consider this point.With the development of intelligent connected vehicle technology, such as V2X(Vehicle to Everything), the potential of energy consumption performance of intelligent connected PHEVs could be improved by taking environment information from V2X and smart sensors into lane selection. In this paper, a neural network(NN) based method is proposed to predict the future status of the local vehicle using the information from V2X, and then another network is used to estimate the future energy consumption of each lane. The lane selection is decided on energy consumption estimation. Lastly, the effectiveness of the method is validated by simulation using Matlab combined with SUMO(Simulation of Urban MObility).
基金supported by the National Key Research and Development Program of China under Grant 2022YFD1801400 to Zi Lithe National Natural Science Foundation of China under Grants 32302851 to Junchao Shi,32272956 to Zi Li,32172828 to Wenqi Hethe Natural Science Foundation Project of Jilin Province under Grant 20240101014JC to Zi Li.
文摘Coronaviruses(CoVs)are a large family of human and animal pathogens that cause significant health and economic burdens worldwide.Thapsigargin(Tg)is a plant-derived sesquiterpene lactone with potent antiviral effects;however,the underlying mechanism remains unclear.Here,we show that Tg exhibited strong antiviral activity against the neurotropic swine CoV porcine hemagglutinating encephalomyelitis virus(PHEV)both in vivo and in vitro.Tg also exhibited inhibitory activity against other three swine coronaviruses in cell lines.Specifically,Tg treatment significantly inhibited the replication and transcription of genomic RNA in the viral life cycle but did not directly inactivate PHEV.Transcriptome analysis and glycolysis/mitochondrial stress testing confirmed that Tg alters intracellular metabolic flux,and suppresses glycolysis and oxidative phosphorylation(OXPHOS).Furthermore,metabolic reprogramming is associated with the antiviral effect of Tg and is required for productive PHEV infection.Overall,our findings highlight that Tg plays a crucial role in combating viral infections by targeting host energy metabolism shared by pathogenic microorganisms,suggesting that targeting key nodes of host metabolic processes may be a strategy for designing antiviral drugs against coronaviruses.
