With the increasingly widespread of advanced metering infrastructure,electric load clustering is becoming more essential for its great potential in analytics of consumers’energy consumption patterns and preference th...With the increasingly widespread of advanced metering infrastructure,electric load clustering is becoming more essential for its great potential in analytics of consumers’energy consumption patterns and preference through data mining.Moreover,a variety of electric load clustering techniques have been put into practice to obtain the distribution of load data,observe the characteristics of load clusters,and classify the components of the total load.This can give rise to the development of related techniques and research in the smart grid,such as demand-side response.This paper summarizes the basic concepts and the general process in electric load clustering.Several similarity measurements and five major categories in electric load clustering are then comprehensively summarized along with their advantages and disadvantages.Afterwards,eight indices widely used to evaluate the validity of electric load clustering are described.Finally,vital applications are discussed thoroughly along with future trends including the tariff design,anomaly detection,load forecasting,data security and big data,etc.展开更多
The Ultrasonic Electric Propulsion(UEP)system is a cutting-edge propulsion technology that is mostly used on platforms for small satellites(less than 10 kg).The characteristics of droplet partial emissions(DPEs)in the...The Ultrasonic Electric Propulsion(UEP)system is a cutting-edge propulsion technology that is mostly used on platforms for small satellites(less than 10 kg).The characteristics of droplet partial emissions(DPEs)in the UEP system are investigated using a high-speed imaging technique(an ultra-high speed camera(NAC HX-6)and a long-distance microscope)in this work.The experiments demonstrate that there are a few partial emission modes,including left-side emission,double-side emission,and right-side emission,that are present in the droplet emission process of the UEP system.These modes are primarily caused by the partial formation of capillary standing waves(CSWs)on the emission surface of the ultrasonic nozzle.The emission rate for single-and double-sided emissions varies at different times,indicating that there are different CSWs engaged in droplet emission due to variations in the liquid film thickness and charge state of the liquid cones.Additionally,as the droplets emit continuously,a raised area on the emission surface appears,with several droplets emitting there as a result of charge accumulation.Additionally,photos of the CSWs with emitting droplets are obtained,which highlights the CSWs'distinctive wave morphology.展开更多
With the dramatic increase in electric vehicles(EVs)globally,the demand for lithium-ion batteries has grown dramatically,resulting in many batteries being retired in the future.Developing a rapid and robust capacity e...With the dramatic increase in electric vehicles(EVs)globally,the demand for lithium-ion batteries has grown dramatically,resulting in many batteries being retired in the future.Developing a rapid and robust capacity estimation method is a challenging work to recognize the battery aging level on service and provide regroup strategy of the retied batteries in secondary use.There are still limitations on the current rapid battery capacity estimation methods,such as direct current internal resistance(DCIR)and electrochemical impedance spectroscopy(EIS),in terms of efficiency and robustness.To address the challenges,this paper proposes an improved version of DCIR,named pulse impedance technique(PIT),for rapid battery capacity estimation with more robustness.First,PIT is carried out based on the transient current excitation and dynamic voltage measurement using the high sampling frequency,in which the coherence analysis is used to guide the selection of a reliable frequency band.The battery impedance can be extracted in a wide range of frequency bands compared to the traditional DCIR method,which obtains more information on the battery capacity evaluation.Second,various statistical variables are used to extract aging features,and Pearson correlation analysis is applied to determine the highly correlated features.Then a linear regression model is developed to map the relationship between extracted features and battery capacity.To validate the performance of the proposed method,the experimental system is designed to conduct comparative studies between PIT and EIS based on the two 18650 batteries connected in series.The results reveal that the proposed PIT can provide comparative indicators to EIS,which contributes higher estimation accuracy of the proposed PIT method than EIS technology with lower time and cost.展开更多
基金supported in part by the National Natural Science Foundation of China(No.51877189)National Natural Science Foundation of China Joint Program on Smart Grid(No.U2066601)Young Elite Scientists Sponsorship Program by China Association of Science and Technology(No.2018QNRC001)。
文摘With the increasingly widespread of advanced metering infrastructure,electric load clustering is becoming more essential for its great potential in analytics of consumers’energy consumption patterns and preference through data mining.Moreover,a variety of electric load clustering techniques have been put into practice to obtain the distribution of load data,observe the characteristics of load clusters,and classify the components of the total load.This can give rise to the development of related techniques and research in the smart grid,such as demand-side response.This paper summarizes the basic concepts and the general process in electric load clustering.Several similarity measurements and five major categories in electric load clustering are then comprehensively summarized along with their advantages and disadvantages.Afterwards,eight indices widely used to evaluate the validity of electric load clustering are described.Finally,vital applications are discussed thoroughly along with future trends including the tariff design,anomaly detection,load forecasting,data security and big data,etc.
基金supported by National Natural Science Foundation of China(No.12102099)the National Key R&D Program of China(No.2021YFC2202700)the Outstanding Academic Leader Project of Shanghai(Youth)(No.23XD1421700),respectively。
文摘The Ultrasonic Electric Propulsion(UEP)system is a cutting-edge propulsion technology that is mostly used on platforms for small satellites(less than 10 kg).The characteristics of droplet partial emissions(DPEs)in the UEP system are investigated using a high-speed imaging technique(an ultra-high speed camera(NAC HX-6)and a long-distance microscope)in this work.The experiments demonstrate that there are a few partial emission modes,including left-side emission,double-side emission,and right-side emission,that are present in the droplet emission process of the UEP system.These modes are primarily caused by the partial formation of capillary standing waves(CSWs)on the emission surface of the ultrasonic nozzle.The emission rate for single-and double-sided emissions varies at different times,indicating that there are different CSWs engaged in droplet emission due to variations in the liquid film thickness and charge state of the liquid cones.Additionally,as the droplets emit continuously,a raised area on the emission surface appears,with several droplets emitting there as a result of charge accumulation.Additionally,photos of the CSWs with emitting droplets are obtained,which highlights the CSWs'distinctive wave morphology.
基金support from the China Scholarship Council(Grant No.202108890044).
文摘With the dramatic increase in electric vehicles(EVs)globally,the demand for lithium-ion batteries has grown dramatically,resulting in many batteries being retired in the future.Developing a rapid and robust capacity estimation method is a challenging work to recognize the battery aging level on service and provide regroup strategy of the retied batteries in secondary use.There are still limitations on the current rapid battery capacity estimation methods,such as direct current internal resistance(DCIR)and electrochemical impedance spectroscopy(EIS),in terms of efficiency and robustness.To address the challenges,this paper proposes an improved version of DCIR,named pulse impedance technique(PIT),for rapid battery capacity estimation with more robustness.First,PIT is carried out based on the transient current excitation and dynamic voltage measurement using the high sampling frequency,in which the coherence analysis is used to guide the selection of a reliable frequency band.The battery impedance can be extracted in a wide range of frequency bands compared to the traditional DCIR method,which obtains more information on the battery capacity evaluation.Second,various statistical variables are used to extract aging features,and Pearson correlation analysis is applied to determine the highly correlated features.Then a linear regression model is developed to map the relationship between extracted features and battery capacity.To validate the performance of the proposed method,the experimental system is designed to conduct comparative studies between PIT and EIS based on the two 18650 batteries connected in series.The results reveal that the proposed PIT can provide comparative indicators to EIS,which contributes higher estimation accuracy of the proposed PIT method than EIS technology with lower time and cost.
