Typical application scenarios,such as vehicle to grid(V2G)and frequency regulation,have imposed significant long-life demands on lithium-ion batteries.Herein,we propose an advanced battery life-extension method employ...Typical application scenarios,such as vehicle to grid(V2G)and frequency regulation,have imposed significant long-life demands on lithium-ion batteries.Herein,we propose an advanced battery life-extension method employing bidirectional pulse charging(BPC)strategy.Unlike traditional constant current charging methods,BPC strategy not only achieves comparable charging speeds but also facilitates V2G frequency regulation simultaneously.It significantly enhances battery cycle ampere-hour throughput and demonstrates remarkable life extension capabilities.For this interesting conclusion,adopting model identification and postmortem characterization to reveal the life regulation mechanism of BPC:it mitigates battery capacity loss attributed to loss of lithium-ion inventory(LLI)in graphite anodes by intermittently regulating the overall battery voltage and anode potential using a negative charging current.Then,from the perspective of internal side reaction,the life extension mechanism is further revealed as inhibition of solid electrolyte interphase(SEI)and lithium dendrite growth by regulating voltage with a bidirectional pulse current,and a semi-empirical life degradation model combining SEI and lithium dendrite growth is developed for BPC scenarios health management,the model parameters are identified by genetic algorithm with the life simulation exhibiting an accuracy exceeding 99%.This finding indicates that under typical rate conditions,adaptable BPC strategies can extend the service life of LFP battery by approximately 123%.Consequently,the developed advanced BPC strategy offers innovative perspectives and insights for the development of long-life battery applications in the future.展开更多
This paper presents an advanced methodology for optimizing a UK network load demand with various uncertainties which are related to individual driving behaviours. Without the optimized regulation for traditional power...This paper presents an advanced methodology for optimizing a UK network load demand with various uncertainties which are related to individual driving behaviours. Without the optimized regulation for traditional power system demand, EVs （electric vehicles） would have an adverse impact on the stability of power systems. This becomes more significant for large-scale EVs plugging into the power grid. Traditional optimized methodologies are effective only for EV charging. The proposed techniques improve the system flexibility and stability through an advanced optimization model and flexible bidirectional charging/discharging control. Three scenarios with different charging and discharging power levels and various penetration levels of EVs are discussed in detail in this paper. Simulation results demonstrate that bidirectional EV power flow control has vast potentials to improve the load demand profile, with increased proportion of EVs, and charging/discharging power levels.展开更多
Across the U.S.,the increasing demand for electric vehicle(EV)charging infrastructure is placing new demands on the power grid,challenging its stability and efficiency.To address these challenges,this study proposes a...Across the U.S.,the increasing demand for electric vehicle(EV)charging infrastructure is placing new demands on the power grid,challenging its stability and efficiency.To address these challenges,this study proposes a Vehicle-to-Building-to-Grid(V2B2G)framework that incorporates urban-scale human mobility modeling to optimize EV charging and discharging.Using anonymized GPS traces from the study community,we extracted individual mobility patterns and applied kernel-density estimation to predict departure and arrival times for each user.The framework was tested in a mixed-use community in Phoenix,Arizona that includes both residential and commercial buildings.A comprehensive decentralized model predictive control(MPC)framework is implemented to minimize energy costs and enhance grid flexibility through demand-side management while maintaining occupant comfort.Four different control strategies were designed and evaluated,the strategy which balances both user and grid benefits demonstrated the best performance,achieving:(1)a flattened grid net load curve,with a 56%reduction in on-peak demand and a 56%decrease in peak load rebound;(2)a 37.96%reduction in grid net load compared to the baseline control;and(3)a 68.05%performance improvement when considering six flexibility factors:cost savings,total-energy reduction,on-peak demand reduction,off-peak demand reduction,load shifting from peak to non-peak hours,and peak-load-rebound reduction.These findings enhance our understanding of the impacts of urban mobility and EV charging optimization on grid management.展开更多
基金supported by the National Natural Science Foundation of China(52177217)。
文摘Typical application scenarios,such as vehicle to grid(V2G)and frequency regulation,have imposed significant long-life demands on lithium-ion batteries.Herein,we propose an advanced battery life-extension method employing bidirectional pulse charging(BPC)strategy.Unlike traditional constant current charging methods,BPC strategy not only achieves comparable charging speeds but also facilitates V2G frequency regulation simultaneously.It significantly enhances battery cycle ampere-hour throughput and demonstrates remarkable life extension capabilities.For this interesting conclusion,adopting model identification and postmortem characterization to reveal the life regulation mechanism of BPC:it mitigates battery capacity loss attributed to loss of lithium-ion inventory(LLI)in graphite anodes by intermittently regulating the overall battery voltage and anode potential using a negative charging current.Then,from the perspective of internal side reaction,the life extension mechanism is further revealed as inhibition of solid electrolyte interphase(SEI)and lithium dendrite growth by regulating voltage with a bidirectional pulse current,and a semi-empirical life degradation model combining SEI and lithium dendrite growth is developed for BPC scenarios health management,the model parameters are identified by genetic algorithm with the life simulation exhibiting an accuracy exceeding 99%.This finding indicates that under typical rate conditions,adaptable BPC strategies can extend the service life of LFP battery by approximately 123%.Consequently,the developed advanced BPC strategy offers innovative perspectives and insights for the development of long-life battery applications in the future.
文摘This paper presents an advanced methodology for optimizing a UK network load demand with various uncertainties which are related to individual driving behaviours. Without the optimized regulation for traditional power system demand, EVs （electric vehicles） would have an adverse impact on the stability of power systems. This becomes more significant for large-scale EVs plugging into the power grid. Traditional optimized methodologies are effective only for EV charging. The proposed techniques improve the system flexibility and stability through an advanced optimization model and flexible bidirectional charging/discharging control. Three scenarios with different charging and discharging power levels and various penetration levels of EVs are discussed in detail in this paper. Simulation results demonstrate that bidirectional EV power flow control has vast potentials to improve the load demand profile, with increased proportion of EVs, and charging/discharging power levels.
基金supported by the U.S.National Science Foundation(Award No.1949372).
文摘Across the U.S.,the increasing demand for electric vehicle(EV)charging infrastructure is placing new demands on the power grid,challenging its stability and efficiency.To address these challenges,this study proposes a Vehicle-to-Building-to-Grid(V2B2G)framework that incorporates urban-scale human mobility modeling to optimize EV charging and discharging.Using anonymized GPS traces from the study community,we extracted individual mobility patterns and applied kernel-density estimation to predict departure and arrival times for each user.The framework was tested in a mixed-use community in Phoenix,Arizona that includes both residential and commercial buildings.A comprehensive decentralized model predictive control(MPC)framework is implemented to minimize energy costs and enhance grid flexibility through demand-side management while maintaining occupant comfort.Four different control strategies were designed and evaluated,the strategy which balances both user and grid benefits demonstrated the best performance,achieving:(1)a flattened grid net load curve,with a 56%reduction in on-peak demand and a 56%decrease in peak load rebound;(2)a 37.96%reduction in grid net load compared to the baseline control;and(3)a 68.05%performance improvement when considering six flexibility factors:cost savings,total-energy reduction,on-peak demand reduction,off-peak demand reduction,load shifting from peak to non-peak hours,and peak-load-rebound reduction.These findings enhance our understanding of the impacts of urban mobility and EV charging optimization on grid management.
