The uncertainties associated with the variations in the thermosphere are responsible for the inaccurate prediction of the orbit decay of low Earth orbiting space objects due to the drag force.Accurate forecasting of t...The uncertainties associated with the variations in the thermosphere are responsible for the inaccurate prediction of the orbit decay of low Earth orbiting space objects due to the drag force.Accurate forecasting of the thermosphere is urgently required to avoid satellite collisions,which is a potential threat to the rapid growth of spacecraft applications.However,owing to the imperfections in the physics-based forecast model,the long-range forecast of the thermosphere is still primitive even if the accurate prediction of the external forcing is achieved.In this study,we constructed a novel methodology to forecast the thermosphere for tens of days by specifying the uncertain parameters in a physics-based model using an intelligent optimized particle filtering algorithm.A comparison of the results suggested that this method has the capability of providing a more reliable forecast with more than 30-days leading time for the thermospheric mass density than the existing ones under both weak and severe disturbed conditions,if solar and geomagnetic forcing is known.Moreover,the accurate estimation of the state of thermosphere based on this technique would further contribute to the understanding of the temporal and spatial evolution of the upper atmosphere.展开更多
In this paper, a cost-benefit analysis based optimal planning model of battery energy storage system(BESS) in active distribution system(ADS) is established considering a new BESS operation strategy. Reliability impro...In this paper, a cost-benefit analysis based optimal planning model of battery energy storage system(BESS) in active distribution system(ADS) is established considering a new BESS operation strategy. Reliability improvement benefit of BESS is considered and a numerical calculation method based on expectation is proposed for simple and convenient calculation of system reliability improvement with BESS in planning phase. Decision variables include both configuration variables and operation strategy control variables. In order to prevent the interaction between two types of variables and enhance global search ability, intelligent single particle optimizer(ISPO) is adopted to optimize this model. Case studies on a modified IEEE benchmark system verified the performance of the proposed operation strategy and optimal planning model of BESS.展开更多
基金supported by the Project of Stable Support for Youth Team in Basic Research Field,CAS(Grant No.YSBR-018)the B-type Strategic Priority Program of the Chinese Academy of Sciences(Grant No.XDB41000000)the China Postdoctoral Science Foundation(Grant No.2021TQ0318)。
文摘The uncertainties associated with the variations in the thermosphere are responsible for the inaccurate prediction of the orbit decay of low Earth orbiting space objects due to the drag force.Accurate forecasting of the thermosphere is urgently required to avoid satellite collisions,which is a potential threat to the rapid growth of spacecraft applications.However,owing to the imperfections in the physics-based forecast model,the long-range forecast of the thermosphere is still primitive even if the accurate prediction of the external forcing is achieved.In this study,we constructed a novel methodology to forecast the thermosphere for tens of days by specifying the uncertain parameters in a physics-based model using an intelligent optimized particle filtering algorithm.A comparison of the results suggested that this method has the capability of providing a more reliable forecast with more than 30-days leading time for the thermospheric mass density than the existing ones under both weak and severe disturbed conditions,if solar and geomagnetic forcing is known.Moreover,the accurate estimation of the state of thermosphere based on this technique would further contribute to the understanding of the temporal and spatial evolution of the upper atmosphere.
文摘In this paper, a cost-benefit analysis based optimal planning model of battery energy storage system(BESS) in active distribution system(ADS) is established considering a new BESS operation strategy. Reliability improvement benefit of BESS is considered and a numerical calculation method based on expectation is proposed for simple and convenient calculation of system reliability improvement with BESS in planning phase. Decision variables include both configuration variables and operation strategy control variables. In order to prevent the interaction between two types of variables and enhance global search ability, intelligent single particle optimizer(ISPO) is adopted to optimize this model. Case studies on a modified IEEE benchmark system verified the performance of the proposed operation strategy and optimal planning model of BESS.
