The Last Interglacial Period strata in the Milanggouwan section in the Salawusu River valley on the Ordos Plateau, China, have 8.5 sedimentary cycles composed alternately of eolian dune sands, fluvio-lacustrine facies...The Last Interglacial Period strata in the Milanggouwan section in the Salawusu River valley on the Ordos Plateau, China, have 8.5 sedimentary cycles composed alternately of eolian dune sands, fluvio-lacustrine facies and paleosols. Based on comprehensive analyses on the distribution of magnetic susceptibility and CaCO3 and paleo-ecology indicated by fossils in the region, it is considered that the sedimentation cycles resulted from dry-cold and warm-humid climate fluctuations. Magnetic susceptibility values and CaCO3 contents in stratigraphic sectors I, III, V and II, IV basically respectively present peaks and low vales, and the former three can in time correlate with MIS5a, MIS5c and MIS5e successively and the latter two with MIS5b and MIS5d. In addition, some horizons of eolian dune sands and the low vales of their magnetic susceptibility and CaCO3 are also correlated with 6 periods of cooling events indicated by the higher content of foraminifer Neogloboquadrina pachyderma (S.) documented in the V29—191 drill in the North Atlantic and the cold events recorded by δ 18O in the ice cores in GRIP, especially with 9 periods of dust events in Chinese Loess Plateau.展开更多
[Objective]The paper was to discuss identification effects of pedometer on estrus of Holstein cows during peak lactation period. [Method]The estrus of Holstein cows during peak lactation period were identified by manu...[Objective]The paper was to discuss identification effects of pedometer on estrus of Holstein cows during peak lactation period. [Method]The estrus of Holstein cows during peak lactation period were identified by manual observation and pedometer monitoring. [Result]Compared with manual observation,the detection rate of estrus in Holstein cows using pedometer monitoring was increased by 24. 01%,which reduced the labor cost and enhanced accuracy rate. [Conclusion]The research could provide reliable basis for estrus identification of cows.展开更多
With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this prob...With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.展开更多
Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours ...Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.展开更多
基金supported by the National Basic Research Program of China(Grant 2004CB720200)the National Natural Science Foundation of China(Grant 49971009)the Chinese Academy of Sciences(Grant KZCX2-SW-118).
文摘The Last Interglacial Period strata in the Milanggouwan section in the Salawusu River valley on the Ordos Plateau, China, have 8.5 sedimentary cycles composed alternately of eolian dune sands, fluvio-lacustrine facies and paleosols. Based on comprehensive analyses on the distribution of magnetic susceptibility and CaCO3 and paleo-ecology indicated by fossils in the region, it is considered that the sedimentation cycles resulted from dry-cold and warm-humid climate fluctuations. Magnetic susceptibility values and CaCO3 contents in stratigraphic sectors I, III, V and II, IV basically respectively present peaks and low vales, and the former three can in time correlate with MIS5a, MIS5c and MIS5e successively and the latter two with MIS5b and MIS5d. In addition, some horizons of eolian dune sands and the low vales of their magnetic susceptibility and CaCO3 are also correlated with 6 periods of cooling events indicated by the higher content of foraminifer Neogloboquadrina pachyderma (S.) documented in the V29—191 drill in the North Atlantic and the cold events recorded by δ 18O in the ice cores in GRIP, especially with 9 periods of dust events in Chinese Loess Plateau.
基金Supported by Fund of Xinjiang Agricultural Vocational Technical College in2011(XJNZYKJ2011012)
文摘[Objective]The paper was to discuss identification effects of pedometer on estrus of Holstein cows during peak lactation period. [Method]The estrus of Holstein cows during peak lactation period were identified by manual observation and pedometer monitoring. [Result]Compared with manual observation,the detection rate of estrus in Holstein cows using pedometer monitoring was increased by 24. 01%,which reduced the labor cost and enhanced accuracy rate. [Conclusion]The research could provide reliable basis for estrus identification of cows.
基金supported by the Science and Technology Project from the State Grid Shanghai Municipal Electric Power Company of China (52094019006U)the Shanghai Rising-Star Program (18QB1400200)。
文摘With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.
基金Key R&D Program of Tianjin,China(No.20YFYSGX00060).
文摘Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.
