Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electri...Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.展开更多
The number of available control sources is a limiting factor to many network control tasks.A lack of input sources can result in compromised controllability and/or sub-optimal network performance,as noted in engineeri...The number of available control sources is a limiting factor to many network control tasks.A lack of input sources can result in compromised controllability and/or sub-optimal network performance,as noted in engineering applications such as the smart grids.The mechanism can be explained by a linear timeinvariant model,where structural controllability sets a lower bound on the number of required sources.Inspired by the ubiquity of time-varying topologies in the real world,we propose the strategy of spatiotemporal input control to overcome the source-related limit by exploiting temporal variation of the network topology.We theoretically prove that under this regime,the required number of sources can always be reduced to 2.It is further shown that the cost of control depends on two hyperparameters,the numbers of sources and intervals,in a trade-off fashion.As a demonstration,we achieve controllability over a complex network resembling the nervous system of Caenorhabditis elegans using as few as 6%of the sources predicted by a static control model.This example underlines the potential of utilizing topological variation in complex network control problems.展开更多
The International Conference on"Quantitative Biology 2019:Dynamic Signaling in Cells and Embryos"was successfully held at Dongshan Hotel,Yantai,China,from June 22nd to 24th.The conference was co-sponsored by...The International Conference on"Quantitative Biology 2019:Dynamic Signaling in Cells and Embryos"was successfully held at Dongshan Hotel,Yantai,China,from June 22nd to 24th.The conference was co-sponsored by the Center for Quantitative Biology(CQB)of Peking University and Yantai University and was organized by Prof.Chao Tang,Prof.Feng Liu,and Prof.Yihan Lin from Peking University,China,Prof.Michael B.Elowitz from Caltech,USA,and Prof.Yibao Chen and Prof.Xuran Wu from Yantai University,China.Totally 26 experts in the field of quantitative biology were invited to deliver talks from Canada,China,France,Germany,Israel,Japan,Singapore,South Korea,Spain,and United States.A total of 267 researchers worldwide attended the conference,and participated in diverse conference activities,including invited and contributed talks,flash talks,poster presentations,and panel discussions.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:51677059。
文摘Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.
基金partially supported by the National Key RD Program of China(2020AAA0105200,2018AAA01012600)National Natural Science Foundation of China(61876215)+5 种基金Beijing Academy of Artificial Intelligence(BAAI)in part by the Science and Technology Major Project of Guangzhou(202007030006)Pengcheng laboratorypartially funded by the Ministry of Education,Singapore,under contract RG19/20partly supported by the Future Resilient Systems Project(FRS-Ⅱ)at the Singapore-ETH Centre(SEC)funded by the National Research Foundation of Singapore(NRF)。
文摘The number of available control sources is a limiting factor to many network control tasks.A lack of input sources can result in compromised controllability and/or sub-optimal network performance,as noted in engineering applications such as the smart grids.The mechanism can be explained by a linear timeinvariant model,where structural controllability sets a lower bound on the number of required sources.Inspired by the ubiquity of time-varying topologies in the real world,we propose the strategy of spatiotemporal input control to overcome the source-related limit by exploiting temporal variation of the network topology.We theoretically prove that under this regime,the required number of sources can always be reduced to 2.It is further shown that the cost of control depends on two hyperparameters,the numbers of sources and intervals,in a trade-off fashion.As a demonstration,we achieve controllability over a complex network resembling the nervous system of Caenorhabditis elegans using as few as 6%of the sources predicted by a static control model.This example underlines the potential of utilizing topological variation in complex network control problems.
文摘The International Conference on"Quantitative Biology 2019:Dynamic Signaling in Cells and Embryos"was successfully held at Dongshan Hotel,Yantai,China,from June 22nd to 24th.The conference was co-sponsored by the Center for Quantitative Biology(CQB)of Peking University and Yantai University and was organized by Prof.Chao Tang,Prof.Feng Liu,and Prof.Yihan Lin from Peking University,China,Prof.Michael B.Elowitz from Caltech,USA,and Prof.Yibao Chen and Prof.Xuran Wu from Yantai University,China.Totally 26 experts in the field of quantitative biology were invited to deliver talks from Canada,China,France,Germany,Israel,Japan,Singapore,South Korea,Spain,and United States.A total of 267 researchers worldwide attended the conference,and participated in diverse conference activities,including invited and contributed talks,flash talks,poster presentations,and panel discussions.
