Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainabili...Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainability through coordinated electricity,thermal,natural gas,and hydrogen utilization.This study proposes a two-stage distributionally robust optimization(DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES.The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response(DR)program to adjustflexible multi-energy loads,thereby prioritizing RES consumption.Uncertainties from RES generation and load demand are addressed through an ambiguity set,enabling robust decision-making.The column-and-constraint generation(C&CG)algorithm efficiently solves the two-stage DRO model.Case studies demonstrate that the proposed method reduces operational costs by 3.56%,increases photovoltaic consumption rates by 5.44%,and significantly lowers carbon emissions compared to conventional approaches.Furthermore,the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods,highlighting its potential to advance cost-effective,low-carbon energy systems while ensuring grid stability under uncertainty.展开更多
Doubled haploid(DH)technology has revolutionized crop breeding by enabling the production of homozygous lines in a single generation.In vivo haploid induction(HI)offers a more widely applicable approach that can signi...Doubled haploid(DH)technology has revolutionized crop breeding by enabling the production of homozygous lines in a single generation.In vivo haploid induction(HI)offers a more widely applicable approach that can significantly improve DH breeding efficiency.ToPAR,a parthenogenesis gene,originally identified in dandelion(Taraxacum officinale),has been characterized.Researchers have successfully induced haploid embryo-like structures and haploid offspring in lettuce and foxtail millet,respectively.展开更多
This paper grasps the research theme of artificial intelligence(AI)and human intelligence(HI)synergy to create value,and analyzes the development status of AI and HI in the current context of digital intelligence,as w...This paper grasps the research theme of artificial intelligence(AI)and human intelligence(HI)synergy to create value,and analyzes the development status of AI and HI in the current context of digital intelligence,as well as the significance of their synergy to empower value creation.At the same time,the theory of resource arrangement is introduced,and the connotation and composition of the theory are summarized,as well as the development in the field of research and application.This paper focuses on revealing the intrinsic relationship between resource orchestration theory and AI and HI collaborative work,aiming to fully explore the potential of resource orchestration theory in the collaborative innovation of AI and HI,and put forward practical suggestions based on this.展开更多
基金supported by National Key Research and Development Program(2024YFE0115600).
文摘Addressing climate change and facilitating the large-scale integration of renewable energy sources(RESs)have driven the development of hydrogen-coupled integrated energy systems(HIES),which enhance energy sustainability through coordinated electricity,thermal,natural gas,and hydrogen utilization.This study proposes a two-stage distributionally robust optimization(DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES.The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response(DR)program to adjustflexible multi-energy loads,thereby prioritizing RES consumption.Uncertainties from RES generation and load demand are addressed through an ambiguity set,enabling robust decision-making.The column-and-constraint generation(C&CG)algorithm efficiently solves the two-stage DRO model.Case studies demonstrate that the proposed method reduces operational costs by 3.56%,increases photovoltaic consumption rates by 5.44%,and significantly lowers carbon emissions compared to conventional approaches.Furthermore,the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods,highlighting its potential to advance cost-effective,low-carbon energy systems while ensuring grid stability under uncertainty.
基金supported by the Nanfan Special Project of the Chinese Academy of Agricultural Sciences(Grant Nos.YBXM2320 and YBXM2433)the Project of Sanya Yazhou Bay Science and Technology City,China(Grant No.SCKJ-JYRC-2024-58)the Agricultural Science and Technology Innovation Program,China(Grant No.CAAS-ASTIP-2021-CNRRI).
文摘Doubled haploid(DH)technology has revolutionized crop breeding by enabling the production of homozygous lines in a single generation.In vivo haploid induction(HI)offers a more widely applicable approach that can significantly improve DH breeding efficiency.ToPAR,a parthenogenesis gene,originally identified in dandelion(Taraxacum officinale),has been characterized.Researchers have successfully induced haploid embryo-like structures and haploid offspring in lettuce and foxtail millet,respectively.
文摘This paper grasps the research theme of artificial intelligence(AI)and human intelligence(HI)synergy to create value,and analyzes the development status of AI and HI in the current context of digital intelligence,as well as the significance of their synergy to empower value creation.At the same time,the theory of resource arrangement is introduced,and the connotation and composition of the theory are summarized,as well as the development in the field of research and application.This paper focuses on revealing the intrinsic relationship between resource orchestration theory and AI and HI collaborative work,aiming to fully explore the potential of resource orchestration theory in the collaborative innovation of AI and HI,and put forward practical suggestions based on this.
