热电联产(combined heat and power,CHP)机组作为区域综合能源系统中的核心耦合单元,是实现其高效运行的关键。然而CHP机组固有的热电耦合特性对其灵活调节能力和运行性能的提升存在一定限制,且其“以电定热”和“以热定电”的调度策略...热电联产(combined heat and power,CHP)机组作为区域综合能源系统中的核心耦合单元,是实现其高效运行的关键。然而CHP机组固有的热电耦合特性对其灵活调节能力和运行性能的提升存在一定限制,且其“以电定热”和“以热定电”的调度策略缺乏前瞻性考虑多元负荷和可再生能源的波动特征。集成储能系统可有效实现热电解耦,然而储能的充放电能力受其能量状态的影响。基于此,该文采用长短记忆神经网络对区域综合能源系统中多元负荷及可再生能源进行预测,以考虑多元负荷及可再生能源的时序波动,提出耦合源-荷多元预测与电热混合储能的主动调度策略。构建计及碳排放惩罚、可再生能源弃电惩罚及运行成本的优化调度模型。以某区域综合能源系统为例,对比分析“以电定热”、“以热定电”和“主动调度”策略。结果显示,长短记忆神经网络的最大预测误差为4.7%。采用电-热混合储能主动调度策略的运行成本比“以电定热”和“以热定电”运行策略分别降低了11.12%和3.67%。此外,主动调度策略可在平滑热电比负荷曲线的同时降低区域综合能源系统购电成本,并且对CHP机组的能效具有促进作用,进一步降低了区域综合能源系统的运行成本。展开更多
This study empirically examines the impact,mechanisms,and heterogeneity of artificial intelligence(AI)on innovation in manufacturing enterprises,using data from Chinese A-share listed companies(2011-2022).Using fixed-...This study empirically examines the impact,mechanisms,and heterogeneity of artificial intelligence(AI)on innovation in manufacturing enterprises,using data from Chinese A-share listed companies(2011-2022).Using fixed-effects models and mediation analysis,we find that AI significantly drives innovation in manufacturing,a conclusion supported by various robustness checks.The development of AI enables manufacturing enterprises to achieve cost savings and workforce upgrading.Mechanism analysis identifies two key channels through which AI fosters innovation:increasing talent compensation and widening wage disparities.Heterogeneity tests reveal stronger innovation effects in non-state-owned enterprises,firms in the mature and declining stages,industries with lower concentration,and enterprises located in central and eastern China.Further analysis shows that AI’s impact on substantive innovation is non-linear and moderated by technological intensity and economic uncertainty.Based on these findings,we propose policy recommendations,including the steadfast promotion of intelligent transformation,stage-differentiated implementation,enhanced talent cultivation and policy support,and the accelerated realization of AI’s innovation potential.展开更多
文摘热电联产(combined heat and power,CHP)机组作为区域综合能源系统中的核心耦合单元,是实现其高效运行的关键。然而CHP机组固有的热电耦合特性对其灵活调节能力和运行性能的提升存在一定限制,且其“以电定热”和“以热定电”的调度策略缺乏前瞻性考虑多元负荷和可再生能源的波动特征。集成储能系统可有效实现热电解耦,然而储能的充放电能力受其能量状态的影响。基于此,该文采用长短记忆神经网络对区域综合能源系统中多元负荷及可再生能源进行预测,以考虑多元负荷及可再生能源的时序波动,提出耦合源-荷多元预测与电热混合储能的主动调度策略。构建计及碳排放惩罚、可再生能源弃电惩罚及运行成本的优化调度模型。以某区域综合能源系统为例,对比分析“以电定热”、“以热定电”和“主动调度”策略。结果显示,长短记忆神经网络的最大预测误差为4.7%。采用电-热混合储能主动调度策略的运行成本比“以电定热”和“以热定电”运行策略分别降低了11.12%和3.67%。此外,主动调度策略可在平滑热电比负荷曲线的同时降低区域综合能源系统购电成本,并且对CHP机组的能效具有促进作用,进一步降低了区域综合能源系统的运行成本。
基金funded by grants from the National Social Science Fund of China General Project“Research on Value Creation of New Quality Productive Forces in Manufacturing Driven by Digital Intelligence”(No.24BJY005).
文摘This study empirically examines the impact,mechanisms,and heterogeneity of artificial intelligence(AI)on innovation in manufacturing enterprises,using data from Chinese A-share listed companies(2011-2022).Using fixed-effects models and mediation analysis,we find that AI significantly drives innovation in manufacturing,a conclusion supported by various robustness checks.The development of AI enables manufacturing enterprises to achieve cost savings and workforce upgrading.Mechanism analysis identifies two key channels through which AI fosters innovation:increasing talent compensation and widening wage disparities.Heterogeneity tests reveal stronger innovation effects in non-state-owned enterprises,firms in the mature and declining stages,industries with lower concentration,and enterprises located in central and eastern China.Further analysis shows that AI’s impact on substantive innovation is non-linear and moderated by technological intensity and economic uncertainty.Based on these findings,we propose policy recommendations,including the steadfast promotion of intelligent transformation,stage-differentiated implementation,enhanced talent cultivation and policy support,and the accelerated realization of AI’s innovation potential.
