Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.展开更多
Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited comp...Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited computation and communication resources of the secondary controller.To enhance the efficiency of secondary control,we developed a novel distributed self-triggered active power-sharing control strategy by introducing the signum function and a flexible linear clock.Unlike continuous communication–based controllers,the proposed self-triggered distributed controller prompts distributed generators to perform control actions and share information with their neighbors only at specific time instants monitored by the linear clock.Therefore,this approach results in a significant reduction in both the computation and communication requirements.Moreover,this design naturally avoids Zeno behavior.Furthermore,a modified triggering condition was established to achieve further reductions in computation and communication.The simulation results confirmed that the proposed control scheme achieves distributed active power sharing with very few controller triggers,thereby substantially enhancing the efficacy of secondary control in MGs.展开更多
在“双碳”目标背景下,探究重庆三峡库区农业碳排放特征及其驱动因素,可为库区低碳农业发展提供科学依据。采用联合国政府间气候变化专门委员会(IPCC)的因子法测算2015—2022年重庆三峡库区农业碳排放量,系统分析库区农业碳排放量和强...在“双碳”目标背景下,探究重庆三峡库区农业碳排放特征及其驱动因素,可为库区低碳农业发展提供科学依据。采用联合国政府间气候变化专门委员会(IPCC)的因子法测算2015—2022年重庆三峡库区农业碳排放量,系统分析库区农业碳排放量和强度时空分异特征,利用Tapio脱钩模型分析库区农业碳排放量与农业经济增长的脱钩关系,并进一步运用LMDI(logarithmic mean divisia index)模型解析库区农业碳排放驱动因素。结果表明:重庆三峡库区农业碳排放总量整体呈波动降低趋势,农业碳排放总量从2015年的645.89万t降至2022年的620.74万t,库区农业碳排放主要来源为农田土壤碳排放和畜禽养殖碳排放。库区农业碳排放强度总体呈下降趋势,各区县间碳排放强度差距逐渐缩小。2015—2022年,库区农业经济与农业碳排放量整体上呈脱钩关系。随着农业生产的恢复与发展,农业产值增长,农业碳排放量增加。脱钩关系以2019年为节点表现为由强脱钩向弱脱钩转变。农业生产效率、农业人口规模、农业产业结构对库区农业碳排放量的增长具有抑制作用,而农业经济规模对农业碳排放量的增长则具有促进作用。基于以上结果,本文提出减少禽畜养殖业碳排放量、控制农田土壤利用碳排放量和发挥农业碳排放驱动因素抑制作用等相关建议,以期为库区低碳农业发展提供理论依据。展开更多
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
基金Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Northeast Electric Power University)Open Fund(MPSS2023⁃01)National Natural Science Foundation of China(No.52477133)+2 种基金Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited computation and communication resources of the secondary controller.To enhance the efficiency of secondary control,we developed a novel distributed self-triggered active power-sharing control strategy by introducing the signum function and a flexible linear clock.Unlike continuous communication–based controllers,the proposed self-triggered distributed controller prompts distributed generators to perform control actions and share information with their neighbors only at specific time instants monitored by the linear clock.Therefore,this approach results in a significant reduction in both the computation and communication requirements.Moreover,this design naturally avoids Zeno behavior.Furthermore,a modified triggering condition was established to achieve further reductions in computation and communication.The simulation results confirmed that the proposed control scheme achieves distributed active power sharing with very few controller triggers,thereby substantially enhancing the efficacy of secondary control in MGs.
文摘在“双碳”目标背景下,探究重庆三峡库区农业碳排放特征及其驱动因素,可为库区低碳农业发展提供科学依据。采用联合国政府间气候变化专门委员会(IPCC)的因子法测算2015—2022年重庆三峡库区农业碳排放量,系统分析库区农业碳排放量和强度时空分异特征,利用Tapio脱钩模型分析库区农业碳排放量与农业经济增长的脱钩关系,并进一步运用LMDI(logarithmic mean divisia index)模型解析库区农业碳排放驱动因素。结果表明:重庆三峡库区农业碳排放总量整体呈波动降低趋势,农业碳排放总量从2015年的645.89万t降至2022年的620.74万t,库区农业碳排放主要来源为农田土壤碳排放和畜禽养殖碳排放。库区农业碳排放强度总体呈下降趋势,各区县间碳排放强度差距逐渐缩小。2015—2022年,库区农业经济与农业碳排放量整体上呈脱钩关系。随着农业生产的恢复与发展,农业产值增长,农业碳排放量增加。脱钩关系以2019年为节点表现为由强脱钩向弱脱钩转变。农业生产效率、农业人口规模、农业产业结构对库区农业碳排放量的增长具有抑制作用,而农业经济规模对农业碳排放量的增长则具有促进作用。基于以上结果,本文提出减少禽畜养殖业碳排放量、控制农田土壤利用碳排放量和发挥农业碳排放驱动因素抑制作用等相关建议,以期为库区低碳农业发展提供理论依据。
