As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as w...As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.展开更多
We propose a new generalized Su–Schrieffer–Heeger model with hierarchical long-range hopping based on a onedimensional tetratomic chain. The properties of the topological states and phase transition, which depend on...We propose a new generalized Su–Schrieffer–Heeger model with hierarchical long-range hopping based on a onedimensional tetratomic chain. The properties of the topological states and phase transition, which depend on the cointeraction of the intracell and intercell hoppings, are investigated using the phase diagram of the winding number. It is shown that topological states with large positive/negative winding numbers can readily be generated in this system. The properties of the topological states can be verified by the ring-type structures in the trajectory diagram of the complex plane. The topological phase transition is strongly related to the opening(closure) of an energy bandgap at the center(boundaries) of the Brillouin zone. Finally, the non-zero-energy edge states at the ends of the finite system are revealed and matched with the bulk–boundary correspondence.展开更多
电热能源系统模型维度高将会导致求解难度较大。为此,提出一种兼具求解速度与隐私性的复杂供热管网等值简化模型。首先,基于热网拓扑结构特点,提出可对供热管网进行灵活化简的供热管网拓扑简化方法,并根据简化后的管道结构和参数建立复...电热能源系统模型维度高将会导致求解难度较大。为此,提出一种兼具求解速度与隐私性的复杂供热管网等值简化模型。首先,基于热网拓扑结构特点,提出可对供热管网进行灵活化简的供热管网拓扑简化方法,并根据简化后的管道结构和参数建立复杂供热管网等值简化模型。其次,充分考虑热电联产(combined heat and power,CHP)机组以热定电模式和热网热惯性对旋转备用容量的影响,建立了系统旋转备用模型。基于此,建立了考虑旋转备用约束的电热能源系统调度模型。最后,采用信息间隙决策理论(information gap decision theory, IGDT)处理系统成本与风电不确定度之间的关系。算例结果分析了供热管网拓扑简化方法在不同简化程度下的简化效果,验证了所提模型适用于电热能源系统优化调度,有效地减少优化模型的求解时间。展开更多
基金This project is supported by the National Natural Science Foundation of China(NSFC)(Nos.61806087,61902158).
文摘As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.
基金Project supported by the National Natural Science Foundation of China(Grant No.11405100)the Natural Science Basic Research Program in Shaanxi Province of China(Grant Nos.2022JZ-02,2020JM-507,and 2019JM-332)+1 种基金the Doctoral Research Fund of Shaanxi University of Science and Technology in China(Grant Nos.2018BJ-02 and 2019BJ-58)the Youth Innovation Team of Shaanxi Universities.
文摘We propose a new generalized Su–Schrieffer–Heeger model with hierarchical long-range hopping based on a onedimensional tetratomic chain. The properties of the topological states and phase transition, which depend on the cointeraction of the intracell and intercell hoppings, are investigated using the phase diagram of the winding number. It is shown that topological states with large positive/negative winding numbers can readily be generated in this system. The properties of the topological states can be verified by the ring-type structures in the trajectory diagram of the complex plane. The topological phase transition is strongly related to the opening(closure) of an energy bandgap at the center(boundaries) of the Brillouin zone. Finally, the non-zero-energy edge states at the ends of the finite system are revealed and matched with the bulk–boundary correspondence.
文摘电热能源系统模型维度高将会导致求解难度较大。为此,提出一种兼具求解速度与隐私性的复杂供热管网等值简化模型。首先,基于热网拓扑结构特点,提出可对供热管网进行灵活化简的供热管网拓扑简化方法,并根据简化后的管道结构和参数建立复杂供热管网等值简化模型。其次,充分考虑热电联产(combined heat and power,CHP)机组以热定电模式和热网热惯性对旋转备用容量的影响,建立了系统旋转备用模型。基于此,建立了考虑旋转备用约束的电热能源系统调度模型。最后,采用信息间隙决策理论(information gap decision theory, IGDT)处理系统成本与风电不确定度之间的关系。算例结果分析了供热管网拓扑简化方法在不同简化程度下的简化效果,验证了所提模型适用于电热能源系统优化调度,有效地减少优化模型的求解时间。
