Nowadays,the microgrid cluster is an important application scenario for energy trading.In trading,one of the most important research directions is the issue of pricing.To determine reasonable pricing for the microgrid...Nowadays,the microgrid cluster is an important application scenario for energy trading.In trading,one of the most important research directions is the issue of pricing.To determine reasonable pricing for the microgrid cluster,data communication is used to create the cyber-physical system(CPS),which can improve the observability of microgrids.Then,the following works are carried out in the CPS.In the physical layer:1)Regarding trading between microgrids and the load,based on the generalized game theory,an optimal pricing strategy is proposed,which takes into account the interactive relationships among microgrids and transforms the pricing problem into a Nikaido-Isoda function to obtain the optimal prices conveniently;2)Regarding peer-to-peer trading between two microgrids,based on evolutionary game theory and the penalty mechanism,the optimal sale price of the seller is selected with boundary rationality.In the cyber layer,regarding the communication interruption issue existing in pricing(i.e.,the game process),based on the principle of matching the performance of the path with the importance degree of the data,a dynamic regulating method of paths is proposed,i.e.,adopting a new path to re-transmit the interrupted data to the destination.Finally,the effect of the proposed strategies is verified by case studies.展开更多
A system combining photovoltaic power generation and cogeneration is proposed to improve the photoelectric absorption capacity. First, a time-of-use price strategy is adopted to guide users to change their electricity...A system combining photovoltaic power generation and cogeneration is proposed to improve the photoelectric absorption capacity. First, a time-of-use price strategy is adopted to guide users to change their electricity consumption habits for participation in the demand response, and a demand response model is established. Then, particle swarm optimization(PSO)is used with the aim of minimizing the operation cost of the microgrid to achieve economic dispatching of the microgrid. This considers power balance equation constraints, unit operation constraints, energy storage constraints, and heat storage constraints. Finally, the simulation results show the improved level of photoelectric consumption using the proposed scheme and the economic benefits of the microgrid.展开更多
Accurate state estimation is critical to wide-area situational awareness of smart grid.However,recent research found that power system state estimators are vulnerable to a new type of cyber-attack,called false data in...Accurate state estimation is critical to wide-area situational awareness of smart grid.However,recent research found that power system state estimators are vulnerable to a new type of cyber-attack,called false data injection attack(FDIA).In order to ensure the security of power system operation and control,a hybrid FDIA detection mechanism utilizing temporal correlation is proposed.The proposed mechanism combines Variational Mode Decomposition(VMD)technology and machine learning.For the purpose of identifying the features of FDIA,VMD is used to decompose the system state time series into an ensemble of components with different frequencies.Furthermore,due to the lack of online model updating ability in a traditional extreme learning machine,an OS-extreme learning machine(OSELM)which has sequential learning ability is used as a detector for identifying FDIA.The proposed detection mechanism is evaluated on the IEEE-14 bus system using real load data from an independent system operator in New York.Apart from detection accuracy,the impact of attack intensity and environment noise on the performance of the proposed method are tested.The simulation results demonstrate the efficiency and robustness of our method.展开更多
基金This work was supported in part by the National Key Research and Development Program of China(2018YFA0702200)the National Natural Science Foundation of China(61933005,61833008)+6 种基金the Natural Science Foundation of Jiangsu Province of China(BK20220395)the Leading Technology Foundation Research Project of Jiangsu Province(BK20202011)the Natural Science Foundation of Jiangsu Universities(22KJB470024)Jiangsu Provincial Key Research and Development Program(BE2020001)Natural Science Foundation of Hebei Province of China(E2020203139)Natural Science Foundation of Nanjing University of Posts and Telecommunications(NY222032)the National Research Foundation of Korea(2020R1A2B5B02002002).
文摘Nowadays,the microgrid cluster is an important application scenario for energy trading.In trading,one of the most important research directions is the issue of pricing.To determine reasonable pricing for the microgrid cluster,data communication is used to create the cyber-physical system(CPS),which can improve the observability of microgrids.Then,the following works are carried out in the CPS.In the physical layer:1)Regarding trading between microgrids and the load,based on the generalized game theory,an optimal pricing strategy is proposed,which takes into account the interactive relationships among microgrids and transforms the pricing problem into a Nikaido-Isoda function to obtain the optimal prices conveniently;2)Regarding peer-to-peer trading between two microgrids,based on evolutionary game theory and the penalty mechanism,the optimal sale price of the seller is selected with boundary rationality.In the cyber layer,regarding the communication interruption issue existing in pricing(i.e.,the game process),based on the principle of matching the performance of the path with the importance degree of the data,a dynamic regulating method of paths is proposed,i.e.,adopting a new path to re-transmit the interrupted data to the destination.Finally,the effect of the proposed strategies is verified by case studies.
基金supported by the key projects of the National Natural Science Foundation of China (No.61833008,No.61573300)Jiangsu Provincial Natural Science Foundation of China (No.BK20171445)Key Research and Development Plan of Jiangsu Province (No.BE2016184)。
文摘A system combining photovoltaic power generation and cogeneration is proposed to improve the photoelectric absorption capacity. First, a time-of-use price strategy is adopted to guide users to change their electricity consumption habits for participation in the demand response, and a demand response model is established. Then, particle swarm optimization(PSO)is used with the aim of minimizing the operation cost of the microgrid to achieve economic dispatching of the microgrid. This considers power balance equation constraints, unit operation constraints, energy storage constraints, and heat storage constraints. Finally, the simulation results show the improved level of photoelectric consumption using the proposed scheme and the economic benefits of the microgrid.
基金supported by the National Natural Science Foundation of China under Grants.61573300,61833008Natural Science Foundation of Jiangsu Province under Grant.BK20171445Key R&D Program of Jiangsu Province under Grant.BE2016184.
文摘Accurate state estimation is critical to wide-area situational awareness of smart grid.However,recent research found that power system state estimators are vulnerable to a new type of cyber-attack,called false data injection attack(FDIA).In order to ensure the security of power system operation and control,a hybrid FDIA detection mechanism utilizing temporal correlation is proposed.The proposed mechanism combines Variational Mode Decomposition(VMD)technology and machine learning.For the purpose of identifying the features of FDIA,VMD is used to decompose the system state time series into an ensemble of components with different frequencies.Furthermore,due to the lack of online model updating ability in a traditional extreme learning machine,an OS-extreme learning machine(OSELM)which has sequential learning ability is used as a detector for identifying FDIA.The proposed detection mechanism is evaluated on the IEEE-14 bus system using real load data from an independent system operator in New York.Apart from detection accuracy,the impact of attack intensity and environment noise on the performance of the proposed method are tested.The simulation results demonstrate the efficiency and robustness of our method.
