Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve...Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.展开更多
As the number of power terminals continues to increase and their usage becomes more widespread,the security of power systems is under great threat.In response to the lack of effective trust evaluation methods for term...As the number of power terminals continues to increase and their usage becomes more widespread,the security of power systems is under great threat.In response to the lack of effective trust evaluation methods for terminals,we propose a trust evaluation model based on equipment portraits for power terminals.First,we propose an exception evaluation method based on the network flow order and evaluate anomalous terminals by monitoring the external characteristics of network traffic.Second,we propose an exception evaluation method based on syntax and semantics.The key fields of each message are extracted,and the frequency of keywords in the message is statistically analyzed to obtain the keyword frequency and time-slot threshold for evaluating the status of the terminal.Thus,by combining the network flow order,syntax,and semantic analysis,an equipment portrait can be constructed to guarantee security of the power network terminals.We then propose a trust evaluation method based on an equipment portrait to calculate the trust values in real time.Finally,the experimental results of terminal anomaly detection show that the proposed model has a higher detection rate and lower false detection rate,as well as a higher real-time performance,which is more suitable for power terminals.展开更多
The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection an...The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection and its convergence to local optimal solutions.To overcome these limitations,an improved KFCM algorithm with adaptive optimal clustering number selection is proposed in this paper.This algorithm optimizes the KFCM algorithm by combining the powerful global search ability of genetic algorithm and the robust local search ability of simulated annealing algorithm.The improved KFCM algorithm adaptively determines the ideal number of clusters using the clustering evaluation index ratio.Compared with the traditional KFCM algorithm,the enhanced KFCM algorithm has robust clustering and comprehensive abilities,enabling the efficient convergence to the global optimal solution.展开更多
基金supported by the Science and Technology Project of State Grid Shanxi Electric Power Research Institute:Research on Data-Driven New Power System Operation Simulation and Multi Agent Control Strategy(52053022000F).
文摘Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.
基金supported by the National Key Research and Development Program of China(No.2021YFB2401200)。
文摘As the number of power terminals continues to increase and their usage becomes more widespread,the security of power systems is under great threat.In response to the lack of effective trust evaluation methods for terminals,we propose a trust evaluation model based on equipment portraits for power terminals.First,we propose an exception evaluation method based on the network flow order and evaluate anomalous terminals by monitoring the external characteristics of network traffic.Second,we propose an exception evaluation method based on syntax and semantics.The key fields of each message are extracted,and the frequency of keywords in the message is statistically analyzed to obtain the keyword frequency and time-slot threshold for evaluating the status of the terminal.Thus,by combining the network flow order,syntax,and semantic analysis,an equipment portrait can be constructed to guarantee security of the power network terminals.We then propose a trust evaluation method based on an equipment portrait to calculate the trust values in real time.Finally,the experimental results of terminal anomaly detection show that the proposed model has a higher detection rate and lower false detection rate,as well as a higher real-time performance,which is more suitable for power terminals.
基金supported by the Planning Special Project of Guangdong Power Grid Co.,Ltd.:“Study on load modeling based on total measurement and discrimination method suitable for system characteristic analysis and calculation during the implementation of target grid in Guangdong power grid”(0319002022030203JF00023).
文摘The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection and its convergence to local optimal solutions.To overcome these limitations,an improved KFCM algorithm with adaptive optimal clustering number selection is proposed in this paper.This algorithm optimizes the KFCM algorithm by combining the powerful global search ability of genetic algorithm and the robust local search ability of simulated annealing algorithm.The improved KFCM algorithm adaptively determines the ideal number of clusters using the clustering evaluation index ratio.Compared with the traditional KFCM algorithm,the enhanced KFCM algorithm has robust clustering and comprehensive abilities,enabling the efficient convergence to the global optimal solution.
