State-Failure-Network Method And Its Application For The Cascading Failures In Power Systems

In the past decades,the cascading failures have brought about several large blackouts,which caused severe losses to society.As the interconnections between the power networks get tighter,the cascading failures are becoming of higher complexity and faster propagation.Thus,the analyses and mitigation of cascading failures have been attracting the attention from the researchers.In this thesis,the analyses,control and mitigation of cascading failures based on the simulated failure data are studied in depth.As for the theoretical research,the state-failure-network method is proposed.For the application of the proposed method,we study the identification of the critical components of the power systems and the optimizing of the measures to mitigate cascading failures.The identification of the critical components in the power systems is one of the important objectives of the cascading failure analyses.Up to now,the analyses based on the topological methods can reveal some vulnerabilities in the power systems,but they neglect the relationships between the cascading failures and lose the accuracy.The methods based on the simulation models can obtain decent accuracy,whereas the methods suffer from the problem of low computation efficiency.As the failure data generated by the simulations contain sufficient information of the cascading failures,the methods based on the failure data are supposed to be efficient and accurate,which are getting increasing attention.In this thesis,a data-based state-failure-network method is proposed.The state-failurenetwork can identify the critical overload failure components and critical hidden failure components,and upgrading the identified critical components can effectively mitigate the cascading failure risks of the power systems.Then,the state-failure-network is improved to achieve the calculation of cascading failure risks,and further evolved into the compound state-failure-network to consider multiple scenarios,which offers an efficient way to solve the planning and operation problems considering multiple scenarios and objectives.Main work of the thesis includes:(1)Proposing the data-based state-failure-network method.The state-failure-network is formed by the failure data.Then,the states and failures are given the values that are calculated according to statistics of the data.The calculated values quantify the relationships between the failures and the expected risk;thus,they can be used to identify the critical failures in the state-failure-network.Afterwards,the criticality indexes are calculated to identify the critical overloaded failure components of the power system.(2)Studying the applications of the state-failure-network on the risk assessments of the system operations.Firstly,the state-failure-network in(1)is improved.By linking the parameters in the power systems and those in the state-failure-network,the calculations of state-failure-network can assess the cascading failure risks.As the computation complexity of the calculations in the state-failure-network are much lower than that of the calculations in the cascading failure simulations,the state-failure-network can achieve quicker calculations of the blackout risks after the changes of the line capacities.(3)Improving the way to form the state-failure-network by searching the states,which can search sufficient hidden failures.After calculating the critical hidden failure indexes,the critical hidden failure components can be identified.Then,the relays of the critical components can be updated and the occurrence probabilities of the severe blackouts are remarkably reduced.In addition,the impacts of the upgrading can be accurately obtained by the calculation of the state-failure-network based on(2).(4)Proposing the compound state-failure-network to consider the multiple scenarios.The importance sampling technique is adopted,where the sampling weights are changed adaptively based on the characteristics of the sampled failure chains in scenarios,and the compound state-failure-network can be more efficiently formed.Hence,the compound state-failure-network can be used to efficiently solve the multi-objective optimization problems considering the economic requirements and safety requirements of the scenarios.