Research On Methods Of Protection Against Coordinated Multistage Transmission Line Attacks In Smart Grid

The smart grid plays an important role in daily life,which is one of the most complex networks in modern society.With the increase of connectivity in smart grid,local and remote generators can be dispatched mutually to meet their own high electric demands,which not only realizes a wide range of resource sharing and optimization,but also reduces outages of smart grid year by year.However,the high interconnectivity poses a threat to smart grid.Specifically,when a physical or cyber attack against a smart grid transmission line is launched,the smart grid will experience cascading failures,which may result large-scale power outages.As a result,various social production activities will be affected by large-scale power outages(e.g.,traffic paralysis).At that moment,any equipment that relies on electricity will be unavailable,which results in huge economic losses.When the power outage lasts too long,it will have serious negative social impact,and even pose a great threat to national security.Although such power outages do not take place very frequently,due to the existence of their extreme riskiness,they will lead to catastrophic consequences once accidents occur.Therefore,it is very necessary to identify key transmission lines that can cause smart grid cascading failures in an attack environment.Since coordinated multistage transmission line attacks can lead to larger negative impacts compared with a single-stage attack or a multistage attack without coordination,this thesis aims to identify the key transmission lines of the smart grid that can cause cascading failures under multistage coordinated attacks and optimizes the deployment of limited defense resources.To this end,this thesis first formulates a total generation loss maximization problem with the consideration of multiple attackers and multiple stages.Due to the large size of solution space,it is very challenging to solve the formulated problem.To overcome the challenge,this thesis reformulates the problem as a Markov game and design its components(e.g.,state,action,and reward).Next,this thesis proposes a scalable algorithm to solve the Markov game based on multi-agent deep reinforcement learning with prioritized experience replay,which can determine the optimal attacking transmission line sequences.Then,this thesis designs a defense strategy to decide the optimal defense transmission line set.Extensive simulation results show the effectiveness of the proposed algorithm and the designed defense strategy.To be specific,in the IEEE 118 bus,compared with the defenseless scheme and the random defense scheme,the optimal defense strategy designed under coordinated multistage transmission line attacks can reduce the loss of power generation by 17.85% and 11.96%,respectively.In the IEEE 300 bus,compared with the defenseless scheme and the random defense scheme,the optimal defense strategy designed under coordinated multistage transmission line attacks can reduce the loss of power generation by 20.14% and 18.49%,respectively.Finally,this thesis makes a brief summary and points out future research directions.