Study On Optimization Strategy Of Disaster Prevention And Emergency Of Power System Under Extreme Weather

The basic reason for the blackout caused by extreme natural disasters is that the existing design standards of power facilities could not withstand the increasing natural disasters.Therefore,in order to enhance the power supply capability and disaster resistance ability of power systems under extreme natural disasters,it is necessary to identify and reinforce important components in power system before disasters occur.While emergency power resources could be used to supply power to important power users in the area where power supply is not reserved after disasters,reducing the losses of power system blackouts to social and economic development.Therefore,optimization strategies of disaster prevention and emergency of power system under extreme weather are proposed in this thesis,considering identification of critical lines,planning of backbone grid and optimal scheduling of emergency power sources.A single evaluation index is utilized to identify critical lines in most existing studies,and the influence of various factors on critical lines identification could not be considered comprehensively.A multi-dimensional identification method of critical lines in regional power system under typhoon conditions is proposed,with the location of transmission lines in the network topology structure,the operation state of power systems,the economic loss of the lines’fault,and the influence of the lines’ parameter and external environment on the identification results considered.The optimal combination weight model and the modified radar chart method are utilized to determine the importance degree of the line.The simulation results show that the proposed method can consider various factors in the identification of critical lines comprehensively and better reflect the importance degree of the lines under typhoon conditions in the power systems.Then,a multi-objective planning model for anti-disaster backbone grid considering economics and network frame performance is proposed based on the identification results of critical lines.With the guarantee rate of the load requirements,security operation constraints of the power system and connectivity of the network topology satisfied.The multi-objective planning model are constructed for maximizing economics,resilience and network survivability.The graph repair strategy is utilized in comprehensive learning particle swarm optimization algorithm,and the mixed strategy Nash equilibrium are adopted to extract the best backbone grid.The numerical results of a regional power grid in Guangdong shows that the proposed model can provide a reasonable backbone network of the power system to formulate disaster prevention and emergency strategies.Considering the lines contained in the anti-disaster backbone grid are limited and many loads are still not been supplied with electricity after the disaster,an optimal scheduling method for emergency power sources are proposed to guarantee continuous power supply for important power users.The chance-constrained programming model for optimal scheduling of emergency power sources for disaster prevention,which aims at minimizing the total outage loss of important power users,are constructed with the uncertainties in the process of emergency power sources scheduling in actual power system considered.The simulation results verify that the proposed method can distribute emergency power supply for disaster prevention reasonably and reduce power outage losses.To sum up,the identification of critical lines and planning of backbone grids in regional power systems before disasters can provide technical guidance for wind-proof reinforcement of power system.It is not only conducive to reducing the probability of blackouts,but also help to speed up the recovery of power supply after disasters.The optimal scheduling of emergency power sources in power system after disasters,which could be used as a supplement to the disaster prevention strategies before disasters,is of great significance to reduce the losses caused by blackouts.