Research On The Planning And Restoration Of Resilient Distribution System To Hedge Against Nature Disasters

In recent decades,the power grid has frequently encountered extreme natural disasters such as the typhoon and flood.Especially,power distribution systems are vulnerable to natural disasters due to the fragile facilities,radial topology and limited back-up resources.However,the reliability,which is wildly used in power distribution systems,can deal with the "high probability,low impact" events,but ignores the extreme natural disasters with the characteristic of "high impact,low probability".Under this background,the concept of resilience is proposed.The preparedness before the extreme event and the restoration after the extreme event are required for the resilient distribution system.Specifically,the resilient planning can improve the resilience of distribution systems via line hardening and emergency resource allocation,and the resilient restoration can reduce the blackout costs by coordinating the resource dispatch with the sequential recovery of distribution systems.However,the current study on the resilient planning and restoration is still in the initial stage,where the related research is not sufficient and the modeling methods are absent.In particular,there are several gaps to be bridged:1)There is a lack of resilience indices to assess the planning and restoration methods;2)The coordination between the flexible dispatch of emergency resources and the sequential restoration of distribution systems is not modeled comprehensively;3)As for the conventional resource planning in distribution systems,such as the line hardening and stationary diesel generator allocation,there is no sufficient research on the coordination between the pre-event planning and the post-event restoration;4)As for the flexible resource planning in distribution systems,such as the mobile emergency generator allocation,the multi-stage coordination including the pre-event planning,the preventive response and the post-event restoration is not well established.To bridge these gaps,the main contributions of this dissertation are listed as follows:1)This dissertation proposes a methodology for fast resilience assessment of distribution systems with a non-simulation-based method,which can significantly improve the assessment accuracy and computational efficiency.First,a probabilistic metric is proposed to assess the system resilience against extreme events,which quantifies the system performance starting from the pre-event stage to the post-event stage.Then,a mixed-integer linear programming is proposed to model the energization paths(EPs)with binary decision variables.Subsequently,the resilience metric-related probability events are built using the EPs.Last,the probabilistic resilience metric is explicitly expressed based on the total probability formula,conditional probability formula and EP-topology simplification methods.In the proposed method,the topology evolution along with the system degradation,restoration(part healed)and recovery(all healed)is characterized with a non-simulation-based method,rather than the multiple scenarios in traditional methods.The numerical tests on the IEEE 123-node distribution system validate the effectiveness of the proposed method.2)This dissertation proposes a novel planning method to improve the resilience of distribution systems by line hardening and backup generator allocation,where the pre-event planning and post-event restoration can be properly coordinated.A multi-disaster-scenario based distributionally robust planning model is proposed to hedge against two types of natural disaster-related uncertainties:random offensive resources(ORs)of various natural disasters,and random probability distribution of line outages(PDLO)that are incurred by a certain natural disaster.The OR uncertainty is represented by the defined probability-weighted scenarios with stochastic programming,and the PDLO uncertainty is modeled as the moment based ambiguity sets.Then,the equivalent reformulation of the original MDS-DRM is first derived to eliminate the PDLO-related variables,and the reformulation problem is solved by the proposed primal cut based decomposition method to improve the computational efficiency of the proposed model.Finally,Simulation results are demonstrated for IEEE 13-node,33-node and 135-node distribution systems to validate the effectiveness of the proposed method in enhancing the disaster-induced network resilience.3)This dissertation proposes a novel three-stage stochastic planning model is proposed for mobile emergency generator allocation in resilient distribution systems,with the integration of planning stage(PLS),preventive response stage(PRS)and emergency response stage(ERS).Moreover,the nonanticipativity constraints are considered to guarantee that the decisions in each stage should depend on the current realizations of uncertainties.Specifically,in the PLS,the intensity uncertainty(IU)of disasters and the outage uncertainty(OU)incurred by a given disaster are considered with probability-weighted scenarios for the effective MEG allocation.Then,with the IU revealing in the PRS,the MEGs are pre-positioned with the consideration of OU.It is noted that the pre-position decisions should only correspond to the IU realizations,according to nonanticipativity constraints.Last,with the further realizations of OU in the ERS,the MEGs are re-routed from the pre-positioned location to the target location,and the provisional microgrids can be formed to restore critical loads.The proposed planning model can be large in size due to multiple scenarios.Therefore,the progressive hedging algorithm(PHA)is customized to reduce the computational burden.The simulations results based on 13 and 123 node distribution systems show the effectiveness of the proposed model and justify the superiority over the two-stage model.4)This dissertation proposes a sequential disaster recovery model for distribution systems with co-optimization of maintenance and restoration crew dispatch.To efficiently restore electricity customers from a large-scale blackout,we propose a novel mixed-integer linear programing model for the optimal disaster recovery of power distribution systems.In the proposed recovery scheme,the maintenance crews(MCs)are scheduled to repair damaged components,and the restoration crews(RCs)are dispatched to switch on the manual switches.Then,the MC and RC dispatch models are integrated into the disaster recovery scheme,which will generate an optimal sequence of control actions for distributed generation,controllable load,and re-mote/manual switches.Besides,to address the time scale related challenges in the model formulation,the technical constraints for system operation are investigated in each energization step rather than time step,hence the co-optimization problem is formulated as an "event-based" model with variable time steps.Consequently,the disaster recovery,MC dispatch and RC dispatch are properly co-operated,and the whole distribution systems can be re-stored step by step.Last,the effectiveness of the co-optimization model is validated in the modified IEEE 123 bus test distribution system.