Abstract
Recently, resilience studies have become an indispensable tool for sustainable operation of energy infrastructure. In line with the need, this study presents a mathematical model to enhance resilience level of power distribution systems against natural disasters. The model is designed as a three-stage algorithm according to system operators’ actions. The first stage schedules pre-event actions. At this stage, forecasts about the approaching disaster as well as fragility curves of system components are used to identify failure probability of system components. The failure probabilities are used to trip out the lines as much as possible to defensively operate the distribution network, and advantages of alternatives such as distributed energy resources and normally-open switches are taken to serve critical loads. The second stage is to monitor system operating conditions during the event and identify the status of system components. The third stage mainly focuses on scheduling post-event actions. At this stage, based on real data about different elements of the network, available alternatives are taken to restore as much critical load as possible. To evaluate performance of the model, it is applied to a distribution test system and the results are discussed in detail.
Highlights
In recent years, occurrence of catastrophic events in different countries has caused widespread outages in power systems
Failure probability of the lines is determined based on approaching event's severity and components’ fragility curves
An optimisation problem is run to obtain the optimal pre-disturbance network configuration such that system loads are served through less vulnerable paths
Summary
Occurrence of catastrophic events in different countries has caused widespread outages in power systems. Gao et al [1] have demonstrated that widespread installation of distributed generators (DGs) can effectively improve the resilience of distribution systems To achieve this goal, pre-hurricane resource allocation problem has been formulated as a mixedinteger stochastic non-linear program whose simulation results indicate effectiveness of the approach for restoring more critical load in post-event stage. The model optimises pre-event actions according to the forecasts about the approaching hazard and fragility curves of system components [16] At this stage, lines with high failure probability and flowing power are intentionally tripped out as much as possible, and advantages of distributed energy resources and potential manoeuvres in network configuration are taken to serve the total load.
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