Growing widespread outages in power systems caused by natural disasters have highlighted the nece... more Growing widespread outages in power systems caused by natural disasters have highlighted the necessity of applying defensive approaches with the goal of prompt service restoration. In this context, this paper proposes a stochastic model with the goal of optimally using proactive operational actions before the upcoming disturbance hits. The actions considered in this study include network reconfiguration and crew prepositioning. To take the effective actions, the model simulates probable damages caused by the events via a set of scenarios generated by Monte Carlo simulation method. The proposed model aims at minimizing the expected load curtailment caused by the event over the scenarios. To calculate the amount of load curtailments, potential post-disturbance actions are also considered in the model. The model is mathematically formulated in mixed integer linear programming (MILP) fashion which can be easily solved via available software packages. A standard distribution system with a realistic set of data is employed to validate the effectiveness of the proposed model.
Distribution System Resilience Enhancement via Mobile Emergency Generators
IEEE Transactions on Power Delivery, 2021
Natural calamities always have been a serious threat to energy systems. In this regard, this pape... more Natural calamities always have been a serious threat to energy systems. In this regard, this paper constitutes a stochastic mixed integer linear programming (SMILP) model to enhance the resilience of power distribution systems to deal with disastrous events. In particular, the proposed model is developed to enhance both survivability and restoration capability of distribution systems. In this regard, to increase the preparedness of the power distribution system, the system operator reconfigures the network by utilizing remote-control switches (RCSs), manual switches (MSs), and distributed generations (DGs) before the natural calamity hits. The proposed model contemplates the traveling time of crew teams to the MS sites in the transportation system in order to achieve the best switching sequence. In addition, it pre-positions the crews and mobile emergency generators (MEGs) in staging locations to hasten the likely post-disturbance operations. To do so, likely post-event operations are included in the model using the scenario generation technique. To validate the performance of the developed model a distribution system is employed. The results of simulations confirm the effectiveness of the proposed approach in declining the interruption of electric energy for customers.
Toward Operational Resilience of Smart Energy Networks in Complex Infrastructures
Advances in Intelligent Systems and Computing, 2020
Smart energy systems can mitigate electric interruption costs provoked by manifold disruptive eve... more Smart energy systems can mitigate electric interruption costs provoked by manifold disruptive events via making efforts toward proper pre-disturbance preparation and optimal post-disturbance restoration. In this context, effective contingency management in power distribution networks calls for contemplating disparate parameters from interconnected electric and transportation systems. This chapter, while considering transportation issues in power networks’ field operations, presents a navigation system for pre-positioning resources such as field crews and reconfiguring the network to acquire a more robust configuration in advance of the imminent catastrophe. Also, after the occurrence of the calamity, this navigator optimally allocates the resources to recover the devastating system. So, providing a coordination framework for manual field operation and automation system, this navigator takes a step from traditionally operated systems accommodation toward smart networks. During the contingency management process, there might be modifications in initial data due to the dynamic and time-varying condition of electric and transportation systems. Therefore, the mentioned navigator copes with a real-time problem of data-driven decision making in which, the decisions need to track online changes to the input data. Decision making by the navigation system in this environment is based on a mixed integer linear programming (MILP) optimization which is described in this chapter in detail.
Hardening Strategy to Boost Resilience of Distribution Systems via Harnessing a Proactive Operation Model
2019 Smart Grid Conference (SGC), 2019
Nowadays, large-scale power outages induced by ever-growing natural disasters are increasing at a... more Nowadays, large-scale power outages induced by ever-growing natural disasters are increasing at a galloping rate. In this regard, this paper aims at improving the resilience of power distribution systems in facing high impact low probability (HILP) events in the planning phase of the system. To this end, optimal switch placement along with the optimal distribution line hardening strategies is proposed to mitigate the repercussions of the natural calamities. So, decreasing the failure probability of the distribution lines alongside the optimal placement of remote-controlled switches (RCSs) to increase the maneuvering capability of the system, the system operator would be able to strengthen the system and cope with disastrous events. To do so, in this paper, a proactive strategy is used to simulate the operation of the system in confronting the HILP events. The proposed model implemented on a real 47-bus power distribution system and the efficacy of the model is approved by the simulation results in enhancing the resilience level of the system.
Sectionalizing switches are the main components of any restoration scheme in fault situations of ... more Sectionalizing switches are the main components of any restoration scheme in fault situations of power distribution systems. In this paper, customer outage costs reduction is aimed through the optimal simultaneous placement of manual and remote-controlled switches (RCSs). Network reconfigurations are constrained such that operational considerations like statutory ranges for voltage levels, lines' thermal capacities, and necessity of radial configuration be conserved. Total cost reduction is mathematically modeled in a mixed-integer linear programming (MILP) model that makes the global optimal solution accessible. The validity of the proposed model is evaluated on the IEEE 33-bus network. In this study, investment cost of switches and damage cost of customers are considered as two objectives where Pareto front is derived for decision-making purposes.
To improve the resilience of electric distribution systems, this paper proposes a stochastic mult... more To improve the resilience of electric distribution systems, this paper proposes a stochastic multi-period mixed-integer linear programming model that determines where to underground distribution lines and how to coordinate mobile generators in order to serve critical loads during extreme events. The proposed model represents the service restoration process using the linearized DistFlow approximation of the AC power flow equations as well as binary variables for the undergrounding statuses of the lines, the configurations of switches, and the locations of mobile generators during each time period. The model also enforces a radial configuration of the distribution network and considers the transportation times needed to reposition the mobile generators. Using an extended version of the IEEE 123-bus test system, numerical simulations show that combining the ability to underground distribution lines with the deployment of mobile generators can significantly improve the resilience of the power supply to critical loads.
Recently, resilience studies have become an indispensable tool for sustainable operation of energ... more 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 postevent 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.
Growing widespread outages in power systems caused by natural disasters have highlighted the nece... more Growing widespread outages in power systems caused by natural disasters have highlighted the necessity of applying defensive approaches with the goal of prompt service restoration. In this context, this paper proposes a stochastic model with the goal of optimally using proactive operational actions before the upcoming disturbance hits. The actions considered in this study include network reconfiguration and crew prepositioning. To take the effective actions, the model simulates probable damages caused by the events via a set of scenarios generated by Monte Carlo simulation method. The proposed model aims at minimizing the expected load curtailment caused by the event over the scenarios. To calculate the amount of load curtailments, potential post-disturbance actions are also considered in the model. The model is mathematically formulated in mixed integer linear programming (MILP) fashion which can be easily solved via available software packages. A standard distribution system with a realistic set of data is employed to validate the effectiveness of the proposed model.
Distribution System Resilience Enhancement via Mobile Emergency Generators
IEEE Transactions on Power Delivery, 2021
Natural calamities always have been a serious threat to energy systems. In this regard, this pape... more Natural calamities always have been a serious threat to energy systems. In this regard, this paper constitutes a stochastic mixed integer linear programming (SMILP) model to enhance the resilience of power distribution systems to deal with disastrous events. In particular, the proposed model is developed to enhance both survivability and restoration capability of distribution systems. In this regard, to increase the preparedness of the power distribution system, the system operator reconfigures the network by utilizing remote-control switches (RCSs), manual switches (MSs), and distributed generations (DGs) before the natural calamity hits. The proposed model contemplates the traveling time of crew teams to the MS sites in the transportation system in order to achieve the best switching sequence. In addition, it pre-positions the crews and mobile emergency generators (MEGs) in staging locations to hasten the likely post-disturbance operations. To do so, likely post-event operations are included in the model using the scenario generation technique. To validate the performance of the developed model a distribution system is employed. The results of simulations confirm the effectiveness of the proposed approach in declining the interruption of electric energy for customers.
Toward Operational Resilience of Smart Energy Networks in Complex Infrastructures
Advances in Intelligent Systems and Computing, 2020
Smart energy systems can mitigate electric interruption costs provoked by manifold disruptive eve... more Smart energy systems can mitigate electric interruption costs provoked by manifold disruptive events via making efforts toward proper pre-disturbance preparation and optimal post-disturbance restoration. In this context, effective contingency management in power distribution networks calls for contemplating disparate parameters from interconnected electric and transportation systems. This chapter, while considering transportation issues in power networks’ field operations, presents a navigation system for pre-positioning resources such as field crews and reconfiguring the network to acquire a more robust configuration in advance of the imminent catastrophe. Also, after the occurrence of the calamity, this navigator optimally allocates the resources to recover the devastating system. So, providing a coordination framework for manual field operation and automation system, this navigator takes a step from traditionally operated systems accommodation toward smart networks. During the contingency management process, there might be modifications in initial data due to the dynamic and time-varying condition of electric and transportation systems. Therefore, the mentioned navigator copes with a real-time problem of data-driven decision making in which, the decisions need to track online changes to the input data. Decision making by the navigation system in this environment is based on a mixed integer linear programming (MILP) optimization which is described in this chapter in detail.
Hardening Strategy to Boost Resilience of Distribution Systems via Harnessing a Proactive Operation Model
2019 Smart Grid Conference (SGC), 2019
Nowadays, large-scale power outages induced by ever-growing natural disasters are increasing at a... more Nowadays, large-scale power outages induced by ever-growing natural disasters are increasing at a galloping rate. In this regard, this paper aims at improving the resilience of power distribution systems in facing high impact low probability (HILP) events in the planning phase of the system. To this end, optimal switch placement along with the optimal distribution line hardening strategies is proposed to mitigate the repercussions of the natural calamities. So, decreasing the failure probability of the distribution lines alongside the optimal placement of remote-controlled switches (RCSs) to increase the maneuvering capability of the system, the system operator would be able to strengthen the system and cope with disastrous events. To do so, in this paper, a proactive strategy is used to simulate the operation of the system in confronting the HILP events. The proposed model implemented on a real 47-bus power distribution system and the efficacy of the model is approved by the simulation results in enhancing the resilience level of the system.
Sectionalizing switches are the main components of any restoration scheme in fault situations of ... more Sectionalizing switches are the main components of any restoration scheme in fault situations of power distribution systems. In this paper, customer outage costs reduction is aimed through the optimal simultaneous placement of manual and remote-controlled switches (RCSs). Network reconfigurations are constrained such that operational considerations like statutory ranges for voltage levels, lines' thermal capacities, and necessity of radial configuration be conserved. Total cost reduction is mathematically modeled in a mixed-integer linear programming (MILP) model that makes the global optimal solution accessible. The validity of the proposed model is evaluated on the IEEE 33-bus network. In this study, investment cost of switches and damage cost of customers are considered as two objectives where Pareto front is derived for decision-making purposes.
To improve the resilience of electric distribution systems, this paper proposes a stochastic mult... more To improve the resilience of electric distribution systems, this paper proposes a stochastic multi-period mixed-integer linear programming model that determines where to underground distribution lines and how to coordinate mobile generators in order to serve critical loads during extreme events. The proposed model represents the service restoration process using the linearized DistFlow approximation of the AC power flow equations as well as binary variables for the undergrounding statuses of the lines, the configurations of switches, and the locations of mobile generators during each time period. The model also enforces a radial configuration of the distribution network and considers the transportation times needed to reposition the mobile generators. Using an extended version of the IEEE 123-bus test system, numerical simulations show that combining the ability to underground distribution lines with the deployment of mobile generators can significantly improve the resilience of the power supply to critical loads.
Recently, resilience studies have become an indispensable tool for sustainable operation of energ... more 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 postevent 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.
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Papers by Babak Taheri