A coordinated planner-disaster-risk-averse-planner investment model for enhancing the resilience of integrated electric power and natural gas networks

Aldarajee, Ammar H.M.; Hosseinian, Seyed Hossein; Vahidi, B.; Dehghan, Shahab

doi:10.1016/j.ijepes.2020.105948

Cited by 44 publications

(16 citation statements)

References 33 publications

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“…In [9], a strategy based on IGDT technique was introduced to facilitate decision making for distribution system planners upon the occurrence of natural disasters. In [10], a tri-level planner-disaster-risk-averseplanner model was introduced for planning in integrated natural gas and power networks exposed to extreme disasters. That work utilizes IGDT optimization technique to improve the resilience of the integrated system under extreme events.…”

Section: Indices Dmentioning

confidence: 99%

A Stochastic Planning Model for Improving Resilience of Distribution System Considering Master-Slave Distributed Generators and Network Reconfiguration

et al. 2021

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The recent experiences of extreme weather events highlight the significance of boosting the resilience of distribution systems. In this situation, the resilience of distribution systems planning leads to an efficient solution for protecting the system from these events via line hardening and the installation of distributed generators (DGs). For this aim, this study presents a new two-stage stochastic mixed-integer linear programming model (SMILP) to hedge against natural disaster uncertainty. The first stage involves making investment decisions about line hardening and DG installation. Then, in the second stage, the dynamic microgrids are created according to a master-slave concept with the ability of integrating distributed generators to minimize the cost of loss of load in each uncertain outage scenario. In particular, this paper presents an approach to select the line damage scenarios for the SMILP. In addition, the operational strategies such as load control capability, microgrid formation and network reconfiguration are integrated into the distribution system plans for resilience improvement in both planning and emergency response steps. The simulation results for an IEEE 33-bus test system demonstrate the effectiveness of the proposed model in improving disaster-induced the resilience of distribution systems.

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Section: Indices Dmentioning

confidence: 99%

A Stochastic Planning Model for Improving Resilience of Distribution System Considering Master-Slave Distributed Generators and Network Reconfiguration

et al. 2021

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“…[17] Presents a decomposition‐based method for effectively solving the DAD model in interdependent systems. Extremely random features of natural events led to an Information Gap Decision Theory (IGDT) based generation and transmission expansion planning (GTEP) model for robustly improving the resilience of integrated electric power and natural gas systems [18]. In terms of the type of event, DAD models are robust methods that generally have been used in the references to increase resilience against intentional events.…”

Section: Introductionmentioning

confidence: 99%

A two‐stage simulation‐based framework for optimal resilient generation and transmission expansion planning

Firoozjaee

Sheikh‐El‐Eslami

2022

IET Generation Trans & Dist

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This paper presents a two‐stage resilient framework for generation and transmission expansion planning that profits static and dynamic models. The first stage problem finds the generation and transmission expansion results without considering extreme events. Given the planned power system, in the second stage, a simulation‐based method is employed to accurately model the effects of the severe events and measure the expected demand not served. The proposed framework updates the formulation of the planning problem to efficiently search for a new expansion plan resulting in higher resilience levels. This paper uses the maximizing social welfare in the planning model to find the optimal result. Also, the effect of maximizing social welfare in updating the formulation of the planning problem is investigated. In this case, the planning problem is a bi‐level problem that using the primal‐dual formulation leads to a single‐level problem called a mathematical program with equilibrium constraints. After the linearization, the planning problem becomes a mixed‐integer linear programming problem. The planning model profits from reinforced transmission lines to improve power system resilience. The proposed framework is evaluated on 4‐bus, 6‐bus, and 118‐bus systems. According to the results, the proposed method with a low additional cost boosts power system resilience.

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“…As an example focused on the resiliency of the integrated electric power and natural gas networks, a tri‐level resilience‐constrained planning model is introduced in Ref. 6 The work of Ref. 6 aims at enhancing the resiliency of the coupled energy network under extreme events affecting all production and transportation facilities.…”

Section: Introductionmentioning

confidence: 99%

“…6 The work of Ref. 6 aims at enhancing the resiliency of the coupled energy network under extreme events affecting all production and transportation facilities. Besides, a bi‐level, multi‐objective, and bi‐directional planning model is presented in Ref.…”

Section: Introductionmentioning

confidence: 99%

“…4,10,17,18. However, this review article categorizes diverse resiliency enhancement methods and thoroughly discusses each category. Different techniques to characterize low‐frequency/high‐frequency uncertain parameters in resiliency study of power systems, as uncertain parameters play a key role in power system resiliency evaluation and planning 5‐7 . To the best of the authors' knowledge, there is no paper in the literature that reviews different techniques characterizing uncertain parameters in the resiliency studies of power systems.…”

Section: Introductionmentioning

confidence: 99%

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A critical reviewon definitions, indices, and uncertainty characterizationin resiliency‐orientedoperation ofpower systems

Izadi

Hosseinian

Dehghan

et al. 2020

Int Trans Electr Energ Syst

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A coordinated planner-disaster-risk-averse-planner investment model for enhancing the resilience of integrated electric power and natural gas networks

Cited by 44 publications

References 33 publications

A Stochastic Planning Model for Improving Resilience of Distribution System Considering Master-Slave Distributed Generators and Network Reconfiguration

A Stochastic Planning Model for Improving Resilience of Distribution System Considering Master-Slave Distributed Generators and Network Reconfiguration

A two‐stage simulation‐based framework for optimal resilient generation and transmission expansion planning

A critical reviewon definitions, indices, and uncertainty characterizationin resiliency‐orientedoperation ofpower systems

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