A Fast and Scalable Transmission Switching Algorithm for Boosting Resilience of Electric Grids Impacted by Extreme Weather Events

Hussain, Tanveer; Suryanarayanan, Siddharth; Hansen, Timothy M.; Alam, S M Shafiul

doi:10.1109/access.2022.3179470

Cited by 6 publications

(6 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This explicit consideration of switching actions is the minimisation of the Euclidean distance w l (z * l − 𝛼 l ) 2 between the binary variables z l and the base topology that considers all lines as available 𝛼 |Ω| l ∈ {1} |Ω| , where w l is a weighting parameter. The physical constraints that ensure the capacity of power systems are met are in Equations ( 2)-( 5) and the big-M method in Equations ( 6) and (7) ensures that when a line is switched off (z l = 0), the line flow constraints on other lines that share same bus connections remain active.  in Equation (8) sets an upper bound for the number of transmission lines that can be switched at all times.…”

Section: Heuristic Approachesmentioning

confidence: 99%

“…The KNN heuristic is based on Johnson [7] where a mapping exists between vectors of OCs X and the known DC optimal switching instances

f(X)

resulting in a set

\Omega ^S

of TS solved instances. The KNN heuristic trains on the training data

\Omega ^S

, and in real‐time chooses k instances that are similar to a candidate OC X based on the Euclidean distance or

l_{\infty }

‐norm.…”

Section: Heuristic Approachesmentioning

confidence: 99%

“…while satisfying the constraints in Equations ( 2)- (7). Solving this optimisation returns the nearest feasible topology Y * r+1 in the event that the TS solution obtained Y r+1 is not feasible.…”

Section: Proposed Rbfnn Heuristicmentioning

confidence: 99%

“…Importantly the short-term operations savings can be up to 25% of dispatch costs on the IEEE 118-bus system [1]. Other use cases of TS in power systems operations include reducing operating costs in a security-constrained unit commitment formulation that considers circuit breaker reliabil-ity [6] and boosting resilience of power grids to extreme weather events [7].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Real‐time transmission switching with neural networks

Bugaje

Cremer

Štrbac

2022

IET Generation Trans & Dist

View full text Add to dashboard Cite

The classical formulation of the transmission switching problem as a mixed-integer problem is intractable for large systems in real-time control settings. Several heuristics have been proposed in the past to speed up the computation time, which only limits the number of switchable lines. In this paper, a real-time switching heuristic based on neural networks that provides almost instantaneous switching actions, are presented. The findings are shown on case studies of the IEEE 118-bus test system, and the results show that the proposed heuristic is robust to out of distribution data. Additionally, the proposed heuristic has significant computational savings while all other performance metrics like accuracy are similar to state-of-the-art machine learning methods proposed for transmission switching.

show abstract

Section: Heuristic Approachesmentioning

confidence: 99%

“…The KNN heuristic is based on Johnson [7] where a mapping exists between vectors of OCs X and the known DC optimal switching instances

f(X)

resulting in a set

\Omega ^S

of TS solved instances. The KNN heuristic trains on the training data

\Omega ^S

, and in real‐time chooses k instances that are similar to a candidate OC X based on the Euclidean distance or

l_{\infty }

‐norm.…”

Section: Heuristic Approachesmentioning

confidence: 99%

Section: Proposed Rbfnn Heuristicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Real‐time transmission switching with neural networks

Bugaje

Cremer

Štrbac

2022

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…TS aware mixed-integer linear programming model is developed for multi-scenario transmission network expansion planning (TNEP) problem [23]. Moreover, TS is also used for LSR [24], [25], which is the main focus of this paper. Despite of all its advantages, TS is being used by industries on limited occasions [9], [26].…”

Section: Preliminaries a Transmission Switching (Ts)mentioning

confidence: 99%

Load Shed Recovery With Transmission Switching and Intentional Islanding Methods After (N-2) Line Contingencies

et al. 2022

Self Cite

View full text Add to dashboard Cite

Changing power system configuration may result in load shed recovery (LSR) because topology change can provide power flow control in meshed network. Some topologies may favor generation redispatch as compared to others and can eliminate line congestion which leads to LSR. One of the known methods for topology change is called transmission switching (TS) and research conducted in the past showed that TS is an effective means of mitigating load shedding. However, another method of topology control also exits and it is referred as intentional islanding (IIS). In this manuscript, we explore IIS as a potential solution for LSR. IIS based on generator coherency has been presented in literature for mitigating cascading failures. However, IIS has not been explored solely as a LSR mechanism. In this paper, we compare the LSR based on IIS with well known LSR algorithm based on TS. The comparison is performed for IEEE 39-bus system and IEEE 118-bus system. The results show that IIS has a potential to perform better than TS in terms of computational efficiency and LSR.INDEX TERMS Contingency analysis, load shed recovery, intentional islanding, transmission switching, topology control.

show abstract

The Role of Optimal Transmission Switching in Enhancing Grid Flexibility: A Review

et al. 2023

View full text Add to dashboard Cite

The integration of variable renewable energy sources (RES) into power grids has resulted in a more complex operating environment for power system operators (SO), necessitating the need for increased grid flexibility. This is crucial for utilities, as the cost-effective utilization of existing infrastructure is necessary, given the prolonged construction period and high investment costs associated with building new power delivery facilities. Under the umbrella of smart grid, optimal transmission switching (OTS) is a cost-effective transmission technology that can alleviate concerns related to network congestion, limited transmission capacity, and high penetration of renewables. OTS is a concept that is integrated into the optimal power flow (OPF) problem such that it provides SO the choice to temporarily switch one or more lines out of service from the network. OTS is shown in the literature to have economic benefits, reduce operational cost, relieve network congestion, serve as a corrective mechanism for reducing voltage violations, improve system reliability, and minimize system loss. Despite the significant attention given to OTS by researchers over the past decade, no extensive review paper exists on the topic in the literature. Therefore, this paper provides a state-of-the-art overview of the OTS problem. The concept of OTS is explained by approximating the alternating current OPF problem into a linear direct current OPF problem. Various alternative models of the OTS problem proposed in the literature are discussed. The paper also analyzes the interaction between OTS and other flexibility options such as Dynamic thermal rating (DTR), Energy storage systems (ESS), and RES. Furthermore, the paper presents the general framework and impact of the short-term OTS problem on long-term expansion planning problems. Finally, an extensive literature review on the impact of OTS on system reliability is provided.

show abstract

A Fast and Scalable Transmission Switching Algorithm for Boosting Resilience of Electric Grids Impacted by Extreme Weather Events

Cited by 6 publications

References 33 publications

Real‐time transmission switching with neural networks

Real‐time transmission switching with neural networks

Load Shed Recovery With Transmission Switching and Intentional Islanding Methods After (N-2) Line Contingencies

The Role of Optimal Transmission Switching in Enhancing Grid Flexibility: A Review

Contact Info

Product

Resources

About