A methodology for reliability assessment of substations using fault tree and Monte Carlo simulation

Barbosa, Jair Diaz; Santos, Ricardo Caneloi dos; Romero, Jesus Franklin Andrade; Asano, Patrícia Teixeira Leite; Neto, Antonio V. Silva; Camargo, João Batista; Almeida, Jorge Rady de; Cugnasca, Paulo Sérgio

doi:10.1007/s00202-019-00756-2

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…This equation is obtained assuming that the distribution function is exponential and is calculated using the inverse transform method. So by calculating transition times from State 1 to all states from 2 to n, the shortest time associated with the jth state is selected and is determined as the residence time in State 1 [22][23][24][25][26]. This way, the model goes from State 1 to State n. This procedure is repeated for the whole simulation period.…”

Section: The Proposed Markov Modelmentioning

confidence: 99%

Evaluation of Power System Reliability Incorporating Protection System Miscoordination

Sabzebin

Noghabi

Mazlumi

2022

Preprint

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The operation of protection systems has a considerable impact on power system reliability. The main reason for cascading outages is protection system misoperation. Two leading causes of protection system misoperation are protection system failure and incorrect settings. The failure of any of its components of the protection system results in failure to operate or undesired tripping and incorrect settings of relays cause protection miscoordination. In this paper, an analysis of power system reliability regarding failure and incorrect settings of the protection system is paid. This paper proposes an eight-state Markov model for a transmission line and its protection system incorporating protection system miscoordination distingue from failure to operate and undesired trip. The situation of network lines in the period of simulation time has been determined by the sequential Monte Carlo method, and are calculated the reliability indices such as Loss of Load Probability (LOLP), Loss of Load Expectation (LOLE), Expected Energy Not Supplied (EENS), and Expected Frequency of Load Curtailment (EFLC). The proposed model is applied to a 6-bus IEEE RBTS network, and the reliability indices are calculated and compared from both perspectives to show the importance of the proposed model.

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Section: The Proposed Markov Modelmentioning

confidence: 99%

Evaluation of Power System Reliability Incorporating Protection System Miscoordination

Sabzebin

Noghabi

Mazlumi

2022

Preprint

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“…Analytical methods include (Todinov, 2007; Singh et al., 2018; Barbosa et al., 2019): State space method using Markov processes, where all possible system states are enumerated; consequently, this approach can be regarded as the most direct approach to calculating reliability indices (Singh et al., 2018). Network reduction method, where the serial and parallel elements of a system are reduced to a single equivalent element; hence the reliability of the reduced system equals the reliability of the initial system (Todinov, 2007).…”

Section: Background and Related Workmentioning

confidence: 99%

A variable neighborhood search simheuristic algorithm for reliability optimization of smart grids under uncertainty

Antoniadis

Cordy

Sifaleras

et al. 2021

Int Trans Operational Res

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A fundamental part of the self‐healing grid is reducing disturbances and automatically responding to problems. Toward this goal, smart grid operators would be of great use to ensure stability after a potential overload for a planning horizon, as the electrical values are unknown. To evaluate the robustness of the topology reconfiguration after a disturbance, like an overload, reliability analysis through simulation can be employed. However, the simulation approach we propose in this paper, except for the excessive time it consumes, cannot assure the quality of its solutions. To achieve a more robust configuration, we, additionally, propose a single‐stage stochastic program to optimize the grid topology configuration after a potential overload to ensure stability for the next day. We suggest a simheuristic approach based on a Variable Neighborhood Search metaheuristic to solve the above stochastic optimization problem. We evaluate the two approaches for this real‐world problem, together with Creos Luxembourg S.A., the leading grid operator in Luxembourg. We show that our method can quickly suggest countermeasures to operators facing potential overloading incidents, ensuring the smart grid's stability for the next day.

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“…Different simplification processes are defined for various cyber network topologies. Regarding the system state searching step, the Monte Carlo Simulation (MCS) is the most common used method applied by researchers [17] [18] [19] [20] [9]. The MCS has shown its high ability in reliability assessment of large power systems.…”

Section: Introductionmentioning

confidence: 99%

Smart Grids Reliability Assessment Using a Simplified Mapping Step

Gholami

Mohammadtaheri

Gholami³

2022

Preprint

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Reliability of the smart grids has always been an important factor considered by power system planners. Cyber network failures have significant impacts on the reliability of the smart grids as a cyber-physical system. The complexity of the reliability assessment of cyber-physical systems is significantly higher than traditional power systems due to interdependency between cyber and power network elements. A mapping step is applied to system states to address this interdependency in the reliability assessment task. This paper aims to lower the complexity and computational cost of reliability assessment in cyber-physical systems by proposing a simplified mapping step. The simplification steps are applied to various connection types between cyber components using a defined interconnection matrix based on the cyber network topology. The two-state reliability model probabilities are updated for each cyber element. The proposed method lowers the number of possible system states and computational cost significantly since the effects of some cyber networks are considered in the probability updating step. The proposed approach is applied to different cyber network topologies such as bus, ring, and redundant star in a microgrid. Loss of load probability and expected energy not supplied are calculated as the reliability indices of the system. The results reveal the efficiency of proposed method in reliability assessment of the cyber-physical system using remarkably decreased numbers of system states.

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A methodology for reliability assessment of substations using fault tree and Monte Carlo simulation

Cited by 8 publications

References 10 publications

Evaluation of Power System Reliability Incorporating Protection System Miscoordination

Evaluation of Power System Reliability Incorporating Protection System Miscoordination

A variable neighborhood search simheuristic algorithm for reliability optimization of smart grids under uncertainty

Smart Grids Reliability Assessment Using a Simplified Mapping Step

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