Power system risk assessment using a hybrid method of fuzzy set and Monte Carlo simulation

Li, Wenyuan; Zhou, Jiaqi

doi:10.1109/pes.2009.5275942

Cited by 41 publications

(73 citation statements)

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“…A new approach to incorporate the fuzzy load model in system reliability assessment has been presented in [22]. Reference [10] presented a method that combines fuzzy and probabilistic techniques. A fuzzy membership function with a probabilistic mean value is developed to model outage parameters, whereas a fuzzy representation for the peak load with the probability distribution for a load curve is developed to model the system load.…”

Section: Fuzzy Set Applications In Faulted Power Systemsmentioning

confidence: 99%

“…A triangle membership function of repair time (hours per failure) can be easily created with the point and interval estimates [10,23], as can be seen in Fig. 1.…”

Section: Fuzzy Modeling Of Repair Timementioning

confidence: 99%

“…The membership function equals 1 for the estimated r. The significant level a is always a small value such as 0.05 [7,10,12] and half of a is located at each of the two bounds in t-distribution.…”

Section: Fuzzy Modeling Of Repair Timementioning

confidence: 99%

“…The most basic feature of probabilistic reliability evaluation is the modeling of stochastic factors in power systems, including random outages of system components and uncertain variation of loads. Combinations of likelihoods and consequences of random outage events create the indices that represent the systems risk [10].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Canizes

Soares

Vale

et al. 2012

Energy

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a b s t r a c tThis paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system.The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment's effect on the transmission network.A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

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Section: Fuzzy Set Applications In Faulted Power Systemsmentioning

confidence: 99%

“…A triangle membership function of repair time (hours per failure) can be easily created with the point and interval estimates [10,23], as can be seen in Fig. 1.…”

Section: Fuzzy Modeling Of Repair Timementioning

confidence: 99%

Section: Fuzzy Modeling Of Repair Timementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Canizes

Soares

Vale

et al. 2012

Energy

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“…In [29], a multi objective probabilistic risk index is proposed to capture the likelihood and consequences of events. Fuzzy and Monte Carlo simulation based hybrid technique is proposed in [30] for the assessment of power system risk. Multiobjective optimization based algorithm is presented in [31] for the active distribution network planning, taking into account uncertainties in DG and the demand response.…”

Section: Introductionmentioning

confidence: 99%

Steady-state security in distribution networks with large wind farms

Jayaweera

Islam

2014

J. Mod. Power Syst. Clean Energy

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Aging network assets, forced and unforced outages, and the way the networks are operated in a deregulated market are of significant concerns to integrate large wind farms in a distribution network. In many cases, the constrained network capacity is a potential barrier to the large-scale integration of wind power. This paper probabilistically assesses the steady-state security in a distribution network in the presence of large wind farms. The approach incorporates active distribution network operating conditions, including intermittent power outputs, random outages, demand fluctuations, and dynamic interactions and exchanges, and then assesses the steady state security using Monte Carlo simulation. A case study is performed by integrating large wind farms into a distribution network. The results suggest that intermittent outputs of large wind farms in a distribution network can impact the steady-state security considerably. However, the level of impact of wind farms does not necessarily correlate with the installed capacity of them.

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A study of reliability assessment and topology similarity: Methodology, relationship, and applications

Tang

et al. 2019

Int Trans Electr Energ Syst

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Summary This paper attempts to investigate the relationship between topology and reliability of a distribution network associated with a singular value sequence (SVS) to accurately represent the crucial features of the distribution network topology, in which a novel algorithm called topology similarity analysis (TSA) is proposed for the first time and adopted to calculate the reliability indices of the distribution networks. Under such framework, SVS is treated as a similarity index that constructs a standard database of distribution network topology. Moreover, TSA outperforms other typical algorithms used in distribution network reliability assessment with a lower calculation costs and higher efficiency. Two case studies, eg, standard IEEE 33‐bus system and large‐scale practical 148‐bus system, are carried out at first to evaluate the effectiveness of the proposed approach. Then, TSA incorporated with splitting method is applied in the 148‐bus case. Simulation results demonstrate that TSA is 2 to 2000 times faster than that of other typical algorithms. Besides, the overall calculation time of TSA just grows insignificantly as the scale of the distribution network increases, together with a guaranteed less than 0.005% precision error.

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Power system risk assessment using a hybrid method of fuzzy set and Monte Carlo simulation

Cited by 41 publications

References 0 publications

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Steady-state security in distribution networks with large wind farms

A study of reliability assessment and topology similarity: Methodology, relationship, and applications

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