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

Agriculture plays a central role in maintaining food security and achieving sustainable development for human society. It is a challenge for the agricultural sector to mitigate greenhouse gas (GHG) emissions and maintain agricultural production. However, dual-level uncertainties exist in the processes of agricultural GHG accounting and emission reduction management. In this research, an integrated approach for identifying adaptation strategies in agricultural GHG emission reduction management was developed through incorporating life cycle analysis (LCA) of agricultural production into a general mathematical programming model. This approach strengthened the applicability of LCA and the comprehensiveness of programming models in generating agricultural adaptive actions under different GHG emission restriction targets. Also, dual-level uncertainties of LCA and adaptation management can be effectively addressed. A case study was proposed to illustrate application of the approach in Dalian City, China. The results indicated that farming patterns in eight districts would change significantly. The total area of maize fields would account for the primary proportion (i.e., 40-45 %) in its agricultural sector. Rice, peanut and cabbage fields would be the minor contributors in terms of GHG emissions. In addition to effective rainfall (i.e., [156, 259] mm/ha), a certain amount of water would be supplied for agricultural irrigation to maximize the city's agricultural yields. Compared with other agricultural crops, rice fields would need the largest amount of irrigation water (i.e., [153.72, 277.98] Mt) to meet the requirements of local government plans.

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“…; x AE n Þ. These interval LCI data can reflect the extent of uncertainty Canizes et al 2012;Markowski and Siuta 2014).…”

Section: Uncertainty Analysis Of Lca Results (First-level Uncertainty)mentioning

confidence: 98%

Adaptation strategies for mitigating agricultural GHG emissions under dual-level uncertainties with the consideration of global warming impacts

Yue

Cai

et al. 2016

Stoch Environ Res Risk Assess

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“…For a given significant level the failure rate falls into the random confidence interval (4) with the probability of [18,[19][20][21]: (4) where is the statistical number of failures within the time in the data samples. The two bounds of the failure rate can be estimated by equations (5-7) [18]:…”

Section: B Fuzzy Set Functions For Andmentioning

confidence: 99%

“…is the is the point estimate of repair time. A triangle membership function for repair time (in hours per failure) can be easily created using the point and interval estimates [18,[19][20][21].…”

Section: B Fuzzy Set Functions For Andmentioning

confidence: 99%

Modified discrete PSO to increase the delivered energy probability in distribution energy systems

Canizes

Soares

Morais

et al. 2013

2013 IEEE Computational Intelligence Applications in Smart Grid (CIASG)

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This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

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“…Generally speaking, fuzzy reliability based on CFA has covered a wide variety of subjects in power systems [8,9,[11][12][13][14][15][16]. To provide secure operation of a power system, the ability of its protection systems must be investigated in depth and it is well-accepted that the reliability of a power system [18,19] is strongly related to the reliability of its relevant protection systems [20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…The reliability concepts have extensively been incorporated into fuzzy computations in numerous cases [11][12][13][14][15]. It is well-accepted that a fuzzy perspective offers distinct advantages concerning the reliability issues; it considers the uncertainty of input data (failure rates, repair rates and so on).…”

Section: Introductionmentioning

confidence: 99%

The reliability investigation considering data uncertainty; an application of Fuzzy Transformation Method in substation protection

Aghili

Hajian-Hoseinabadi

2014

International Journal of Electrical Power & Energy Systems

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

Cited by 36 publications

References 30 publications

Adaptation strategies for mitigating agricultural GHG emissions under dual-level uncertainties with the consideration of global warming impacts

Adaptation strategies for mitigating agricultural GHG emissions under dual-level uncertainties with the consideration of global warming impacts

Modified discrete PSO to increase the delivered energy probability in distribution energy systems

The reliability investigation considering data uncertainty; an application of Fuzzy Transformation Method in substation protection

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