Simplified Cross-Entropy Based Approach for Generating Capacity Reliability Assessment

Carvalho, Leonel; Gonzalez-Fernandez, Reinaldo A.; Silva, Armando M. Leite da; Rosa, Mauro; Miranda, Vladimiro

doi:10.1109/tpwrs.2012.2213618

Cited by 34 publications

(20 citation statements)

References 22 publications

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“…5, which shows that the proposed method is more efficient than the CSMC method. Also, there is a plot hereafter showing the estimate of LOLE with respect to the number of simulation runs, which clearly illustrates the increased convergence speed of the proposed method (see Figs 6,8,10 and 12). It is worth mentioning that as the system failure event is rare in such a short T L , reliability metrics as LOLE obtained by the CSMC method need a huge number of simulation runs, for example, 100 000 in our numerical studies, to converge (Fig.…”

Section: Efficient Gain Studiesmentioning

confidence: 81%

“…It can be noted that, in order to solve (11) in the two stages, two stop criteria are defined to assist in simulating the needed system state transition paths, respectively: Criterion (1) hitting any system failure state, and Criterion (2) reaching the end of a specific lead time. For the sake of clarity, in the first simulation stage under Criterion (1), the duration of Γ k , T G k , should replace T L in (8) to update the relevant parameters. Thus, the resulting likelihood can be expressed as followŝ…”

Section: Ideas Underlining the Proposed Methodsmentioning

confidence: 99%

“…Nonetheless, both of these two sorts of techniques are confronted with a heavy simulation computational burden as a large number of system states must be sampled before the indices converge. Tremendous work has been devoted to the improvement of computational efficiency of Monte Carlo methods, especially for the non-sequential Monte Carlo method, such as that reported in [4,5,[8][9][10][11] and the references therein. Recently, an optimisation method proposed in [12] accelerates evaluation of the failure states of composite power system by eliminating redundant line flow constraints.…”

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confidence: 99%

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Adaptive sequential importance sampling technique for short‐term composite power system adequacy evaluation

Wang

Guo

2014

IET Generation, Transmission & Distribution

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The well-known sequential Monte Carlo simulation is a powerful tool to analyse short-term reliability of complicated composite power system. However, the corresponding computational burden is tremendous when applied to a highly reliable system. Aiming at improving the simulation efficiency, an adaptive importance sampling technology is proposed in this study. The proposed method, on the basis of component state duration sampling technique combined with cross-entropy method, is able to provide reliability evaluation of highly reliable non-homogeneous Markov system. The Weibull and lognormal distributions are considered to describe repair time of individual components comprising a system. Through the case studies conducted on a reinforced Roy Billinton reliability test system, it is validated that the proposed method is effective and of high efficiency and the efficiency gain against the crude sequential Monte Carlo simulation is robust to variation of load level and lead timescale. The proposed method is useful and efficient to timely monitor the system operating pressure under different lead timescales.

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Section: Efficient Gain Studiesmentioning

confidence: 81%

Section: Ideas Underlining the Proposed Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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Adaptive sequential importance sampling technique for short‐term composite power system adequacy evaluation

Wang

Guo

2014

IET Generation, Transmission & Distribution

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“…Large amount of following studies have successively introduced the concepts of the expansion of Hartley entropy and Shannon entropy [16], relative entropy [17], cumulative residual entropy [18][19][20][21], joint entropy [22,23], conditional entropy [24][25][26], mutual information [27][28][29][30][31][32], cross entropy [33][34][35][36][37][38], fuzzy entropy [15,39], maximum entropy principle [40,41] and minimum cross-entropy principle [42,43], and a series of achievements have been made in these aspects. Zhong makes use of general information functions to unify the methods of describing information metrics with Entropy formulas [4].…”

Section: About the Metrics Of Informationmentioning

confidence: 99%

Objective information theory: A Sextuple model and 9 kinds of metrics

Shen

et al. 2014

2014 Science and Information Conference

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In the contemporary era, the importance of information is undisputed, but there has never been a common understanding of information, nor a unanimous conclusion to the researches on information metrics. Based on the previous studies, this paper analyzes the important achievements in the researches of the properties and metrics of information as well as their main insufficiencies, and discusses the essence and connotation, the mathematical expressions and other basic problems related to information. On the basis of the understanding of the objectivity of information, it proposes the definitions and a Sextuple model of objective information; discusses the basic properties of information, and brings forward the definitions and mathematical expressions of nine kinds of metrics of information, i.e., extensity, detailedness, sustainability, richness, containability, delay, distribution, validity and matchability. Through these, this paper establishes a basic theory frame of Objective Information Theory to support the analysis and research on information and information system systematically and comprehensively.

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“…Therefore, probabilistic methods, which are able to capture the random behaviour of units and load fluctuations, have replaced deterministic approaches and are widely being used to evaluate the system adequacy [48].…”

Section: Total System Generationmentioning

confidence: 99%

Reliability impacts of increased wind generation in the Australian national electricity grid

Mosadeghy¹

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Wind power penetration has been consistently growing and it has been rapidly becoming a significant generation technology in many countries. However, the intermittent and variable nature of wind energy is a major barrier in wind power commitment. Wind speed fluctuations and unpredictability can affect the operation and reliability of power systems. Therefore, the impact of integrating large volume of wind generators on the system reliability needs to be carefully investigated and the reliability contributions of wind farms require to be evaluated for better integration of wind energy sources.Because of intermittency and variability of wind energy, conventional reliability evaluation methods are not applicable and different techniques have been developed to model wind generators.However, most of these methods are time-consuming or may not be able to capture time dependency and correlations between renewable resources and load. Therefore, this research intends to improve the existing reliability methods and proposes a faster and simpler approach. In this approach, wind power and electricity demand are being modelled as time-dependent clusters, which not only can capture their time-dependent attributes, but also is able to keep the correlations between the data sets. To illustrate the effectiveness of this framework, the proposed methodology has been applied to the IEEE reliability test system. In addition, the developed technique is validated by comparing results with the sequential Monte Carlo technique.Due to an increase in the wind power penetration level in Australia, this research also investigates the contribution of wind power in the Australian power system from reliability point of view. In order to calculate the reliability contribution of wind power, the proposed framework is implemented on the national electricity market at two different reliability assessment levels: generation and composite system levels. Moreover, the impacts of strategies such as coordinating hydro units with wind farms on the reliability of wind energy are investigated. Similar to wind energy, photovoltaic (PV) penetration level is increasing in the Australian power system, which can affect not only the reliability of the power system, but also the reliability benefit of wind farms.

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Simplified Cross-Entropy Based Approach for Generating Capacity Reliability Assessment

Cited by 34 publications

References 22 publications

Adaptive sequential importance sampling technique for short‐term composite power system adequacy evaluation

Adaptive sequential importance sampling technique for short‐term composite power system adequacy evaluation

Objective information theory: A Sextuple model and 9 kinds of metrics

Reliability impacts of increased wind generation in the Australian national electricity grid

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