Reliability Assessment of the Brazilian Power System Using Enumeration and Monte Carlo

Rei, Andrea M.; Schilling, M.T.

doi:10.1109/tpwrs.2008.922532

Cited by 56 publications

(25 citation statements)

References 13 publications

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“…Monte Carlo simulation approaches have been widely used, particularly in relation to transmission and generation-related problems [12]. Markov model-based approaches [13] and direct analytical approaches are also reported.…”

Section: B Reliability Evaluation and Optimizationmentioning

confidence: 99%

A method for the evaluation and optimisation of power losses and reliability of supply in a distribution network

Ding

Bell

Elders

2016

2016 Power Systems Computation Conference (PSCC)

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This version is available at https://strathprints.strath.ac.uk/56373/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Abstract-This paper presents two methods for evaluating and optimizing the configuration of a distribution network. A new loss-optimization method is described which partitions, optimizes and then recombines the network topology to identify the lowest loss configurations available. A reliability evaluation method is presented which evaluates, on a load-by-load basis, the most effective restoration path and the associated time. In contrast to previously-reported methods, the operation of different types of switch is integrated into this approach, reducing dependency on pre-determined restoration times for each load each fault location. This provides a more accurate estimate of the outage durations through identification of the specific restoration method for each load under each fault condition. The optimization method applied is shown to be effective in identifying optimally-reliable network topologies. Significant benefits are shown to be available.

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Section: B Reliability Evaluation and Optimizationmentioning

confidence: 99%

A method for the evaluation and optimisation of power losses and reliability of supply in a distribution network

Ding

Bell

Elders

2016

2016 Power Systems Computation Conference (PSCC)

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“…Finally, marginal state is defined as the intermediate state between healthy and at-risk state as represented by (14), and the probability of marginal state can be calculated by using the probabilities of healthy and at-risk state as , and…”

Section: At-risk Statementioning

confidence: 99%

“…These general TNEP problems should start all possible candidates, and screen them with the constraints of power flow and reliability assessments to obtain optimal alternative [13][14]. The constraints of power flow are for the convergence and stability of power system, and those of reliability are for ensuring the power system security.…”

Section: Introductionmentioning

confidence: 99%

Transmission Network Expansion Planning Using Reliability and Economic Assessment

Kim¹,

Son²,

Kim³

2015

Journal of Electrical Engineering and Technology

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-This paper presents a probabilistic approach of reliability evaluation and economic assessment for solving transmission network expansion planning problems. Three methods are proposed for TNEP, which are reorganizing the existing power system focused on the buses of interest, selecting candidates using modified system operating state method with healthy, marginal and at-risk states, and finally choosing the optimal alternative using cost-optimization method. TNEP candidates can be selected based on the state reliability such as sufficient and insufficient indices, as proposed in this paper. The process of economic assessment involves the costs of construction, maintenance and operation, congestion, and outage. The case studies are carried out with modified IEEE-24 bus system and Jeju island power system expansion plan in Korea, to verify the proposed methodology.

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“…For probabilistic DGs, probabilistic methods including Monte Carlo method, scenario based decision making method and point estimate method can be suitably applied. But, Monte Carlo method which was introduced in [22][23] and the scenario based decision making method introduced in [24] are all computationally harder. Compared to the other probabilistic methods, point estimate method (PEM) in [25][26][27] has highly reduced computational costs and is extremely applicable for the probabilistic uncertainties of DGs.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment for Distribution Systems Using a Developed PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Gong

Lei

2017

Preprint

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the intermittency and variability of these permeated Distributed Generators (DGs) could critically cause many security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. And then, four risk indices EENS, PLC, EFLC and SI were established to reflect the system risk level of distribution system. For the certain mathematical distribution of the DGs' output power, a developed PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this developed PEM-based method, enumeration method was used to list the states of distribution systems, an improved PEM was presented to deal with the uncertainties of DGs and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by the tests of a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

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Reliability Assessment of the Brazilian Power System Using Enumeration and Monte Carlo

Cited by 56 publications

References 13 publications

A method for the evaluation and optimisation of power losses and reliability of supply in a distribution network

A method for the evaluation and optimisation of power losses and reliability of supply in a distribution network

Transmission Network Expansion Planning Using Reliability and Economic Assessment

Risk Assessment for Distribution Systems Using a Developed PEM-Based Method Considering Wind and Photovoltaic Power Distribution

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