Analytical reliability assessment of cyber-physical distribution system with distributed feeder automation

Zeng, Guangxuan; Yu, Tao; Wang, Ziyao; Lin, Dan

doi:10.1016/j.epsr.2022.107864

Cited by 13 publications

(3 citation statements)

References 14 publications

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“…To analyse the sensitivity changes of reliability measures in various stages of intelligent distribution networks, a big data analysis was conducted on the initial, initial, development, and mature stages of the national distribution network overhead and cable systems from 2017 to 2022 [4][5][6]. The sensitivity changes of different measures in different stages of the distribution network with the development of the power grid are shown in Table 2.…”

Section: Analysis Of the Combination Model Of Improvement Measuresmentioning

confidence: 99%

Research on grid structure and equipment combination mode to improve the reliability of intelligent distribution network power supply

Wu,

Chen,

Ouyang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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To improve the reliability level of intelligent distribution networks, it is often not possible to implement a single measure, but rather to combine and implement different reliability improvement measures. Therefore, this article studies the corresponding changes in the sensitivity of other measures after a change in a major reliability improvement measure, and based on this, provides the combination relationship of different measures. In addition, a combination analysis of reliability improvement measures was conducted for different stages of power grid development, and effective ranking of measures at different power grid levels was obtained. Further provide the optimal combination model of reliability improvement measures and the formulation process of the optimal improvement strategy, and calculate the reliability improvement strategy combination model for each stage of the city center, urban area, and rural area based on this. This provides clear methodological guidance for improving the reliability of prefecture level power grid companies.

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Section: Analysis Of the Combination Model Of Improvement Measuresmentioning

confidence: 99%

Research on grid structure and equipment combination mode to improve the reliability of intelligent distribution network power supply

Wu,

Chen,

Ouyang

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

View full text Add to dashboard Cite

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“…Indeed, other aspects are less controlled and mostly external to electric power systems, contributing to the deterioration of reliability indicators. However, having optimal switching contributes to improving reliability indicators despite the existence of electric failures [11]. The reliability analysis is carried out by levels, where level 1 evaluates the sufficiency in the generation, level 2 evaluates the sufficiency in the generation plus the availability of transmission lines, and level 3, which is the objective of this research, evaluate the reliability in electric energy distribution.…”

Section: B Study Of the Reliability In Electric Distribution Systemsmentioning

confidence: 99%

Optimal Location of Reclosers in Electrical Distribution Systems Considering Multicriteria Decision Through the Generation of Scenarios Using the Montecarlo Method

et al. 2023

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This work presents a novel methodology for the optimal location of reclosers in electric distribution systems. The proposal uses a multicriteria analysis to evaluate the reliability indicators for this level 3 (distribution) by generating scenarios from pseudo-random variables. The reliability indicators considered in the study are the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Customer Average Interruption Duration Index (CAIDI), and Average Energy Not Supplied (AENS). It is employed a deterministic random generation in a defined range associated with each analysis variable (failure rate by elements and loads, failure duration, number of customers per load point, mean power consumed at each load point, etc.) The reliability indicators (criteria) are calculated for every possible location of a recloser in the candidate primary sections, thus obtaining the decision matrix, normalized and weighted by the CRITIC method to find the optimal location according to a minimum criterion. This analysis is repeated N times through the generation of scenarios using the Montecarlo method, establishing the probability of occurrence of each winning alternative and choosing the final optimal location of the first recloser within the distribution system. The methodology also proposes the switching coordination repeating the previously described analysis for locating a second recloser considering that the first was already a winning alternative within the generation of "many" scenarios. The scope of the proposed methodology is the number of reclosers that it is desired to analyze considering cost constraints and is general for any distribution system. The analysis is carried out with comprehensive programming in the Matlab software environment. The results successfully respond to the maneuver and switching tests with the joint criterion of minimizing all reliability indicators for level 3 (distribution). With this proposal, knowledge gaps in reliability studies are solved. The absence of data is completed with generations of pseudo-random variables, and the optimal location of the reclosers responds to all reliability criteria in distribution with weighting alternatives. The novel proposed methodology is validated with an exhaustive search analysis where all possible single or multiple reconnection scenarios are analyzed. The winning location alternative found coincides with the one determined by the proposed methodology in more than 90% of the generated random scenarios.

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“…As an important part of power supply reliability assurance, relay protection is a traditional means to achieve fault isolation. However, the distribution network is very large, and traditional relay protection alone cannot greatly shorten the power supply recovery time [4]. In order to solve these disadvantages, feeder automation system has become an important tool to shorten the power supply recovery time.…”

Section: Introductionmentioning

confidence: 99%

Design of quick centralized feeder automation control system

Cao,

Yu,

Xue

et al. 2023

Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023)

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Power supply reliability is an important performance index of distribution network, and the traditional relay protection mode is the key role to ensure power supply reliability. However, when faults often occur, the power supply restoration time of the traditional relay protection mode is long, so it is difficult to meet the requirements of distribution network for fast fault recovery. In view of this disadvantage, a quick centralized feeder automation control system is proposed in this paper, which realizes the rapid transmission and processing of information and shortens the fault isolation time and power supply recovery time through the transmission of short data packet format. In addition, the signal based on Beidou timestamp is introduced to locate the fault point quickly and accurately. Finally based on the real time digital simulator (RTDS), a simulation test platform is built to verify the correctness and effectiveness of the quick centralized feeder automation control system.

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Analytical reliability assessment of cyber-physical distribution system with distributed feeder automation

Cited by 13 publications

References 14 publications

Research on grid structure and equipment combination mode to improve the reliability of intelligent distribution network power supply

Research on grid structure and equipment combination mode to improve the reliability of intelligent distribution network power supply

Optimal Location of Reclosers in Electrical Distribution Systems Considering Multicriteria Decision Through the Generation of Scenarios Using the Montecarlo Method

Design of quick centralized feeder automation control system

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