Review of Fault Types, Impacts, and Management Solutions in Smart Grid Systems

Mousa, Mohammed; Abdelwahed, Sherif; Klüss, Joni

doi:10.4236/sgre.2019.104007

Cited by 8 publications

(8 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The SMART goal principle is a guideline used to determine the goals or targets of activity and organisational goals (Mousa et al, 2019). Meanwhile, according to Desjardins (2021), setting the right target or target is very important in motivating and improving the performance of a team because there is a clear focus on what will be achieved.…”

Section: Discussionmentioning

confidence: 99%

“…SMART is a well-known concept for effectively formulating goals, one of which is SMART. 'SMART objectives are used to formulate and achieve goals effectively and can be used in conjunction with evaluation' (Dovhopolyk & Smyrnova, 2021;Mousa et al, 2019).…”

Section: Smart Modelmentioning

confidence: 99%

“…Meanwhile, Alimohammadi et al (2018) stated that a method is needed that can facilitate organisations in setting targets, plans and goals, namely the SMART goals method. The SMART goal principle was first introduced by George T. Doran in 1981 in the November 1981 issue of Management Review Magazine (Mousa et al, 2019). A well-known concept for formulating training objectives effectively is SMART, namely 'specific, measurable, achievable, realistic and time-based'.…”

Section: Introductionmentioning

confidence: 99%

“…Time-based training has a deadline. The SMART-based training management model in our article has the goal of one skill at a time (Mousa et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Training management model to improve the competence of counselling guidance teachers

Laia

Situmorang²,

Wau³

et al. 2022

CJES

View full text Add to dashboard Cite

The role of the counselling guidance teacher is not only limited to helping students solve the problems they are facing. The study aims to analyse the effectiveness of the SMART-based management model on the competence of counselling guidance teachers. A prospective cross-sectional interventional study with baseline and repeat surveys was conducted to evaluate the effect of the SMART-based model. The training participants were 84 who were selected purposively and divided into 2 groups (intervention and control). Competency data was measured through a questionnaire and analysed by statistical independent t-test using SPSS software. The results showed that the SMART-based training management model was effective in improving the competence of counselling guidance teachers (p-value = 0.001). SMART-based can effectively formulate training objectives so that they are more focused and measurable. The SMART-based model can be used as an alternative training to improve the competence of counselling guidance teachers. Keywords: Competence, counselling guidance, SMART-model, training management, teacher.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Smart Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Time-based training has a deadline. The SMART-based training management model in our article has the goal of one skill at a time (Mousa et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Training management model to improve the competence of counselling guidance teachers

Laia

Situmorang²,

Wau³

et al. 2022

CJES

View full text Add to dashboard Cite

show abstract

“…A power failure refers to a problem or malfunction in the power supply system that results in the inability to transmit or provide electricity effectively. As shown in Figure 2, power failures can typically be categorized into two aspects: short circuit faults and open circuit faults [16].…”

Section: Fault Classificationmentioning

confidence: 99%

A Knowledge Graph Method towards Power System Fault Diagnosis and Classification

Li,

Wang

2023

Electronics

View full text Add to dashboard Cite

As the scale and complexity of electrical grids continue to expand, the necessity for robust fault detection techniques becomes increasingly urgent. This paper seeks to address the limitations in traditional fault detection approaches, such as the dependence on human experience, low efficiency, and a lack of logical relationships. In response, this study presents a cascaded model that leverages the Random Forest classifier in combination with knowledge reasoning. The proposed method exhibits a high efficiency and accuracy in identifying six basic fault types. This approach not only simplifies fault detection and handling processes but also improves their interpretability. The paper begins by constructing a power fault simulation model, which is based on the IEEE 14-bus system. Subsequently, a Random Forest classification model is developed and compared with other commonly used models such as Support Vector Machines (SVMs), k-Nearest Neighbor (KNN), and Naïve Bayes, using metrics such as the F1-score, accuracy, and confusion matrices. Our results reveal that the Random Forest classifier outperforms the other models, particularly in small-sample datasets, with an accuracy of 90%. Then, we apply knowledge mining technology to create a comprehensive knowledge graph of power faults. At last, we use the transE model for knowledge reasoning to enhance the interpretability to assist decision making and to validate its reliability.

show abstract

Non-parametric method for identification and prediction of events in the power system based on digital signal processing device

Мисриханов

Ryabchenko

Shuntov

2023

Rudenko International Conference “Methodological Problems in Reliability Study of Large Energy Systems” (Rses 2021)

View full text Add to dashboard Cite

Review of Fault Types, Impacts, and Management Solutions in Smart Grid Systems

Cited by 8 publications

References 51 publications

Training management model to improve the competence of counselling guidance teachers

Training management model to improve the competence of counselling guidance teachers

A Knowledge Graph Method towards Power System Fault Diagnosis and Classification

Non-parametric method for identification and prediction of events in the power system based on digital signal processing device

Contact Info

Product

Resources

About