Application of electricity tracing theory and hybrid ant colony algorithm for ranking bus priority in power system

Hamid, Zulkiffli Abdul; Musirin, Ismail; Rahim, M. N. A.; Kamari, Nor Azwan Mohamed

doi:10.1016/j.ijepes.2012.07.010

Cited by 11 publications

(6 citation statements)

References 21 publications

(27 reference statements)

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“…Whereas the remaining three (non FVSI-LT) are Loss Sensitivity (LS) [19], Risk of Voltage Instability Index (RVI) [17], and Voltage Magnitude based ranking (VM) [20]. The first FVSI-LT is marked as FVSI-LT A in which the tracing algorithm is based on optimization technique as proposed in [15]. The second one is FVSI-LT B with TGLDF [6] as the tracing algorithm.…”

Section: Resultsmentioning

confidence: 99%

“…(8) Thus, the only way for tracing FVSI contributed by a load bus is by tracing the receiving end power fraction, x r i via any power tracing algorithms, as proposed in [6], [11] and [14]. It is recommended to explore article [15] for a brief explanation on how to perform FVSI-LT using the existing tracing algorithms. By determining the traced FVSI as in (8), the system operator (SO) is able to make a ranking list of load buses precisely indicating their priority to be shed.…”

Section: Fvsi Modification For Fvsi-ltmentioning

confidence: 99%

See 1 more Smart Citation

Utilizing Stability Index Tracing for Precise Load Buses Identification in Load Shedding Problem

Hamid¹,

Musirin²,

Othman³

2013

ENG

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This paper proposes a new approach for suitable load buses identification via stability index tracing in performing corrective load shedding. The proposed identification technique is called the Fast Voltage Stability Index Load Tracing (FVSI-LT). By implementing a power tracing algorithm, a group of major contributors on the stress experienced by a power system is able to be precisely identified by a system operator (SO) based on the traced values of FVSI. To be precise, the traced FVSI via FVSI-LT can be used to form a ranking list indicating the priority of buses committed for shedding purpose. After designing a Fuzzy Inference System (FIS) for deciding the allowable load powers to be shed and performing experiment on IEEE 57-Bus reliability test system (RTS), it is revealed that the ranking list provided by FVSI-LT results to the most consistent improvement in terms of voltage stability and losses minimization

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Section: Resultsmentioning

confidence: 99%

Section: Fvsi Modification For Fvsi-ltmentioning

confidence: 99%

Utilizing Stability Index Tracing for Precise Load Buses Identification in Load Shedding Problem

Hamid¹,

Musirin²,

Othman³

2013

ENG

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“…Natural language is incredibly detailed, but it does not lend itself well to processing. In literature study [19][20][21][22], researchers and engineers have proposed a variety of methods in which knowledge can be represented so that it can be examined by an AI computer program as follows:…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Application of artificial intelligence and machine learning for BIM: review

Bassir

Lodge

Chang

et al. 2023

Int. J. Simul. Multidisci. Des. Optim.

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Quality control is very important aspect in Building Information Modelling (BIM) workflows. Whatever stage of the lifecycle it is important to get and to follow building indicators. The BIM it is very data consuming field and analysis of these data require advance numerical tools from image processing to big data analysis. Artificial intelligent (AI) and machine learning (ML) had proven their efficiency to deal with automate processes and extract useful sources of data in different industries. In addition to the indicators tracking, AI and ML can make a good prediction about when and where to provide maintenance and/or quality control. In this article, a review of the AI and ML application in BIM will be presented. Further suggestions and challenges will be also discussed. The aim is to provide knowledge on the needs nowadays into building and landscaping domain, and to give a wide understanding on how those technics would impact industries and future studies.

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“…Optimization approaches are frequently chosen to tune variables of devices in solving power system stability problems. Some new algorithms, such as Particle Swarm Optimization [15][16][17], Gravitational SearchAlgorithm [18][19][20], Firefly [21][22][23], Whale Optimization Algorithm [24][25][26], Ant Colony Optimization [27][28][29], Flower Pollination Algorithm [30][31][32], Moth Flame Optimization [33][34][35] and Bat Algorithm [36][37][38] have also gained attention because of their efficiency. These algorithms are inspired from nature with the characteristic of the investigated biological system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Energy Scheduling Strategy in Power System using Bat Algorithm Optimization Approach

2020

IJETER

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This paper presents an energy scheduling strategy for power system using Bat Algorithm (BA) optimization technique. BA is inspired by the natural behaviour of microbats, that of echolocation. The paper focuses on the minimization of the total power and cost needed according to the power demand and limits of power generation. Two systems, the IEEE 9 bus with 3 generator system and IEEE 30 bus with 6 generator system, are studied and simulated using Matlab. The performance of BA is compared with evolutionary programming (EP) technique. The simulation results indicate that BA performs better than EP in determining the optimal power generation valuewith minimum generation cost.

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Application of electricity tracing theory and hybrid ant colony algorithm for ranking bus priority in power system

Cited by 11 publications

References 21 publications

Utilizing Stability Index Tracing for Precise Load Buses Identification in Load Shedding Problem

Utilizing Stability Index Tracing for Precise Load Buses Identification in Load Shedding Problem

Application of artificial intelligence and machine learning for BIM: review

Optimal Energy Scheduling Strategy in Power System using Bat Algorithm Optimization Approach

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