An expert system operational aid for restoration and loss reduction of distribution systems

Liu, C.-C.; Lee, S.J.; Venkata, S.S.

doi:10.1109/59.192914

Cited by 439 publications

(131 citation statements)

References 11 publications

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“…Therefore the minimum power loss can be obtained by substituting equation (10) in equation (9). It can be established as follows,…”

Section: Responsibility Of Pgsamentioning

confidence: 99%

“…As per the PGSA, entity loops were identified with analogous state variables denoted as L 1 , L 2 , L 3 , L 4 and L 5 declared in equation (8). The I otc of loops are calculated as per equation (10). The values of I otc,i [for i Ɛ 1-5] are 107.15A, 152.98A, 49.43A, 119.52A and 8.20A respectively.…”

Section: Depiction With Test Systemmentioning

confidence: 99%

“…Then, the switches are opened successively to eliminate the loops. Other methods, such as mathematical programming techniques [5][6][7], expert systems [8][9][10] and optimization algorithm [11] have been proposed in recent years. In [12], the solution procedure employing heuristic rules and fuzzy multiobjective approach are developed to solve the network reconfiguration problem.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distribution System Loss Reduction through Hybrid Heuristic Technique

Wiselin¹,

S²

2012

IJCA

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This paper proposes a hybrid technology to solve the distribution system reconfiguration problem. The technology with the mixture of Plant Growth Simulation Algorithm (PGSA), Greedy and heuristic based fuzzy operation has been proposed. The optimization approach based on PGSA provides detailed description on switch states for calculation. The inclusion of Greedy with PGSA improves the efficiency of optimization by identifying the best loop sequence. Furthermore, the heuristic fuzzy has been introduced with PGSA and Greedy for handling constraints amid optimization. With the use of proposed algorithm, the system loss has been reduced convincingly without compromising the power flow constraints. The effectiveness of the proposed approach is demonstrated by employing the feeder switching operation scheme to IEEE 33 bus distribution system and 83 bus Distribution system of Taiwan Power Company.

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“…Therefore the minimum power loss can be obtained by substituting equation (10) in equation (9). It can be established as follows,…”

Section: Responsibility Of Pgsamentioning

confidence: 99%

Section: Depiction With Test Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distribution System Loss Reduction through Hybrid Heuristic Technique

Wiselin¹,

S²

2012

IJCA

View full text Add to dashboard Cite

show abstract

“…In cases A and B all consumers can be supplied while satisfying operating constraints, the number of switching actions being relatively small. In case C (respectively D) some loads are curtailed at buses 17 and 32 (respectively at buses: 3,15,16,17,31,32) in order to satisfy the operating constraints, the number of switching actions being relatively larger. As expected the tighter the voltage limits the larger the amount of load unsupplied.…”

Section: B Tests On the 33-bus Distribution Networkmentioning

confidence: 99%

“…Accordingly, most researches on service restoration focus on the first step of the decomposed approach by: composite heuristics [4][5][6][7][8][9][10], evolutionary algorithms [11][12][13][14][15], and expert systems [16] among others, for a comprehensive literature survey up to 2010 about the entire service restoration topic the reader is referred to [1].…”

Section: Introductionmentioning

confidence: 99%

Towards optimal post-fault self-healing in future smart distribution grids

Capitanescu

Bilibin

Sachau

2024

RE&PQJ

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Abstract. This paper deals with a key functionality of the future distribution smart grids namely the automatic post-fault network self-healing. To this end we propose an optimization approach that aims finding the post-fault grid topology that minimizes the amount of unsupplied energy to consumers. The approach extends existing optimization models, developed in the context of losses minimization, for our particular application and proposes ways to overcome their limitations. We prove the interest of the approach on a 33-bus benchmark distribution system as well as on a 61-bus real-life distribution grid.

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A hybrid machine learning and meta‐heuristic algorithm based service restoration scheme for radial power distribution system

Srivastava

Bhat

Thadikemalla³

et al. 2021

Int Trans Electr Energ Syst

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In-service Restoration (SR), the healthy section of the feeder can be reenergized by finding the optimal path for power flow. Through conventional methods which are mainly deterministic in nature, the computational burden is very high. Therefore, researchers have proposed various meta-heuristic based methods to solve the SR problem. But since, these methods are probability based; one single algorithm cannot guarantee optimal solution for all scenarios. Hence, the authors have proposed a Machine Learning (ML) based framework, which can predict the best SR scheme for a particular fault scenario among the SR solutions obtained through various meta-heuristic algorithms. The supervised ML model is developed using the fault features as input values and the best performing meta-heuristic algorithm as the target value. To check the validity of the ML framework, the authors have taken four different meta-heuristic algorithms, which are, Enhanced Integer Coded Particle Swarm Optimization (EICPSO), Shuffled Frog Leaping Algorithm (SFLA), Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), and Ant Colony Optimization (ACO) algorithm. The ML model can be extended for

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An expert system operational aid for restoration and loss reduction of distribution systems

Cited by 439 publications

References 11 publications

Distribution System Loss Reduction through Hybrid Heuristic Technique

Distribution System Loss Reduction through Hybrid Heuristic Technique

Towards optimal post-fault self-healing in future smart distribution grids

A hybrid machine learning and meta‐heuristic algorithm based service restoration scheme for radial power distribution system

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