A hybrid genetic algorithm for optimal reactive power planning based upon successive linear programming

Urdaneta, A.J.; Gómez, Julio; Sorrentino, Elmer; Flores, Luis Ivan Ruiz; Rojas, Díaz

doi:10.1109/59.801887

Cited by 80 publications

(26 citation statements)

References 11 publications

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“…Genetic algorithm [3] and the other stochastic search algorithms are global optimization algorithms and suitable for multi-path searching and solving problems with discrete integer constraints. A hybrid optimization algorithm combining with improved GA and continuous linear programming method was proposed in [4], which can obtain the global optimal solution and reduce the computation time.…”

Section: Introductionmentioning

confidence: 99%

A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis

et al. 2016

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Abstract:In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS) is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM) is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network.

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Section: Introductionmentioning

confidence: 99%

A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis

et al. 2016

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“…Metode GA telah diterapkan secara luas untuk penyelesaian masalah optimasi. Penggunaan GA bersifat kompetitif dan direkomendasikan untuk memecahkan masalah optimasi kombinatorial alamiah [2], [3]. Penelitian optimasi terkait menggunakan GA telah berhasil memberikan beberapa alternatif solusi dari permasalahan yang ada [2].…”

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Optimasi Penempatan Load Break Switch (LBS) pada Penyulang Karpan 2 Ambon menggunakan Metode Algoritma Genetika

Tupan

Hasanah

Wijono

2017

EECCIS

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“…GA is used to select the location and the rating of the Var source and SLP is used to solve operational optimization subproblems as a hybrid method in [5], [11], and [14]. GA is used in [22] to handle the MO model.…”

Section: ) Simulated Annealing (Sa)mentioning

confidence: 99%

“…The LP-based technique is used in [4], [5], [8], [11], [14], and [29] to linearize the nonlinear reactive power optimization problem. The LP approach has several advantages.…”

Section: ) Linear Programming (Lp)mentioning

confidence: 99%

Review of reactive power planning: objectives, constraints, and algorithms

Zhang

Tolbert

2008

2008 IEEE/PES Transmission and Distribution Conference and Exposition

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A hybrid genetic algorithm for optimal reactive power planning based upon successive linear programming

Cited by 80 publications

References 11 publications

A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis

A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis

Optimasi Penempatan Load Break Switch (LBS) pada Penyulang Karpan 2 Ambon menggunakan Metode Algoritma Genetika

Review of reactive power planning: objectives, constraints, and algorithms

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