The Impact Of Multiple DG Penetration With FCL In Distribution System For The Enhancement Of Protection Coordination Index Using Particle Swarm Optimization Algorithm

2019 ◽  
Author(s):  
Sujatha B. C. ◽  
Vanishree B. S.
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
The Impact

Disclosure Model of Capital Accounting Information Based on Immune Particle Swarm Optimization Algorithm

2021 ◽  
Vol 7 (6) ◽  
pp. 6332-6347
Author(s):  
Yu Ni
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Information Disclosure ◽  
Particle Swarm Optimization Algorithm ◽  
Accounting Information ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Regulation Mechanism ◽  
Swarm Optimization ◽  
The Impact

The effectiveness of capital market and the allocation of social resources depend on the disclosure of capital accounting information. In order to analyze the tendency of capital accounting information disclosure, this paper proposes a disclosure model of capital accounting information based on immune particle swarm algorithm. There are many factors that affect the tendency of capital accounting information disclosure. We should give priority to corporate governance level and financial status level to construct the impact index system of capital accounting information disclosure. The capital accounting information disclosure model was constructed to establish the functional relationship between each factor variable and disclosure tendency. Particle concentration was maintained through immune memory and self-regulation mechanism to ensure the diversity of the population, which avoids the traditional shortcomings of particle swarm optimization algorithm. Finally, the parameter estimation of capital accounting information disclosure model were completed. The results show that there are four factors affecting the disclosure tendency of capital accounting information, including ownership structure, leverage, growth and audit opinion. The accuracy of the model used in this paper is up to 75%.

scholarly journals Research on Outage Maintenance Optimization Strategy Based on Improved Multi-Objective Particle Swarm Optimization

2021 ◽  
Vol 2138 (1) ◽  
pp. 012008
Author(s):  
Cun Li ◽  
Ding Yuan ◽  
Gaige Liang ◽  
Lu Liu ◽  
Xuedong Jiang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Power Grid ◽  
Complex Structure ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Large Power ◽  
Multi Objective ◽  
The Impact

Abstract With the increasingly complex structure of the transmission system, the impact of power outage caused by faults in the power grid is becoming greater and greater. The power grid shall cut off the maintenance of line equipment to ensure the power supply safety of the system. During the outage maintenance period, how to achieve safe maintenance and low-cost impact is the main content of outage control. Aiming at the problem of outage maintenance, a particle swarm optimization algorithm with the goal of minimum impact, economic optimization and shortest maintenance time is proposed. The game theory is used to select the optimal solution from the solutions of particle swarm optimization algorithm to solve the multi-objective function, so as to improve and ensure the population diversity, realize the efficiency and economy of outage maintenance, and meet the needs of outage plan of large power grid. The effectiveness of the proposed algorithm is further verified by comparing multi class baseline experiments.

Sizing and Locating of Distributed Generations Based on Chaos Particle Swarm Optimization Algorithm

2013 ◽  
Vol 291-294 ◽  
pp. 2119-2123
Author(s):  
Ying Chen ◽  
Lian Guang Liu
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Particle Swarm Optimization Algorithm ◽  
Operating Cost ◽  
Particle Swarm ◽  
Local Optimum ◽  
Swarm Optimization ◽  
Distributed Generations ◽  
Minimum Operating

Optimal configuration of distributed generations (DGs) is an important topic in the developing of intelligent power grid. In this paper, to finding out the optimal sitting and sizing Of DGs in distribution network without considering the newly increased load nodes, an economical model is built that regards the annual minimum operating cost as the objective function. Meanwhile, in order to avoid the particles trapping in local optimum, the chaos particle swarm optimization algorithm (CPSO) is adopted. Through testing on the IEEE 33-bus radial distribution system, the analysis results showed that the algorithm is effective.

scholarly journals Optimasi Penempatan dan Kapasitas Bank Kapasitor Untuk Mereduksi Rugi-Rugi Daya Menggunakan Kombinasi Metode Loss Sensitivity Factors dan Particle Swarm Optimization (PSO)

Electrician ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 48
Author(s):  
Fikri Adi Anggara ◽  
Osea Zebua ◽  
Khairuddin Hasan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Distribution Systems ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Power Losses ◽  
Swarm Optimization ◽  
Sensitivity Factors ◽  
Active Power Losses

Intisari — Sistem distribusi yang memiliki saluran panjang biasanya memiliki masalah rugi-rugi daya dan votage drop. Masalah ini dapat diatasi dengan cara menempatkan bank kapasitor pada sistem distribusi. Masalah utama dalam penempatan bank kapasitor adalah menentukan lokasi dan kapasitas yang optimal. Penelitian ini menggunakan metode Loss Sensitivity Factors (LSF) untuk menentukan kandidat bus yang akan dipilih sebagai lokasi penempatan bank kapasitor dan metode algoritma Particle Swarm Optimization digunakan untuk mencari kapasitas optimal bank kapasitor yang dipasang. Simulasi dilakukan dengan menggunakan perangkat lunak MATLAB. Studi kasus yang digunakan adalah kasus uji IEEE 10 bus dan penyulang Pakis di gardu induk Menggala. Hasil simulasi menunjukkan bahwa kombinasi kedua metode dapat menentukan lokasi penempatan dan kapasitas optimal bank kapasitor dengan reduksi rugi-rugi daya yang minimum untuk kedua studi kasus.Kata kunci — Rugi-Rugi Daya, Bank Kapasitor, Loss Sensitivity Factors, Algoritma Particle Swarm Optimization. Abstract — Distribution systems that have long lines usually have problems with power losses and votage drop. This problem can be overcome by placing a bank capacitor in the distribution system. The main problem in the placement of bank capacitors is determining the optimal location and capacity. This study uses the Loss Sensitivity Factors (LSF) method to determine the candidate bus that will be selected as the location of the placement of bank capacitors and the Particle Swarm Optimization algorithm method is used to find the optimal capacity of the installed bank capacitor. Simulation is done using MATLAB software. The case studies used were the IEEE 10 bus and Pakter feeder test cases at the Menggala substation. The simulation results show that the combination of the two methods can determine the placement location and optimal capacitor capacity of the bank by reducing the minimum power losses for the two case studies.Keywords— Active power losses, Capacitor Bank, Loss Sensitivity Factors, Particle Swarm Optimization Algorithm.

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