Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm
نویسندگان
چکیده
To address the problems of slow convergence speed, easy to fall into local minima and low accuracy presented by previous algorithms in DC distribution network fault location, this paper adopts improved artificial bee colony slime mould algorithm (SMA) improve solve. On basis SMA, an adaptive adjustable feedback factor crossover operator are introduced speed; (ABC) is search ability jump out minima, (ISMA) formed. Firstly, based on six-terminal topology, a mathematical model bipolar short-circuit as well single-pole grounded established occurring between G-VSC W-VSC example. Then principle ISMA detail, suitable fitness function measure location network. Finally, experimental simulations conducted obtain points from optimization compare them with actual values verify algorithm. In addition, efficiency robustness further verified comparing other algorithms.
منابع مشابه
fault location in power distribution networks using matching algorithm
چکیده رساله/پایان نامه : تاکنون روشهای متعددی در ارتباط با مکان یابی خطا در شبکه انتقال ارائه شده است. استفاده مستقیم از این روشها در شبکه توزیع به دلایلی همچون وجود انشعابهای متعدد، غیر یکنواختی فیدرها (خطوط کابلی، خطوط هوایی، سطح مقطع متفاوت انشعاب ها و تنه اصلی فیدر)، نامتعادلی (عدم جابجا شدگی خطوط، بارهای تکفاز و سه فاز)، ثابت نبودن بار و اندازه گیری مقادیر ولتاژ و جریان فقط در ابتدای...
Network Reconfiguration of Distribution System Using Artificial Bee Colony Algorithm
Power distribution systems typically have tie and sectionalizing switches whose states determine the topological configuration of the network. The aim of network reconfiguration of the distribution network is to minimize the losses for a load arrangement at a particular time. Thus the objective function is to minimize the losses of the network by satisfying the distribution network constraints....
متن کاملElite Opposition-based Artificial Bee Colony Algorithm for Global Optimization
Numerous problems in engineering and science can be converted into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been widely used in many areas. However, due to the stochastic characteristics of its solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness o...
متن کاملA KFCM Algorithm Based on Improved Artificial Bee Colony Algorithm
Kernel fuzzy C-mean clustering (KFCM) algorithm is effective for high-dimensional data, but this algorithm has some defects of sensitivity to initialization and local optima. Artificial Bee Colony (ABC) algorithm is based on intelligent behaviors of honey bee swarm. It has the properties of strong global optimization and fast convergence speed. A KFCM algorithm based on improved ABC is proposed...
متن کاملArtificial bee colony algorithm with distribution-based update rule
In last decades, lots of nature-inspired optimization algorithms are developed and presented to the literature for solving optimization problems. Generally, these optimization algorithms can be grouped into two categories: evolutionary algorithms and swarm intelligence methods. Evolutionary methods try to improve the candidate solutions (chromosomes) using evolutionary operators such as crossov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3287322