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Journal ArticleDOI

Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm

F. S. Abu-Mouti, +1 more
- 10 Oct 2011 - 
- Vol. 26, Iss: 4, pp 2090-2101
TLDR
A new optimization approach that employs an artificial bee colony (ABC) algorithm to determine the optimal DG-unit's size, power factor, and location in order to minimize the total system real power loss.
Abstract
Distributed generation (DG) has been utilized in some electric power networks. Power loss reduction, environmental friendliness, voltage improvement, postponement of system upgrading, and increasing reliability are some advantages of DG-unit application. This paper presents a new optimization approach that employs an artificial bee colony (ABC) algorithm to determine the optimal DG-unit's size, power factor, and location in order to minimize the total system real power loss. The ABC algorithm is a new metaheuristic, population-based optimization technique inspired by the intelligent foraging behavior of the honeybee swarm. To reveal the validity of the ABC algorithm, sample radial distribution feeder systems are examined with different test cases. Furthermore, the results obtained by the proposed ABC algorithm are compared with those attained via other methods. The outcomes verify that the ABC algorithm is efficient, robust, and capable of handling mixed integer nonlinear optimization problems. The ABC algorithm has only two parameters to be tuned. Therefore, the updating of the two parameters towards the most effective values has a higher likelihood of success than in other competing metaheuristic methods.

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Citations
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Optimal Distributed Generation Placement in Power Distribution Networks: Models, Methods, and Future Research

TL;DR: An overview of the state-of-the-art models and methods applied to the optimal DG placement problem can be found in this article, where the authors analyze and classify current and future research trends in this field.
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Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Technologies

TL;DR: The key is to provide the methodologies, approaches, and foresights for the emerging technologies of V2H, V2V, and V2G, namely, the vehicle-to-home (V2H), vehicle- to-vehicle (V 2V), and vehicle-To-grid (V1G) technologies.
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State-of-the-Art Techniques and Challenges Ahead for Distributed Generation Planning and Optimization

TL;DR: A critical review of the work in this field can be found in this paper, highlighting the barriers to implementation of the advanced techniques and highlighting why network operators have been slow to pick up on the research to date.
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Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality

TL;DR: This study identifies future research opportunities in relation to challenges for optimal ESS placement planning, development and implementation issues, optimisation techniques, social impacts, and energy security.
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Review of optimization techniques applied for the integration of distributed generation from renewable energy sources

TL;DR: In this article, the authors present a review of recent optimization methods applied to solve the problem of placement and sizing of distributed generation units from renewable energy sources based on a classification of the most recent and highly cited papers.
References
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Journal ArticleDOI

A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm

TL;DR: Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm that is used for optimizing multivariable functions and the results showed that ABC outperforms the other algorithms.
Journal ArticleDOI

Network reconfiguration in distribution systems for loss reduction and load balancing

TL;DR: Accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations.
Journal ArticleDOI

An efficient constraint handling method for genetic algorithms

TL;DR: GA's population-based approach and ability to make pair-wise comparison in tournament selection operator are exploited to devise a penalty function approach that does not require any penalty parameter to guide the search towards the constrained optimum.
Journal ArticleDOI

On the performance of artificial bee colony (ABC) algorithm

TL;DR: The simulation results show that the performance of ABC algorithm is comparable to those of differential evolution, particle swarm optimization and evolutionary algorithm and can be efficiently employed to solve engineering problems with high dimensionality.
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