Binary Adaptive Ant Colony Optimization in Reactive Power Optimization

2012 ◽  
Vol 616-618 ◽  
pp. 2091-2096 ◽  
Author(s):  
Hong Hong ◽  
Fang Liu
Keyword(s):  
Ant Colony Optimization ◽  
State Transition ◽  
Reactive Power ◽  
Ant Colony ◽  
Reactive Power Optimization ◽  
Ant Colony Optimization Algorithm ◽  
Information Update ◽  
Transition Rules ◽  
Update Rules ◽  
State Transition Rules

This article proposed an Adaptive Binary Ant Colony Optimization Algorithm, which is based on the dual network diagram, designed to state transition rules and information update rules, and then according to the algorithm processes adjust information volatilizing factor dynamically, Verify the validity and superiority of the algorithm.

An ant colony optimization algorithm-based emergency control strategy for voltage collapse mitigation

2012 ◽  
Vol 3 (2) ◽  
pp. 147-156 ◽  
Author(s):  
R. A. El-Sehiemy ◽  
A. A. A. El Ela ◽  
A. M. M. Kinawy ◽  
M. T. Mouwafia
Keyword(s):  
Power Systems ◽  
Ant Colony Optimization ◽  
Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Ant Colony ◽  
Voltage Collapse ◽  
Ant Colony Optimization Algorithm ◽  
Preventive Control ◽  
Control Actions

Abstract This paper presents optimal preventive control actions using ant colony optimization (ACO) algorithm to mitigate the occurrence of voltage collapse in stressed power systems. The proposed objective functions are: minimizing the transmission line losses as optimal reactive power dispatch (ORPD) problem, maximizing the preventive control actions by minimizing the voltage deviation of load buses with respect to the specified bus voltages and minimizing the reactive power generation at generation buses based on control variables under voltage collapse, control and dependent variable constraints using proposed sensitivity parameters of reactive power that dependent on a modification of Fast Decoupled Power Flow (FDPF) model. The proposed preventive actions are checked for different emergency conditions while all system constraints are kept within their permissible limits. The ACO algorithm has been applied to IEEE standard 30-bus test system. The results show the capability of the proposed ACO algorithm for preparing the maximal preventive control actions to remove different emergency effects.

scholarly journals Ant Colony Optimization Algorithm for Continuous Domains Based on Position Distribution Model of Ant Colony Foraging

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Liqiang Liu ◽  
Yuntao Dai ◽  
Jinyu Gao
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Research Direction ◽  
Ant Colony ◽  
Distribution Model ◽  
Position Distribution ◽  
Test Functions ◽  
Ant Colony Optimization Algorithm ◽  
Continuous Domains ◽  
Update Rules

Ant colony optimization algorithm for continuous domains is a major research direction for ant colony optimization algorithm. In this paper, we propose a distribution model of ant colony foraging, through analysis of the relationship between the position distribution and food source in the process of ant colony foraging. We design a continuous domain optimization algorithm based on the model and give the form of solution for the algorithm, the distribution model of pheromone, the update rules of ant colony position, and the processing method of constraint condition. Algorithm performance against a set of test trials was unconstrained optimization test functions and a set of optimization test functions, and test results of other algorithms are compared and analyzed to verify the correctness and effectiveness of the proposed algorithm.

Path planning of mobile robot based on adaptive ant colony algorithm

2020 ◽  
Vol 39 (4) ◽  
pp. 5329-5338
Author(s):  
Yan Zheng ◽  
Qiang Luo ◽  
Haibao Wang ◽  
Changhong Wang ◽  
Xin Chen
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
State Transition ◽  
Ant Colony ◽  
Local Optimum ◽  
Heuristic Function ◽  
State Transfer ◽  
Transition Rules ◽  
Adaptive Heuristic ◽  
State Transition Rules

The traditional ant colony algorithm has some problems, such as low search efficiency, slow convergence speed and local optimum. To solve those problems, an adaptive heuristic function is proposed, heuristic information is updated by using the shortest actual distance, which ant passed. The reward and punishment rules are introduced to optimize the local pheromone updating strategy. The state transfer function is optimized by using pseudo-random state transition rules. By comparing with other algorithms’ simulation results in different simulation environments, the results show that it has effectiveness and superiority on path planning.

Modeling and optimizing logistics, information, economic and financial intercluster cooperation using the ant colony optimization algorithm

2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Population Decline ◽  
Innovation System ◽  
Federal District ◽  
Original Model ◽  
Ant Colony ◽  
Industrial Agglomeration ◽  
Ant Colony Optimization Algorithm

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.

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