Hybrid differential evolution with artificial bee colony and its application for design of a reconfigurable antenna array with discrete phase shifters

2012 ◽  
Vol 6 (14) ◽  
pp. 1573-1582 ◽  
Author(s):  
X. Li ◽  
M. Yin
Keyword(s):  
Differential Evolution ◽  
Antenna Array ◽  
Artificial Bee Colony ◽  
Phase Shifters ◽  
Reconfigurable Antenna ◽  
Bee Colony ◽  
Discrete Phase

scholarly journals Hybrid Differential Evolution with Biogeography-Based Optimization for Design of a Reconfigurable Antenna Array with Discrete Phase Shifters

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Xiangtao Li ◽  
Minghao Yin
Keyword(s):  
Differential Evolution ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Dynamic Range ◽  
Phase Shifters ◽  
Main Beam ◽  
Reconfigurable Antenna ◽  
Reconfigurable Design ◽  
Low Sidelobe ◽  
Discrete Phase

Multibeam antenna arrays have important applications in communications and radar. This paper presents a new method of designing a reconfigurable antenna with quantized phase excitations using a new hybrid algorithm, called DE/BBO. The reconfigurable design problem is to find the element excitation that will result in a sector pattern main beam with low sidelobes with additional requirement that the same excitation amplitudes applied to the array with zero-phase should be in a high directivity, low sidelobe pencil-shaped main beam. In order to reduce the effect of mutual coupling between the antenna-array elements, the dynamic range ratio is minimized. Additionally, compared with the continuous realization and subsequent quantization, experimental results indicate that the performance of the discrete realization of the phase excitation value can be improved. In order to test the performances of hybrid differential evolution with biogeography-based optimization, the results of some state-of-art algorithms are considered, for the purposed of comparison. Experiment results indicate the better performance of the DE/BBO.

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

2020 ◽  
Vol 13 (3) ◽  
pp. 384-395
Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li
Keyword(s):  
Differential Evolution ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Bee Colony ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Dynamic Economic Dispatch ◽  
Integrated Power System

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

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