Research on computing the access limit capacity of distributed photovoltaic system based on ant lion algorithm

2020 ◽  
Author(s):  
Wang Xin
Keyword(s):  
Photovoltaic System ◽  
Lion Algorithm ◽  
Ant Lion ◽  
Limit Capacity

A comparative analysis of the queuing search algorithm, the sine-cosine algorithm, the ant lion algorithm to determine the optimal weight design problem of a spur gear drive system

2021 ◽  
Vol 63 (5) ◽  
pp. 442-447
Author(s):  
Hammoudi Abderazek ◽  
Ferhat Hamza ◽  
Ali Riza Yildiz ◽  
Liang Gao ◽  
Sadiq M. Sait
Keyword(s):  
Optimization Algorithm ◽  
Search Algorithm ◽  
Spur Gear ◽  
Ant Lion Optimization ◽  
Lion Algorithm ◽  
Weight Design ◽  
Sine Cosine Algorithm ◽  
Ant Lion ◽  
Teaching Learning ◽  
Lion Optimization Algorithm

Abstract Metaheuristic optimization algorithms have gained relevance and have effectively been investigated for solving complex real design problems in diverse fields of science and engineering. In this paper, a recent meta-heuristic approach inspired by human social concepts, namely the queuing search algorithm (QSA), is implemented for the first time to optimize the main parameters of the spur gear, in particular, to minimize the weight of a single-stage spur gear. The effectiveness of the algorithm introduced is examined in two steps. First, the algorithm used is compared with descriptions in previous studies and indicates that the final results obtained by QSA lead to a reduction in gear weight by 7.5 %. Furthermore, the outcomes obtained are compared with those for the other five algorithms. The results reveal that the QSA outperforms the techniques with which it is compared such as the sine-cosine optimization algorithm, the ant lion optimization algorithm, the interior search algorithm, the teaching-learning-based algorithm, and the jaya algorithm in terms of robustness, success rate, and convergence capability.

Ant lion optimized hybrid intelligent PID-based sliding mode controller for frequency regulation of interconnected multi-area power systems

2020 ◽  
Vol 42 (9) ◽  
pp. 1594-1617
Author(s):  
Gomaa Haroun AH ◽  
Yin-Ya Li
Keyword(s):  
Power Systems ◽  
Power System ◽  
Sliding Mode ◽  
Photovoltaic System ◽  
Frequency Regulation ◽  
Sliding Mode Controller ◽  
Physical Constraints ◽  
Optimization Task ◽  
Suggested Technique ◽  
Ant Lion

In this article, a novel hybrid intelligent Proportional Integral Derivative (PID)-based sliding mode controller (IPID-SMC) is proposed to solve the LFC problem for realistic interconnected multi-area power systems. The optimization task for best-regulating parameters of the suggested controller structure is fulfilled by the ant lion optimizer (ALO) technique. To assess the usefulness and practicability of the suggested ALO optimized IPID-SMC controller, three test systems – that is, four-area hybrid power system, two-area reheat thermal-photovoltaic system and two-area multi-sources power system – are employed. Different nonlinearities such as generation rate constraint (GRC) and governor dead band (GDB) as a provenance of physical constraints are taken into account in the model of the two-area multi-sources power systems to examine the ability of the proposed strategy for handling the practical challenges. The acceptability and novelty of the ALO-based IPID-SMC controller to solve the systems mentioned above are appraised in comparison with some recently reported approaches. The specifications of time-domain simulation disclose that the designed proposed controller provides a desirable level of performance and stability compared with other existing strategies. Furthermore, to check the robustness of the suggested technique, sensitivity analysis is fulfilled by varying the operating loading conditions and plant parameters within a particular tolerable range.

scholarly journals Parameter Optimization of Active Disturbance Rejection Controller Using Adaptive Differential Ant-Lion Optimizer

Algorithms ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 19
Author(s):  
Qibing Jin ◽  
Yuming Zhang
Keyword(s):  
Parameter Optimization ◽  
Disturbance Rejection ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Controller Design ◽  
Ant Lion Optimization ◽  
Active Disturbance Rejection ◽  
Lion Algorithm ◽  
Ant Lion ◽  
Lion Optimization Algorithm

Parameter optimization in the field of control engineering has always been a research topic. This paper studies the parameter optimization of an active disturbance rejection controller. The parameter optimization problem in controller design can be summarized as a nonlinear optimization problem with constraints. It is often difficult and complicated to solve the problem directly, and meta-heuristic algorithms are suitable for this problem. As a relatively new method, the ant-lion optimization algorithm has attracted much attention and study. The contribution of this work is proposing an adaptive ant-lion algorithm, namely differential step-scaling ant-lion algorithm, to optimize parameters of the active disturbance rejection controller. Firstly, a differential evolution strategy is introduced to increase the diversity of the population and improve the global search ability of the algorithm. Then the step scaling method is adopted to ensure that the algorithm can obtain higher accuracy in a local search. Comparison with existing optimizers is conducted for different test functions with different qualities, the results show that the proposed algorithm has advantages in both accuracy and convergence speed. Simulations with different algorithms and different indexes are also carried out, the results show that the improved algorithm can search better parameters for the controllers.

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