scholarly journals Research on Control Parameters for Voltage Source Inverter Output Controllers of Micro-Grids Based on the Fruit Fly Optimization Algorithm

2019 ◽  
Vol 9 (7) ◽  
pp. 1327 ◽  
Author(s):  
Runnan Dong ◽  
Shi Liu ◽  
Geng Liang
Keyword(s):  
Dynamic Response ◽  
Optimization Algorithm ◽  
Reactive Power ◽  
Control Level ◽  
Fruit Fly ◽  
Fruit Fly Optimization Algorithm ◽  
Control Methods ◽  
Fruit Fly Optimization ◽  
Micro Grid ◽  
Micro Grids

Due to the strong intermittency of micro-resources, the poor grid-tied power quality, and the high generation-demand sensitivity in micro-grids, research into the control methods of micro-grid systems has always been a notable issue in the field of micro-grids. The inverter is the core control equipment at the primary control level of the micro-grid, and the key factors affecting its output performance can be divided into three categories: control methods, hardware configuration, and control parameter design. Taking the classical active and reactive power (P-Q) control structure and the three-phase, two-stage inverter topology model as an example, this paper designs a parameter for offline tuning, and an online self-tuning optimization method for an inverter control system based on the fruit fly optimization algorithm (FOA). By simulating and comparing the inverter controllers with non-optimized parameters in the same object and environment, the designed parameter tuning method is verified. Specifically, it improves the dynamic response speed of the inverter controller, reduces the steady-state error and oscillation, and enhances the dynamic response performance of the controller.

scholarly journals Solving optimal reactive power problem by enhanced fruit fly optimization algorithm and status of material algorithm

2020 ◽  
Vol 9 (2) ◽  
pp. 100
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Optimization Algorithm ◽  
Reactive Power ◽  
Collision Operator ◽  
Fruit Fly ◽  
Test System ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization ◽  
Vector Operator ◽  
Solid Liquid ◽  
Power Problem

<div data-canvas-width="397.2735184438622">This paper proposes enhanced fruit fly optimization algorithm (EFF) and status of material algorithm (SMA) to solve the optimal reactive power problem. Fruit fly optimization algorithm is based on the food finding behavior of the fruit fly. There are two steps in food finding procedure of fruit fly: At first it smells the food source by means of osphresis organ and it flies in that direction; afterwards, when it gets closer to the food site, through its sensitive vision it will find the food. At the beginning of the run by diminishing the inertia weight from a large value to a small value, will lead to enhance the global search capability and more local search ability will be in process the end of the run of the EFF algorithm. Then SMA is projected to solve the problem. Three state of material are solid, liquid, and gas. For evolution procedure direction vector operator assign a direction to every molecule consecutively to guide the particle progression. Collision operator imitates the collisions factor in which molecules are interacting to each other. Proposed enhanced EFF, SMA has been tested in standard IEEE 30 bus test system and simulation results show the projected algorithms reduced the real power loss considerably.</div>

Research on Enhancement Technology of Conveyor Belt Fault Images Based on Fruit Fly Optimization Algorithm

2014 ◽  
Vol 8 (1) ◽  
pp. 685-689
Author(s):  
Chunqing Ye ◽  
Changyun Miao ◽  
Xianguo Li ◽  
Yanli Yang
Keyword(s):  
Optimization Algorithm ◽  
Detection System ◽  
Fruit Fly ◽  
Conveyor Belt ◽  
Recognition Algorithm ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization ◽  
Wire Ropes ◽  
Fault Recognition ◽  
Steel Cord

In this research, we studied the fault recognition algorithm of steel cord conveyor belt, and obtained the wire ropes image by adopting the detection system of steel cord conveyor belt, so that the fault recognition algorithm of steel cord conveyor belt was proposed based on Fruit fly optimization algorithm. As we know that the fruit fly optimization algorithm is used for fault detection of the processing steel cord conveyor belt image and for obtaining the fault image. In the MATLAB environment, the algorithm process was designed and verified in terms of the effectiveness and accuracy. The experimental results show that with fast speed and high accuracy in detecting the fault image of steel cord conveyor belt rapidly and accurately, and in classifying scratch from fracture the proposed algorithm is suitable for the fault recognition of steel cord conveyor belt automatically.

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