A novel Green Leaf‐hopper Flame optimization algorithm for competent frequency regulation in hybrid microgrids

2022 ◽  
Author(s):  
Subash Chandra Sahoo ◽  
Amar Kumar Barik ◽  
Dulal Chandra Das
Keyword(s):  
Optimization Algorithm ◽  
Green Leaf ◽  
Frequency Regulation ◽  
Leaf Hopper

Efficacy of certain insecticides in combination with neem against rice green leaf hopper and gundhi bug

2020 ◽  
Vol 82 (4) ◽  
pp. 806-808
Author(s):  
Shubhasree Dash ◽  
Sanjay Kumar Pradhan ◽  
Deepak Kumar Swain ◽  
Laxmi Narayan Mohapatra
Keyword(s):  
Green Leaf ◽  
Leaf Hopper

scholarly journals Optimal Voltage and Frequency Control of an Islanded Microgrid using Grasshopper Optimization Algorithm

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3191 ◽  
Author(s):  
Touqeer Ahmed Jumani ◽  
Mohd Wazir Mustafa ◽  
Madihah Md Rasid ◽  
Nayyar Hussain Mirjat ◽  
Zohaib Hussain Leghari ◽  
...  
Keyword(s):  
Power Quality ◽  
Optimization Algorithm ◽  
Pi Controller ◽  
Parameter Selection ◽  
Current Control ◽  
Control Architecture ◽  
Frequency Regulation ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization

Due to the lack of inertia and uncertainty in the selection of optimal Proportional Integral (PI) controller gains, the voltage and frequency variations are higher in the islanded mode of the operation of a Microgrid (MG) compared to the grid-connected mode. This study, as such, develops an optimal control strategy for the voltage and frequency regulation of Photovoltaic (PV) based MG systems operating in islanding mode using Grasshopper Optimization Algorithm (GOA). The intelligence of the GOA is utilized to optimize the PI controller parameters. This ensures an enhanced dynamic response and power quality of the studied MG system during Distributed Generators (DG) insertion and load change conditions. A droop control is also employed within the control architecture, alongside the voltage and current control loops, as a power-sharing controller. In order to validate the performance of the proposed control architecture, its effectiveness in regulating MG voltage, frequency, and power quality is compared with the precedent Artificial Intelligence (AI) based control architectures for the same control objectives. The effectiveness of the proposed GOA based parameter selection method is also validated by analyzing its performance with respect to the improved transient response and power quality of the studied MG system in comparison with that of the Particle Swarm Optimization (PSO) and Whales Optimization Algorithm (WOA) based parameter selection methods. The simulation results establish that the GOA provides a faster and better solution than PSO and WOA which resulted in a minimum voltage and frequency overshoot with minimum output current and Total Harmonic Distortion (THD).

scholarly journals Scenario of insect pests, predators and pollinators associated with crop plants in an agroforestry in Bangladesh

2019 ◽  
Vol 17 (1) ◽  
pp. 13-22
Author(s):  
MR Mia ◽  
MR Amin ◽  
H Rahman ◽  
MG Miah
Keyword(s):  
Relative Abundance ◽  
Insect Pests ◽  
Fruit Fly ◽  
Crop Plants ◽  
Green Leaf ◽  
Leaf Hopper ◽  
Pest Insects ◽  
Mealy Bug ◽  
Citrus Pests

The abundance of insect pests, predators and pollinators and status of pest insects associated with citrus, mango and pineapple crops grown in an agroforestry in Bangladesh was studied during July 2015 to June 2016. Twenty five species of insects belonging to 19 families in 5 orders were found as pest of citrus and their relative abundance varied from 2.4 to 13.4%. Among the citrus pests, green leaf hopper was most abundant, but whitefly, mealy bug, lemon butterfly and leaf minor were found as major pests. Fifteen species of insects under 13 families in 6 orders were found as pests of mango and their relative abundance varied from 0.5 to 82.6%, and hopper and fruit fly were found as major pests. Four species of insects belonging to 4 families in 3 orders were found as pest of pineapple and their relative abundance varied from 12.2 to 44.9%, and all were found as minor pests. There were 20 species of predator insects belonging to 13 families in 6 orders and their abundance ranged from 0.8 to 2.5/ 40 sweeps. In total 19 species of insects belonging to 12 families in 4 orders were found as pollinators and their abundance varied from 1.7 to 5.1/40 sweeps. The ants and honeybees were most abundant as predators and pollinators, respectively. SAARC J. Agri., 17(1): 13-22 (2019)

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