scholarly journals Grasshopper Optimization Algorithm on Combined Economic Emission Dispatch Problem Involving Cubic Functions

2019 ◽  
Vol 9 (1) ◽  
pp. 808-817
Keyword(s):  
Optimization Algorithm ◽  
Electric Power System ◽  
Test Cases ◽  
Fuel Cost ◽  
Unit System ◽  
Penalty Factor ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

In this paper, grasshopper optimization algorithm is presented to resolve the combined economic emission dispatch (CEED) problem involving cubic functions considering power flow constraints. Electric power system wants to satisfy its customers load demand with minimum fuel cost and emission. Fuel cost and emission has instantly association with energy cost. In CEED problem, the price penalty factor occupies a cardinal role to fetch the optimal results. The various types of price penalty factor available in the literature are analyzed to determine the optimal one for the test cases considered. The test systems used in this CEED problem are 3 unit system considering transmission loss and 13 unit system considering valve point effects. The leading requirement in both the test cases is to optimize the total cost, fuel cost and emission. The numerical and statistical results affirm the high degree of the solution founded by GOA and its superiority is compared with already existing algorithms employed in solving CEED problems

scholarly journals Dynamic Combined Economic Emission Dispatch Including Wind Generators by Real Coded Genetic Algorithm

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Optimization Technique ◽  
Electric Power System ◽  
Fuel Cost ◽  
Renewable Source ◽  
Wind Generators ◽  
Real Coded Genetic Algorithm ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

With the growing environmental depletion, the shift in the focus towards minimizing the emissions of gases released in the conventional generators and further incorporation of a cleaner alternate renewable source of energy such as wind or solar to the existing system is of utmost importance. The research paper aims to build an environmentally resilient electric power system. Real coded genetic algorithm- powerful optimization technique is employed to solve the dynamic combined economic emission dispatch i.e. DCEED strategy for two proposed algorithm. The first proposed DCEED algorithm includes fuel cost of only conventional generators while in the second algorithm along with conventional generators, wind powered generators with varying power output characteristic is added. A comparative analysis of both the algorithms in terms of total combined cost, emission level and fuel cost is taken into account and it is observed that in spite of wind uncertainty the proposed method is more economical.

scholarly journals Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2037 ◽  
Author(s):  
Shahbaz Hussain ◽  
Mohammed Al-Hitmi ◽  
Salman Khaliq ◽  
Asif Hussain ◽  
Muhammad Asghar Saqib
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Power Plant ◽  
Particle Swarm ◽  
Computational Time ◽  
Fuel Cost ◽  
Swarm Optimization ◽  
Penalty Factor ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

This paper presents the optimization of fuel cost, emission of NOX, COX, and SOX gases caused by the generators in a thermal power plant using penalty factor approach. Practical constraints such as generator limits and power balance were considered. Two contemporary metaheuristic techniques, particle swarm optimization (PSO) and genetic algorithm (GA), have were simultaneously implemented for combined economic emission dispatch (CEED) of an independent power plant (IPP) situated in Pakistan for different load demands. The results are of great significance as the real data of an IPP is used and imply that the performance of PSO is better than that of GA in case of CEED for finding the optimal solution concerning fuel cost, emission, convergence characteristics, and computational time. The novelty of this work is the parallel implementation of PSO and GA techniques in MATLAB environment employed for the same systems. They were then compared in terms of convergence characteristics using 3D plots corresponding to fuel cost and gas emissions. These results are further validated by comparing the performance of both algorithms for CEED on IEEE 30 bus test bed.

Chaotic Singer Grasshopper Optimization Algorithm for solving Combined Economic and Emission Dispatch

2021 ◽  
Author(s):  
Md. Ashaduzzaman Niloy ◽  
Faisal Hossain Reevu ◽  
Abrar Yeaser ◽  
Rubaiyat Islam Shupty ◽  
Abrar Shahriar Pramanik
Keyword(s):  
Optimization Algorithm ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Emission Dispatch

Invasive Weed Optimization for Combined Economic and Emission Dispatch Problems

2014 ◽  
Vol 5 (1) ◽  
pp. 1-18 ◽  
Author(s):  
B.K. Panigrahi ◽  
Manjaree Pandit ◽  
Hari Mohan Dubey ◽  
Ashish Agarwal ◽  
Wei-Chiang Hong
Keyword(s):  
Standard Test ◽  
Test Cases ◽  
Invasive Weed Optimization ◽  
Fuel Cost ◽  
Invasive Weed ◽  
Penalty Factor ◽  
Optimum Solution ◽  
Operational Constraints ◽  
Emission Dispatch

In this paper, Invasive Weed Optimization (IWO) algorithm is used to find the optimum solution of Combined Economic Emission Dispatch (CEED) problem. The main objective is to minimize the fuel cost as well as emission level, while satisfying the power demand and associative operational constraints. The bi-objective problem is made to a single objective function using the price penalty factor. Since, the minimize fuel cost and emission are contradictory to each other so to get the optimum compromise solution, weighing factor is used. IWO is applied on three different standard test cases i.e. 6 generators, 10 generators and 40 generators system. To measure the effectiveness and quality of solution, test results have been compared with other existing relevant approaches.

Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm

2021 ◽  
Author(s):  
Betül Sultan Yildiz ◽  
Nantiwat Pholdee ◽  
Sujin Bureerat ◽  
Ali Riza Yildiz ◽  
Sadiq M. Sait
Keyword(s):  
Robust Design ◽  
Optimization Algorithm ◽  
Robot Gripper ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization
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