Economic emission dispatch of thermal generating units using genetic algorithm technique

Vennila, H.; Malini, B.G.; Jeba, V. Evangelin; Prakash, Tapan

doi:10.1504/ijenm.2011.043797

Cited by 4 publications

(4 citation statements)

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“…To satisfy constraint limitation and disallow the workable area, the individual population's fitness performance is measured using (9), which is the combination of objective function equation between (2) and PFS linked with related constraints. This evaluation feature is used to obtain the smallest cost generation value while fulfilling the limitation of equality and non-equality constraint problem, as stated in (4)(5)(6)(7)(8).…”

Section: Penalty Factor Strategy (Pfs)mentioning

confidence: 99%

“…Finally, the new generated agents are set to the maximum and minimum boundary shown in (6). Then, all agents are evaluated using the process details in step 3.2 and update the position of the new best group agent.…”

Section: New Population Generation and Evaluationmentioning

confidence: 99%

“…The conventional techniques have a higher probability of becoming trapped in local minima solution due to the complex fuel cost function problem related to the highly nonlinear characteristic of present power generating units such as ramp rate limit and prohibited operating zones. Nowadays, in order to handle the nonlinear fuel cost function, many advanced optimization techniques based on nature-inspired meta-heuristic has been implemented on ELD such as Genetic Algorithm [6], Particle Swarm Optimization [7], Artificial Bee Colony [8,9], and Ant Colony Optimization [10], Cuckoo Search Algorithm [11,12], to name a few. In 2014, Mohseni, Gholami, Zarei and Zadeh [13] introduced a new meta-heuristic algorithm called Competition Over Resources (COR), inspired by a group of animal communities which compete for resources.…”

Section: Introductionmentioning

confidence: 99%

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The performance of COR optimisation using different constraint handling strategies to solve ELD

Azmi

Zali

Abdullah

et al. 2020

IJEECS

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This research compares the performance of Competitive Over Resources (COR) optimization method using a different type of constraint handling strategy to solve the economic load dispatch (ELD) problem. Previously, most research focused on proposing various optimization techniques using the Penalty Factor Strategy (PFS) to search for a better global optimum. The issue using the penalty factor is that it is difficult to find the correct tune of constant value that influences the algorithm to find the solution. The other technique is using Feasible Solution Strategy (FSS), the idea of which is to locate the infeasible particle to the feasible solution and avoid being trapped by the unsuccessful condition of constraint. This paper investigates the performance of PFS and FSS on the COR optimization method for solving ELD. Both strategies have been tested on two standard test systems to compare the performance in terms of a global solution, robustness and convergence. The simulation shows that FSS is a better solution compared to PFS.

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Section: Penalty Factor Strategy (Pfs)mentioning

confidence: 99%

Section: New Population Generation and Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The performance of COR optimisation using different constraint handling strategies to solve ELD

Azmi

Zali

Abdullah

et al. 2020

IJEECS

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“…This effect badly on the convergence side. Due to this, it was a need to explore new methodologies (Vennila and Ruban Deva Prakash, 2011). Exploring genetic algorithms (Chiang, 2005) on the EELD side provided much better convergence with good results.…”

Section: Introductionmentioning

confidence: 99%

Combined economic and emission dispatch using whale optimisation algorithm

Faseela¹,

Vennila

2019

IJENM

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This paper highlight the use of latest whale optimisation meta heuristic algorithm for solving economic dispatch problem efficiently. This is used to solve the combined economic and emission dispatch problems for standard three generators system and 30 bus IEEE system. The whale optimisation algorithm was found to provide optimum results with easy convergence in comparison with other algorithms like PSO algorithm. Fuel cost and emission costs are combined to derive better result for economic dispatch. For checking the effectiveness of the algorithm, the results obtained using the same are compared with the results of particle swarm optimisation (PSO) and analysed the same against minimum generation cost and easy convergence. The results are found to be excellent for the systems considered.

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Ant Lion Optimization for Solving Combined Economic and Emission Dispatch Problems

Vennila

Rajesh²

2022

Machine Learning and Autonomous Systems

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Economic emission dispatch of thermal generating units using genetic algorithm technique

Cited by 4 publications

References 0 publications

The performance of COR optimisation using different constraint handling strategies to solve ELD

The performance of COR optimisation using different constraint handling strategies to solve ELD

Combined economic and emission dispatch using whale optimisation algorithm

Ant Lion Optimization for Solving Combined Economic and Emission Dispatch Problems

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