NEW DEVELOPMENT OF ANALYSIS TOOL FOR OPTIMIZING GENERATION COST WITH GAS EMISSION VIA AN ELECTROMAGNETISM LIKE ALGORITHM

2016 ◽  
Vol 78 (6-3) ◽  
Author(s):  
F.Y.C. Albert ◽  
S.P. Koh ◽  
C. P. Chen ◽  
S. K. Tiong
Keyword(s):  
Power Generation ◽  
Objective Function ◽  
Environmental Concern ◽  
Economic Dispatch ◽  
Complex Problem ◽  
Analysis Tool ◽  
New Development ◽  
Generation Cost ◽  
Electric Power Generation Systems ◽  
Power Generation Systems

This paper addresses the preliminary new development results of the evolutionary algorithm technique to optimize the formulated problems incorporating the generation cost with emission gas as objective function or constraints. The power generation cost with emission gas are a complex problem which also the major concerns in electric power generation systems in the Environmental or Economic Dispatch Problems (EDP). Thus, due to environmental concern the electrical utilities required to minimize the emission level while optimizing the thermal generating units at a minimum generating cost and hence, satisfying the load demand and the emissions. In this work the electromagnetism-Like algorithm (EML) has been employed for optimizing generation cost and emission constraints economic dispatch problem. The proposed decision analysis tool software in this work will optimize the generation cost with emission gas objective function. The best generation cost with emission gas solution are obtained from different fuel technology via the developed software. 

scholarly journals Optimal economic dispatch of power generation solution using lightning search algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 371
Author(s):  
Murad Yahya Nassar ◽  
Mohd Noor Abdullah ◽  
Asif Ahmed Rahimoon
Keyword(s):  
Power Generation ◽  
Power System ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Optimal Solution ◽  
Fuel Price ◽  
Solution Quality ◽  
Generation Cost

Economic dispatch (ED) is the power demand allocating process for the committed units at minimum generation cost while satisfying system and operational constraints. Increasing cost of fuel price and electricity demand can increase the cost of thermal power generation. Therefore, robust and efficient optimization algorithm is required to determine the optimal solution for ED problem in power system operation and planning. In this paper the lightning search algorithm (LSA) is proposed to solve the ED problem. The system constraints such as power balance, generator limits, system transmission losses and valve-points effects (VPE) are considered in this paper. To verify the effectiveness of LSA in terms of convergence characteristic, robustness, simulation time and solution quality, the two case studies consists of 6 and 13 units have been tested. The simulation results show that the LSA can provide optimal cost than many methods reported in literature. Therefore, it has potential to solve many optimization problems in power dispatch and power system applications.

Application of Genetic Algorithm for Solving Optimum Power Flow Problems

2013 ◽  
Vol 6 (2) ◽  
pp. 62-71 ◽  
Author(s):  
H. Vennila ◽  
T. Ruban Deva Prakash ◽  
B.G. Malini ◽  
M.S. Birundha ◽  
V. Evangelin Jeba ◽  
...  
Keyword(s):  
Information Exchange ◽  
Power Flow ◽  
Economic Dispatch ◽  
General Purpose ◽  
Artificial Chromosomes ◽  
Flow Problems ◽  
Load Demand ◽  
Electric Power Generation Systems ◽  
Power Generation Systems ◽  
Survival Of The Fittest

An efficient and optimum economic operation and planning of electric power generation systems is very important. The basic requirement of power economic dispatch (ED) is to generate adequate electricity to meet load demand at the lowest possible cost under a number of constrains. Genetic Algorithms (GA) represents a class of general purpose stochastic search techniques which simulate natural inheritance by genetics. In this paper, the principles of genetics involving natural selection and evolutionary computing applied for producing an economic dispatch. By simulating “Survival of the fittest” among chromosomes, the optimal chromosome is searched by randomized information exchange. In every generation a new set of artificial chromosomes is created using bits and pieces of the fittest of old ones while randomized.

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