Genetic algorithms based economic dispatch with application to coordination of nigerian thermal power plants

2005 ◽  
Author(s):  
G.A. Bakare ◽  
U.O. Aliyu ◽  
G.K. Venayagamoorthy ◽  
Y.K. Shu'aibu
Keyword(s):  
Genetic Algorithms ◽  
Power Plants ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Thermal Power Plants

scholarly journals Taking into account the constraints in power system mode optimization by genetic algorithms

2021 ◽  
Vol 264 ◽  
pp. 04045
Author(s):  
Tulkin Gayibov ◽  
Behzod Pulatov
Keyword(s):  
Genetic Algorithms ◽  
Power System ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Functional Constraints ◽  
The Past ◽  
Powerful Approach ◽  
System Mode ◽  
The Given

Over the past decades, many publications on the use of genetic algorithms, which offer a new and powerful approach for solving the problem of power system mode optimization, have appeared. Despite this, the issues of effectively taking into account various constraints when solving such problems with genetic algorithms remain opened. In this regard, this article proposes an algorithm for optimizing power system modes by genetic algorithm, taking into account functional constraints in the form of equalities and inequalities by various penalty functions. The results of effectiveness research of the given algorithm in the example of optimization of 8-nodal power system with four thermal power plants and three lines with controlled power flows are presented.

Neural-net based real-time economic dispatch for thermal power plants

1996 ◽  
Vol 11 (4) ◽  
pp. 755-761 ◽  
Author(s):  
M. Djukanovic ◽  
M. Calovic ◽  
B. Milosevic ◽  
D.J. Sobajic
Keyword(s):  
Real Time ◽  
Power Plants ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Thermal Power Plants ◽  
Neural Net

Modeling and Optimization Research of CFB-FGD Based on Improved Genetic Algorithms and BP Neural Network

2012 ◽  
Vol 610-613 ◽  
pp. 1601-1604 ◽  
Author(s):  
Zhi Bo Ren ◽  
Lei Sun ◽  
Yao Deng
Keyword(s):  
Neural Network ◽  
Genetic Algorithms ◽  
Bp Neural Network ◽  
Flue Gas ◽  
Power Plants ◽  
Thermal Power ◽  
Flue Gas Desulfurization ◽  
Operating Costs ◽  
Thermal Power Plants ◽  
Bp Neural Network Model

In order to improve the efficiency of CFB-FGD (circulated fluidized bed for flue gas desulfurization) in many thermal power plants, this paper used the improved genetic algorithms and BP neural network to model and optimize the operation of CFB-FGD. First, this paper build BP neural network model to simulate CFB-FGD. Then, based on this model, we used the improved genetic algorithms to optimize CFB-FGD. The results can help improve the efficiency of CFB-FGD and decrease enterprise operating costs.

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