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- W2787177014 abstract "Lagrange multiplier method also known as λ-iteration method has been in use to find the solution of the economic load dispatch problem for many years. Though it produces results with great accuracy but it suffers from the disadvantage of convergence as it is highly sensitive to the initial value of λ and at times takes more time to produce results. To overcome this drawback, in this paper an innovative technique to solve the ELD problem, by hybridization of artificial neural network (ANN) and LMM is proposed. To formulate the problem, generation cost is expressed as a function of active power by exponential functions. The equality constraint of power balance and inequality constraint that fix the maximum and minimum active power are duly considered. ANN trained by backpropagation algorithm is used to find the optimal value of λ which is then used to find solutions using LMM. Training data, i.e., input and target patterns for ANN are obtained by LMM. Using proposed hybrid method, λ-iterations are eliminated and promising results are obtained in much less computation time. Hence, the proposed method can be useful in real time solution for seeking online solution of ELD problems." @default.
- W2787177014 created "2018-02-23" @default.
- W2787177014 creator A5038053221 @default.
- W2787177014 date "2017-12-01" @default.
- W2787177014 modified "2023-09-27" @default.
- W2787177014 title "Hybridization of artificial neural network and lagrange multiplier method to solve economic load dispatch problem" @default.
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- W2787177014 doi "https://doi.org/10.1109/ictus.2017.8286063" @default.
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