Optimal Electric-Power Distribution and Load-Sharing on Smart-Grids: Analysis by Artificial Neural Network
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2018, Vol 18, Issue 0
Abstract
This study refers to developing an electric-power distribution system with optimal/suboptimal load-sharing in the complex and expanding metro power-grid infrastructure. That is, the relevant exercise is to indicate a smart forecasting strategy on optimal/suboptimal power-distribution to consumers served by a smart-grid utility. An artificial neural network (ANN) is employed to model the said optimal power-distribution between generating sources and distribution centers. A compatible architecture of the test ANN with ad hoc suites of training/prediction schedules is indicated thereof. Pertinent exercise is to determine smartly the power supported on each transmission-line between generating to distribution-nodes. Further, a “smart” decision protocol prescribing the constraint that no transmission-line carries in excess of a desired load. An algorithm is developed to implement the prescribed constraint via the test ANN; and, each value of the load shared by each distribution-line (meeting the power-demand of the consumers) is elucidated from the ANN output. The test ANN includes the use of a traditional multilayer architecture with feed-forward and backpropagation techniques; and, a fast convergence algorithm (deduced in terms of eigenvalues of a Hessian matrix associated with the input data) is adopted. Further, a novel method based on information-theoretic heuristics (in Shannon’s sense) is invoked towards model specifications. Lastly, the study results are discussed with exemplified computations using appropriate field data.
Authors and Affiliations
Dolores De Groff, Roxana Melendez, Perambur Neelakanta, Hajar Akif
Keywords
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- EP ID EP649748
- DOI 10.24297/ijct.v18i0.8059
- Views 164
- Downloads 0
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