Reducing the Electrical Consumption in the Humidity Control Process for Electric Cells using an Intelligent Fuzzy Logic Controller

Abstract

The electrical energy distribution uses a huge network to cover the urbanized areas. The network distribution incorporates an important number of electrical cells that ensure the energy transformation. These cells play a fundamental role to ensure a permanent feeding. Thus, the performance of these cells must be optimized. The main problem that affects these cells is the inside humidity that should be controlled permanently to prevent serious damage and power failure. The presented work proposes the use of a powerful intelligent Fuzzy Logic Controller that can online adapt their internal parameters according to the actually state of the controlled plant and auto-learn from the behavior of the plant how the current humidity level can be decreased. The used controller can stabilize the humidity inside the cells within the recommended range by controlling a set of heating resistances installed inside these cells and in the same time ensuring valuable advantages for the electrical energy distribution company. Unlike the rest of the controllers that are used to stabilize moisture. The intelligent controller used in these papers ensures a very precise control with very low power consumption which trains a very significant energy savings in each electrical cell. Knowing that the distribution network incorporates a very large number of electrical cells, the final savings balance would be a very high amount of energy that can be presented economically with significant savings on the electricity bills.

Authors and Affiliations

Rafik Lasri, Larbi Choukri, Mohammed Bouhorma, Ignacio Rojas, Héctor Pomares

Keywords

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  • EP ID EP397354
  • DOI 10.14569/IJACSA.2016.071243
  • Views 76
  • Downloads 0

How To Cite

Rafik Lasri, Larbi Choukri, Mohammed Bouhorma, Ignacio Rojas, Héctor Pomares (2016). Reducing the Electrical Consumption in the Humidity Control Process for Electric Cells using an Intelligent Fuzzy Logic Controller. International Journal of Advanced Computer Science & Applications, 7(12), 329-336. https://europub.co.uk/articles/-A-397354