Identification of Park Effect Probability in Wave Energy Conversion System using Multi Criteria Decision Making Method (AHP) and Neural Network Model (GMDH Shell)
Satyabrata Saha1, Mrinmoy Majumder2, Manish Pal3

1Mr. Satyabrata Saha, Research Scholar, Department of School of Hydro Informatics Engineering, NIT Agartala Jirania, Tripura (W), India.
2Dr. Mrinmoy Majumder,Assistant Professor, Department of School of Hydro Informatics Engineering, NIT Agartala Jirania, Tripura (W), India.
3Dr. Manish Pal, Associate Professor, Department of Civil Engineering, NIT Agartala Jirania, Tripura (W), India.
Manuscript received on November 21, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 5167-5173  | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4061129219/2019©BEIESP | DOI: 10.35940/ijeat.B4061.129219
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Abstract: The present research work demonstrates the trend of Park Effect to the Wave Energy Conversion system or in wave energy converter. The Park Effect occurred due to various reasons in a real field application of Wave Energy Conversion. Park Effect occurred in wind energy as well as wave energy. All possible factors are considered to find out the Park Effect. To analyze the Park Effect probability, Analytical Hierarchy Process (AHP) is used, from the result a model is generated through Neural Network software named GMDH Shell. There are significant uncertainties arising in particular from the lack of field tested result to calculate the Park Effect proximity on the devices. However, applying various hypotheses for design and physical parameters, it was found that the benefits of Park Effect influenced factors are all non-beneficiary to Park Effect trend. After all the calculations it can predict the proximity of the Park Effect in a Wave Energy Conversion system.
Keywords: AHP; Group Method of Data Handling (GMDH); Multi Criteria Decision Making; Park Effect; Wave Energy; Wave Energy Converter.