Experimental investigation and ANN modeling on improved performance of an innovative method of using heave response of a non-floating object for ocean wave energy conversion
Received date: 23 Jan 2013
Accepted date: 26 Mar 2013
Published date: 05 Sep 2013
Copyright
To convert wave energy into usable forms of energy by utilizing heaving body, heaving bodies (buoys) which are buoyant in nature and float on the water surface are usually used. The wave exerts excess buoyancy force on the buoy, lifting it during the approach of wave crest while the gravity pulls it down during the wave trough. A hydraulic, direct or mechanical power takeoff is used to convert this up and down motion of the buoy to produce usable forms of energy. Though using a floating buoy for harnessing wave energy is conventional, this device faces many challenges in improving the overall conversion efficiency and survivability in extreme conditions. Up to the present, no studies have been done to harness ocean waves using a non-floating object and to find out the merits and demerits of the system. In the present paper, an innovative heaving body type of wave energy converter with a non-floating object was proposed to harness waves. It was also shown that the conversion efficiency and safety of the proposed device were significantly higher than any other device proposed with floating buoy. To demonstrate the improvements, experiments were conducted with non-floating body for different dimensions and the heave response was noted. Power generation was not considered in the experiment to observe the worst case response of the heaving body. The device was modeled in artificial neural network (ANN), the heave response for various parameters were predicted, and compared with the experimental results. It was found that the ANN model could predict the heave response with an accuracy of 99%.
Srinivasan CHANDRASEKARAN , Arunachalam AMARKARTHIK , Karuppan SIVAKUMAR , Dhanasekaran SELVAMUTHUKUMARAN , Shaji SIDNEY . Experimental investigation and ANN modeling on improved performance of an innovative method of using heave response of a non-floating object for ocean wave energy conversion[J]. Frontiers in Energy, 2013 , 7(3) : 279 -287 . DOI: 10.1007/s11708-013-0268-4
| 1 |
Amarkarthik A, Chandrasekaran S, Sivakumar K, Sinhmar H. Laboratory experiment on using non-floating body to generate electrical energy from water waves. Frontiers in Energy, 2012, 6(4): 361–365
|
| 2 |
De O, Falcão A F. Wave energy utilization: a review of the technologies. Renewable & Sustainable Energy Reviews, 2009, 14(3): 899–918
|
| 3 |
Falnes J. A review of wave-energy extraction. Marine Structures, 2007, 20(4): 185–201
|
| 4 |
Eriksson M, Waters R, Svensson O, Isberg J, Leijon M. Wave power absorption: experiments in open sea and simulation. Journal of Applied Physics, 2007, 102(8): 084910-1–084910-5
|
| 5 |
Elwood D, Yim S C, Prudell J, Stillinger C, von Jouanne A, Brekken T, Brown A, Paasch R. Design, construction and ocean testing of a taut-moored dual-body wave energy converter with a linear generator power take-off. Renewable Energy, 2010, 35(2): 348–354
|
| 6 |
Agamloh E B, Wallace A K, von Jouanne A. A novel direct-drive ocean wave energy extraction concept with contact-less force transmission system. Renewable Energy, 2008, 33(3): 520–529
|
| 7 |
Polinder H, Damen M E C, Gardner F. Linear PM generator system for wave energy conversion in the AWS. IEEE Transactions on Energy Conversion, 2004, 19(3): 583–589
|
| 8 |
Al-Habaibeh A, Su D, McCague J, Knight A. An innovative approach for energy generation from waves. Energy Conversion and Management, 2010, 51(8): 1664–1668
|
| 9 |
Vantorre M, Banasiak R, Verhoeven R. Modelling of hydraulic performance and wave energy extraction by a point absorber in heave. Applied Ocean Research, 2004, 26(1-2): 61–72
|
| 10 |
Kalogirou S A. Applications of artificial neural networks in energy systems: a review. Energy Conversion and Management, 1999, 40(10): 1073–1087
|
| 11 |
Deo M C, Sridhar Naidu C. Real time wave forecasting using neural networks. Ocean Engineering, 1998, 26(3): 191–203
|
| 12 |
Pao H T. Forecasting electricity market pricing using artificial neural networks. Energy Conversion and Management, 2007, 48(3): 907–912
|
| 13 |
Tsai J C, Tsai C H. Wave measurements by pressure transducers using artificial neural networks. Ocean Engineering, 2009, 36(15-16): 1149–1157
|
| 14 |
Carballo R, Iglesias G. A methodology to determine the power performance of wave energy converters at a particular coastal location. Energy Conversion and Management, 2012, 61: 8–18
|
/
| 〈 |
|
〉 |