Wave Energy Atlas in Vietnam

Transcription

1 Wave Energy Atlas in Vietnam Nguyen Manh Hung, Duong Cong Dien 1 1 Institute of Mechanics, 264 Doi Can Str. Hanoi, Vietnam nmhungim@gmail.com; duongdienim@gmail.com Abstract Vietnam has achieved remarkable economic progress during the last decade. With the rapid growth of economy, the demand on energy consumption in production and life are also increasing so the energy is facing with some problems, especially the limitation of energy consumption capacity, energy resources etc. While Vietnam is richly endowed with renewable energy resources, which can be used to meet the local energy needs, to solve the energy problems. One of the renewable energy alternative sources is wave energy. In order to study the wave energy, the first most important step is to establish the wave energy atlas to quantify the potential of wave energy at a regional scale across the limit of the South East China sea and coastal zone of Vietnam. The paper consists of three parts, at first data sources of the wind and wave information have been determined and then the second part is dealing with the wave energy computations. A wave energy atlas has been presented in the last part. The atlas is designed to provide a useful reference to assist decision maker in planning, choosing the wave energy conversion system of exploitation of wave energy in Vietnam. Keywords: Marine renewable energy resources, wind and wave information, wave hind cast modeling, wave energy atlas. Introduction Vietnam has achieved remarkable economic progress during the last decade. With the rapid growth of economy, the demand on energy consumption in production and life are also increasing so the energy is facing with some problems, especially the limitation of energy consumption capacity, energy resources etc. While Vietnam is richly endowed with renewable energy resources, which can be used to meet the local energy needs, to solve the energy problems. One of the renewable energy alternative sources is wave energy. 1. Data sources For the research and development of wave energy, it is very important to do the fist step: to estimate the wave energy resources in the coastal zone of Vietnam. The statistics of the wave climate are fundamental influences on all the steps of research and exploiting the wave energy as cost-efficient design, energy production and survival. The statistics of the wave climate can be obtained by two ways: the direct wave observation and the wave computation. Recent research has been advanced the new high-technology of wave observation and mathematical model for wave hind cast and forecast to get the reliable wave climate in the sea. In the technology of wave observation, the satellite technology offers the best potential for accurate measurement of wave height, period and direction. Using the wave data observed by satellite the wave energy potential have been computed for some place in the South China sea (see figure 1). Figure 1: Potential of wave energy estimated by satellite wave data (Harald E. Krogstad et al. 1999) [1]. Because the satellite wave observation data is not synchronic by the time and space and not cover all the South China sea especially the coastal areas of Vietnam where is considered as the best places for wave energy exploitation the mathematical model for wave hind cast is the best way to get the wave climate for the computation of wave energy. The input for the wave model is the wind data which is provided from the available data archive from Japan Meteorological Agency (JMA). The wind data covers 5 years period

2 from 2002 to Depths were developed from Vietnam Navy maps of the East Sea and neighbor seas with the accuracy of 0.1m. 2. Wave energy computation - Wave parameters computation: The wave model are based on a 2 nd generation spectral model SWAN [2]. The grid for wave modeling is latitude and longitude with the integration domain extending from -1 0 N to 23 0 N and 99 0 E to E (97x 81 grid points according to latitude and longitude respectively. The wave spectrum is discretized by 40 frequencies that are logarithmically spaced from Hz to 1.0 Hz at intervals of f/f=0.1 corresponding to the wave period between 1 and to 22 seconds. The wave propagation directions are 72 with the span of in 5 0 increments. The SWAN has been calibrated by the wave data collected at the VietsovPetro oil platform MSP-1 ( E, N) during the passage across the South China sea of a storm named Muifa November The fig, 1 depicts the grid for wave model with the position of the oil platform and twenty points around the coastline of Vietnam for verification of the wave energy computations. By varying some of the physical processes formulations of Janssen and Komen, the most important coefficients for accurate model calibration were determined. While the sensitivity of the model not depends so much on friction coefficients of wind wave or swell, formulations for energy dissipation due to white capping play important role on modeling wave height. In the Komen formulation, the effect of this energy dissipation is greater than the Janssen formulation so it was chosen for further evaluation. The better agreement with the field measurement at MSP-1 is the SWAN run with the double decreased of the default coefficient of energy dissipation (CDS2= ) [3]. At first the wind data from JMA used for wave computation have been checked. Well agreement between measured wind (10m) at two islands in the South China sea (see fig. 1) and satellite wind has been demonstrated in the figures 3 and 4 [4]. Figure 3: Comparison of satellite and measured wind velocities at the Bach Long Vi island (Tonkin gulf) for 2003 Figure 4: Comparison of satellite and measured wind velocities at the Truong Sa island for 2005 In order to verify the wave model, the wave heights have been compared with the recorded wave height at MSP-1 station (see fig. 1). The results of computed and measured wave heights at MSP-1 during October - December and July December 2001 which are represented for Northeast and Southwest monsoon monsoons in the South China sea were compared to judge the modeling performance (see figs 5 and 6) [4] Hs-measured Hs-computed Date (GMT) 1/1/02 0:00 1/6/02 0:00 1/11/02 0:00 1/16/02 0:00 1/21/02 0:00 1/26/02 0:00 1/31/02 0:00 2/5/02 0:00 2/10/02 0:00 2/15/02 0:00 2/20/02 0:00 2/25/02 0:00 3/2/02 0:00 3/7/02 0:00 3/12/02 0:00 3/17/02 0:00 Hs (m) 3/22/02 0:00 3/27/02 0:00 4/1/02 0:00 Figure 2: The wave computation grid for the South China Sea [4]. Figure 5: Comparison of computed and measured wave heights at the MSP-1 station during NE monsoon season 2002

3 3.50 Hs-measured Hs-computed 25 Swan Wave Watch Hs (m) kw/m Date (GMT) 7/1/02 0:00 7/6/02 0:00 7/11/02 0:00 7/16/02 0:00 7/21/02 0:00 7/26/02 0:00 7/31/02 0:00 8/5/02 0:00 8/10/02 0:00 8/15/02 0:00 8/20/02 0:00 8/25/02 0:00 8/30/02 0:00 9/4/02 0:00 9/9/02 0:00 9/14/02 0:00 9/19/02 0:00 9/24/02 0:00 9/29/02 0: Figure 6: Comparison of computed and measured wave heights at MSP-1 station during SW monsoon season 2002 The comparisons show rather good fitting between computed and measured wave heights, the same agreements have been got for the wave periods. - Wave power computation The quantification of the power transmitted by a wave moving across the sea surface was calculated by the following expression [4]: g 2 Po T e H s 64 where: Pw = wave power (W) per meter wave crest ρ = water density (kg/m 3 ) g = acceleration due to gravity (m/s) Hs = significant wave height (m) Te = wave energy period (s) which is determined by the period of peak spectrum by the expression: Te 0. 9T p Based on about mentioned expressions, it is clear that all the accurate of the wave power computation will be depended by the accurate of wave parameters (wave heights and periods). In order to verify the wave power computation the wave parameters computed by WAVEWATCH-III using the wind input from NCEP (fpt:/fpt.ifremer.fr/ifremer.ma) for the same period of time ( ) also have been used as input for the wave power computation. Two wave power results calculated by the different wave models with different wind data inputs are compared at 20 points situated along the coastline of Vietnam (see fig. 1). The results shown in the figs 7 and 8 which belongs to the Northeast and Southwest monsoons seasons means, generally, that the wave data obtained by SWAN model should be consider as a reliable qualitative data for wave power computation. The wave power computation procedure is as follow: - To obtain wave parameters by SWAN model; - To analyze the wave climate: average wave heights, period and direction by monthly, seasonal and annual period; - To compute the wave power by about mentioned formulas; - Mapping the wave energy atlas by monthly, seasonal and annual periods. 2 Figure 7: Comparison of wave power computed by different wave input data for the Northeast monsoon season kw/m Swan Wave Watch Figure 8: Comparison of wave power computed by different wave input data for the Southwest monsoon season 3. A wave energy atlas The wave heights and wave energy atlas during Northeast monsoon, Southwest monsoon season and annual are shown in the figures 9a,b; 10a,b; and 11a,b [4]. Figure 9a: Wave height for Northeast season (November, December, January and February)

4 Figure 9b: Wave energy for Northeast season (November, December, January and February) Figure 11a: Yearly wave height Figure 10a: Wave height for Southwest season (June, July, August and September) Figure 10b: Wave energy for Southwest season (June, July, August and September) Figure 11b: Yearly wave energy Lying at the central part of the long fetch in the South China sea which has a prevailing wind blowing from Northeast and Southwest direction, Vietnam is geographically rather well suited to exploit the wave resource. The biggest wave energy appears during the Northeast monsoon season which last from November to the January next year. The average wave energy during the period at the coastal zones of Binh Thuan, Ninh Thuan provinces South of Central part Vietnam can gets to kw/m (the maximum wave energy during December is about 30 kw/m). During the Southwest monsoon season (from June to September) the average wave energy at the same place is about 5 to 10 kw/m. The coastal zone of Central part of Vietnam is considered as the area with the riches wave energy in Vietnam. The best suitable places for the exploitation of wave energy converters are the areas with the depth of 20 to 50m or the areas around the nears shore islands [5].

5 - As the wave computation grid is too large for including the effects of decreasing depth when the waves coming to the shore (shoaling, refraction etc.) the wave resource near shore should be compared with bathymetric charts to gain an understanding values. - The data used here is sourced from a five year archive. A addition of new data to the wind and wave archive is needed to get a more complete range of seasonal variations 4. Conclusions Although the average wave energy resource in Vietnam is not as high as in some places in the world, but it is the country with the richest wave energy in comparing with the other countries in the Southeast Asia. The extraction of wave energy may demand large capital investments, but the pricing can still compete with fossil fuel and nuclear fuel, since the ocean fuel is free. The transformation process of wave energy to electrical energy does not render any waste that has to be stored or destroys the environment. For Vietnam, This energy is an important alternative in the remote zones as coastal zones and islands where there is no option for energy supply. Despite the expansion of the rural electrification grid, the research and development of renewable energy at all and wave energy in particular in Vietnam has been ongoing for decades in the future. Acknowledgments This study is supported by funds made available under the national research and technology national Project KC.09.19/06-10 Research on the potential of main marine renewable energy and extracting methods. The authors would like to provide acknowledgment to the Ministry of Science and Technology Vietnam the sponsor s of the Project. References [1]. Harald E. Krogstad and Stephen F. Barstow. (1999): Satellite wave measurements for coastal engineering applications. Coastal Engineering, Volume 37, Number 3. August 1999, pages [2]. Swan User Manual, (2005): Swan Cycle III version Delft University of Technology, [3]. Nguyen Manh Hung, Do Le Thuy, Duong Cong Dien. (2005): Storm wave modeling with SWAN. Comparison of measurement data and modeling results for the storm MUIFA 11/2004. Vietnam Journal of Mechanics, Volume 27, Number, [4]. Nguyen Manh Hung, Duong Cong Dien and others (2007): A monograph on the Wave Energy in the South China sea and the sea areas of Vietnam. (2009). The publish house of Natural Sciences and Technology, Hanoi, [5]. Nguyen Manh Hung, (2007): The program of the national Project KC.09.19/06-10 Research on the potential of main marine renewable energy and extracting methods. Hanoi, 2007