High-resolution survey of tidal energy towards power generation and influence of sea-level-rise: A case study at coast of New Jersey, USA H.S. Tang a,b,n , S. Kraatz a , K. Qu a , G.Q. Chen c,d , N. Aboobaker e , C.B. Jiang b a Department of Civil Engineering, City College, City University of New York, NY 10031, USA b School of Hydraulic Engineering, Changsha University of Sciences and Technology, Changsha, Hunan 410114, China c School of Engineering, Peking University, Beijing 100871, China d NAAM Group, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia e Bureau of Research, New Jersey Department of Transportation, Trenton, NJ 08625, USA article info Article history: Received 17 August 2013 Received in revised form 6 November 2013 Accepted 18 December 2013 Available online 11 February 2014 Keywords: Tidal power Marine hydrokinetic energy FVCOM High-resolution High performance computing Sea-level-rise Climate change abstract The first and a crucial step in development of tidal power, which is now attracting more and more attention worldwide, is a reliable survey of temporal and spatial distribution of tidal energy along coastlines. This paper first reviews the advance in assessment of tidal energy, in particular marine hydrokinetic (MHK) energy, and discusses involved challenges and necessary approaches, and then it makes a thorough survey as an illustrative case study on distributions and top sites of MHK energy within the Might-Atlantic-Bight (MAB) with emphasis on the New Jersey (NJ) coastlines. In view of the needs in actual development of tidal power generation and sensitivity of tidal power to flow speed, the former being proportional to the third power of the latter, a high-resolution and detailed modeling is desired. Data with best available accuracy for coastlines, bathymetry, tributaries, etc. are used, meshes as fine as 20 m and less for the whole NJ coast are generated, and the unstructured grid finite volume coastal ocean model (FVCOM) and high performance computing (HPC) facilities are employed. Besides comparison with observation data, a series of numerical tests have been made to ensure reliability of the modeling results. A detailed tidal energy distribution and a list of top sites for tidal power are presented. It is shown that indeed sea-level-rise (SLR) affects the tidal energy distribution significantly. With SLR of 0.5 m and 1 m, tidal energy in NJ coastal waters increases by 21% and 43%, respectively, and the number of the top sties tends to decrease along the barrier islands facing the Atlantic Ocean and increase in the Delaware Bay and the Delaware River. On the basis of these results, further discussions are made on future development for accurate assessment of tidal energy. & 2014 Elsevier Ltd. All rights reserved. Contents 1. Introduction ........................................................................................................ 961 2. A review on tidal energy survey ........................................................................................ 962 2.1. Method and current status ...................................................................................... 962 2.2. Challenge and approach ........................................................................................ 965 3. Region of study, geophysical data, and sea-level-rise ....................................................................... 966 3.1. Mid-Atlantic-Bight and New Jersey shoreline ....................................................................... 966 3.2. Bathymetry, coastlines, rivers, and observation data .................................................................. 966 3.3. Sea-level-rise and its projection .................................................................................. 968 4. Model setup ........................................................................................................ 968 4.1. Model and mesh generation ..................................................................................... 968 4.2. Boundary conditions ........................................................................................... 969 4.3. Scaling of FVCOM ............................................................................................. 971 5. Model validation .................................................................................................... 971 5.1. Model calibration.............................................................................................. 971 Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/rser Renewable and Sustainable Energy Reviews 1364-0321/$ - see front matter & 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.rser.2013.12.041 n Corresponding author at: Department of Civil Engineering, City College, City University of New York,138th Street and Convent Avenue, NY 10031, USA. Tel.: þ1 212 650 8006; fax: þ1 212 650 6965. E-mail address: htang@ccny.cuny.edu (H.S. Tang). Renewable and Sustainable Energy Reviews 32 (2014) 960–982