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Abstract Energy resource classification systems are useful assessment tools that support energy planning and project development, e.g., siting and feasibility studies. They typically establish standard classes of power, a measure of the opportunity for energy resource capture. In this study, we develop wave energy resource classification systems for the US based on wave power (J , kW/m) and its distribution with peak period ( T p , s). These metrics are calculated for 70,386 sites from partitioned bulk wave parameters generated from a validated 30-year WaveWatch III model hindcast. As the operating resonant period bandwidth of a wave energy converter (WEC) technology is an important design characteristic, the dominant period band containing the largest energy content is identified among three peak period band classes. These classification systems, comprised of four power classes and three peak period band classes, are based on the total wave power or the partitioned wave power in the dominant peak period band. They discriminate distinct trends in wave energy resource among five regions within the US, and provide useful information for energy planners, project developers, and technology designers. They also establish a framework for investigating the feasibility of a compatible wave climate (design load) conditions and WEC technology classification system to reduce design and manufacturing costs. Highlights • Classification parameters discriminate distinct trends in US wave climates. • Key attributes classified for energy planning and project development. • Key attributes classified for design and operation of WEC technologies. [ABSTRACT FROM AUTHOR]

Ocean currents represent an alternative source of clean energy given their inherent reliability, persistence and sustainability. The general ocean circulation is characterized by large rotating ocean gyres resulting in rapid ocean currents along the western boundaries because of the Coriolis Effect. The Gulf Stream system is formed by the western boundary current of the North Atlantic Ocean flowing along the east coast of the United States, and is of particular interest as a potential energy resource for the United States. This study presents a national database of ocean current kinetic energy resource derived from seven years of numerical model simulations to help advance awareness and market penetration for ocean current energy. A web based GIS interface is provided for dissemination of the national energy resource data: http://www.oceancurrentpower.gatech.edu/ . The website includes GIS layers of computed monthly and yearly mean ocean current speed and associated power density along the coastlines of the United States, as well as joint and marginal probability histograms for current velocities at a variable horizontal resolution of 4–7 km. Various tools are provided for viewing, identifying, filtering and downloading the data from this website. The Gulf Stream system, especially the Florida Current, concentrates the highest kinetic power density ( > 2000 W / m 2 ). The majority of the kinetic power and its variability are only present in relatively shallow water given the strong correlation with the surface wind stress. The kinetic energy flux in the Florida Current is estimated over 30 years to provide temporal variability of the undisturbed kinetic energy with high statistical significance. Available power of approximately 5 GW associated with the undisturbed natural flow condition from the Gulf Stream system is predicted based on hypothetical turbine parameters. Successful development of renewable energy generation requires further studies to account for more precise technical, economic and environmental constraints. [ABSTRACT FROM AUTHOR]

Abstract: A geodatabase of tidal constituents is developed to present the regional assessment of tidal stream power resource in the USA. Tidal currents are numerically modeled with the Regional Ocean Modeling System (ROMS) and calibrated with the available measurements of tidal current speeds and water level surfaces. The performance of the numerical model in predicting the tidal currents and water levels is assessed by an independent validation. The geodatabase is published on a public domain via a spatial database engine with interactive tools to select, query and download the data. Regions with the maximum average kinetic power density exceeding 500W/m2 (corresponding to a current speed of ∼1m/s), total surface area larger than 0.5km2 and depth greater than 5m are defined as hotspots and documented. The regional assessment indicates that the state of Alaska (AK) has the largest number of locations with considerably high kinetic power density, followed by, Maine (ME), Washington (WA), Oregon (OR), California (CA), New Hampshire (NH), Massachusetts (MA), New York (NY), New Jersey (NJ), North and South Carolina (NC, SC), Georgia (GA), and Florida (FL). [Copyright &y& Elsevier]

Abstract: A multi-criteria assessment methodology that accounts for the physical, environmental and socioeconomic constraints is proposed to assist in the selection of the most suitable locations for tidal stream power conversion projects. For this purpose, the tidal stream power resource data are incorporated into a Geographical Information System (GIS) database together with datasets that are related to different aspects of the site selection methodology. The proposed method is applied to the Georgia coast to find and rank the best locations for power conversion. The suitable areas are narrowed down to a subset of the high power density areas that satisfy the constraints of a tidal stream power conversion scheme. A demonstrative ranking procedure with equal weighting factors for all criteria shows that the Savannah, Ogeeche, Canoochee and Medway Rivers and the Cumberland Sound have the best locations for tidal power conversion on the coast of Georgia. This methodology is also applicable to other sites where sufficient geospatial data are available. [Copyright &y& Elsevier]

Efforts to streamline and codify wave energy resource characterization and assessment for regional energy planning and wave energy converter (WEC) project development have motivated the recent development of resource classification systems. Given the unique interplay between WEC absorption and resource attributes, viz, available wave power frequency, directionality, and seasonality, various consensus resource classification metrics have been introduced. However, the main international standards body for the wave energy industry has not reached consensus on a wave energy resource classification system designed with clear goals to facilitate resource assessment, regional energy planning, project site selection, project feasibility studies, and selection of WEC concepts or archetypes that are most suitable for a given wave energy climate. A primary consideration of wave energy generation is the available energy that can be captured by WECs with different resonant frequency and directional bandwidths. Therefore, the proposed classification system considers combinations of three different wave power classifications: the total wave power, the frequency-constrained wave power, and the frequency-directionally constrained wave power. The dominant wave period bands containing the most wave power are sub-classification parameters that provide useful information for designing frequency and directionally constrained WECs. The bulk of the global wave energy resource is divided into just 22 resource classes representing distinct wave energy climates that could serve as a common language and reference framework for wave energy resource assessment if codified within international standards. • Novel Global WERCS is developed considering three levels of physical WEC constraints. • Total, frequency-, and frequency-directionally constrained wave power classifications are developed. • Dominant peak period bands containing the most wave energy content are delineated. • Most global coastal wave sites fall into just 22 resource classes. • KEYWORDS: Wave energy resource classification, Global wave energy resource, Global wave climate. [ABSTRACT FROM AUTHOR]