Title:
Wave energy resource characterization and classification for the United States & numerical simulation of coastal circulation near Point Sal, California
Wave energy resource characterization and classification for the United States & numerical simulation of coastal circulation near Point Sal, California
Author(s)
Ahn, Seongho
Advisor(s)
Haas, Kevin A.
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Abstract
This thesis contains two different topics: 1) Wave energy resource assessments, characterizations, and classifications for US coastal waters, 2) Numerical studies for three-dimensional circulation during coastal upwelling favorable winds on the inner shelf near Point Sal, California. Ocean waves are a largely abundant and untapped renewable source of energy with limited environmental impact and high energy density. Although ocean waves have significant energy potential, the technology is in early stages of development due to high costs from lower conversion efficiencies as well as risks to operations, maintenance and survival. This study characterizes and classifies the wave energy resource by performing a comprehensive resource assessment of the wave energy for the US. The work for this portion includes three parts. The first part focuses on describing the wave energy resource parameters or metrics for characterization, e.g., wave energy potential, dominant frequency, directional and temporal variability. Partitioned wave parameters generated from a 30-year WaveWatch III model hindcast are used to estimate the total wave energy potential as an annual available energy (AAE), which is a theoretical annual energy production per unit energy capture length without considering energy conversion efficiencies. The distribution of AAE by peak period, wave direction, month, and year are important attributes of the wave energy resource that can be quantified using simple summary metrics (indices), including spectral width, energy-weighted period, directionality coefficient, and direction of maximum directionally resolved AAE. These metrics are used to characterize long-term AAE trends, including inter-annual and seasonal variability. These temporal attributes of the wave energy resource can be parameterized by simple indices as measures of the variability, or constancy, of the resource, which can affect the capacity factor and annual energy production of a wave energy generation project. Geographical distributions of the AAE and these seven resource parameters delineate distinct wave climates and wave energy resource regions within US coastal waters, which supports regional energy planning and project development. The second part uses these parameters to delineate and describe eleven distinct US wave climates or wave energy resource regions based on the key attributes of the resource, wave energy potential, resource attributes, assessed from the part 1. In order to gain a high-level wave resource characteristics, marginal and joint energy distributions of the wave energy in terms of the peak period, wave direction and month, and corresponding resource parameters are provided. The frequency dependence, directional and temporal variability of the conditional wave energy resources at each region is characterized, e.g., the spectral width of the wave energy from a particular direction or month, directionality coefficient of the wave energy within a particular frequency or month. These assessments and characteristics of the conditional wave energy resources can contribute to WEC industries by providing the resource quality of all wave systems and recommending target wave systems for energy generation at each region. Detailed characteristics of energetic wave systems contributing to the total energy at each region are identified and described by linking global and local wind climates. Finally, representative characteristics of the wave energy resources for the eleven regions are summarized.
In the third part, wave energy resource classification systems for the US is developed based on wave power and its distribution with peak period. 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. 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. The 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. This work establishes 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. The circulation during coastal upwelling events near Pt. Sal, a 5km headland in southern California, is considered complex not only due to the complex bathymetry and coastline but a confluence of distinct alongshore currents, e.g., California Undercurrent, coastal jets, and upwelling plumes. The wind stresses and alongshore currents drive geostrophic flows and Ekman transports simultaneously and alongshore variabilities of coastline orientations and a promontory complicate the circulation by creating pressure gradients at the coast. In order to understand the coastal circulations around Pt. Sal, a numerical model, Regional Ocean Modeling System (ROMS) is used for simulations during upwelling favorable wind periods, June-July 2015 and July-September 2017. The coastal upwelling events on 15 July 2015 and 22 July 2017 are identified and three-dimensional particle trajectories are calculated to analyze the circulation pattern on these periods. As a result, characteristics of the coastal circulations, circulation boundary, upwelling front, convergence/divergence, and stratifications, are described. Basic driving forces influencing the circulation during the detected periods, e.g., alongshore/cross-shore wind stresses, California Undercurrent, coastal jet, upwelling plumes, and bathymetry are discussed. The circulation pattern is diagnosed by linking the forcing mechanisms with three-dimensional momentum balances at different locations. Finally, the dominant forcing mechanisms acting on the different regions are identified and two coastal upwelling circulations are compared.
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Date Issued
2019-07-30
Extent
Resource Type
Text
Resource Subtype
Dissertation