Wave energy utilization for pipe-in-pipe heating: a technique to provent hydrate formation in offshore hydrocarbon transportation

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Trabalho de Curso - Graduação - Monografia

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18-08-2025

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ALVES, Ana Carolina de Souza. Wave energy utilization for pipe-in-pipe heating: a technique to provent hydrate formation in offshore hydrocarbon transportation. Orientador: Camilo Andrés Guerrero Martin. 2025. 26 f. Trabalho de Curso (Bacharelado em Engenharia de Exploração e Produção de Petróleo) – Faculdade de Engenharia, Campus Universitário de Salinópolis, Universidade Federal do Pará, Salinópolis, 2025. Disponível em:https://bdm.ufpa.br/handle/prefix/9026. Acesso em:.
This study evaluates the techno-economic performance of a tidal energy project using the Tidal module of the System Advisor Model (SAM). The configuration corresponds to an array-scale installation with a total installed capacity of 1,115 kW. Under the site-specific resource and availability assumptions used in SAM, the model estimates an annual energy production of 212,946 kWh, yielding a capacity factor of 2%. The levelized cost of energy (LCOE) is calculated at 1,449.65 ¢/kWh. A detailed cost decomposition indicates total capital expenditures (CapEx) of $15,971,341.37 (14,324 $/kW), of which device hardware accounts for $4,826,559.72 (4,329 $/kW) and balance-of-system for $9,330,683.69 (8,368 $/kW), with financing charges of $1,814,097.96 (1,627 $/kW). Operations and maintenance (O&M) are projected at $1,362,080.09 per year (1,222 $/kW/yr). In LCOE terms, the contributions are 2.45 $/kWh (devices), 4.73 $/kWh (balance of system), 0.92 $/kWh (financial), and 6.40 $/kWh (O&M), with the remainder attributable to capital recovery. The results highlight the sensitivity of LCOE to capacity factor and O&M intensity: the low modeled capacity factor drives limited energy yield against high fixed costs, while O&M dominates recurring costs. Implications for design and project development include prioritizing resource characterization and device availability, optimizing array sizing and layout to increase capacity utilization, and reducing installation and maintenance logistics to compress both BOS and O&M burdens. These insights can guide subsequent parametric studies within SAM to identify scenarios that materially improve cost competitiveness.

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