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Seas and oceans offer great potential as a widely available source of clean and renewable energy near high energy consumption centers. This source of energy is a valuable option in the energy transition and in energy matrix decarbonization. Wave energy and an oscillating water column (OWC) device stand out as the types of ocean energy with the most potential. An onshore OWC requires locations with rocky outcrops and steeper slopes as the device needs to be physically installed and has lower energy dissipation due to friction with the seabed. However, Brazil has approximately 7490 km of coastlines, with various shoreline geometries and geomorphologies, some of which are very suitable for OWC implementation. Some authors have estimated that the Brazilian coast has a total potential of 114 GW, distributed between wave and tidal energy, with a great possibility of contributing to global decarbonization efforts. This study aimed to identify and quantify the potential of locations suitable for implementing wave energy farms equipped with onshore OWC. For this, a prospect was carried out using the georeferencing software QGIS, resulting in a georeferenced map with a dataset of 319 locations, and determining a power capacity of exploitation of 9.84 GW and an estimated energy of 83,689 GWh/year in ten of the seventeen coastal states. This energy corresponds to twice the energy consumption of the state of Rio de Janeiro, which has a population of approximately 17.5 million people. If the same amount of wave energy as gas-fired thermal generation energy were to be consumed, the use of wave energy would reduce emissions by approximately 44.52 million tons of CO2 annually. This result suggests that wave energy generation should be included in future studies on the expansion of Brazilian electric systems as an accelerating factor in the energy transition. [ABSTRACT FROM AUTHOR]

Pumping systems, especially those used in the water supply sector and in industrial and hydroelectric facilities, are commonly infested by the golden mussel. This causes an increase in maintenance operations (e.g., system shutdowns for cleaning) that can generate an increased energy cost. The geographical expansion of the golden mussel in Latin America presents an economic risk, not only to the ecosystem in general, but also to the energy sector. The imminence of its spread in the Amazon region, one of the main river basins in South America, is cause for concern with regard to the problems that bioinvasion of this species can cause. Given the absence of studies on the loss of energy efficiency in pumping systems impacted by the golden mussel, this study proposes a methodology to estimate the increase in energy consumption and costs of pumping under such bioinfestation. For the standardization of the methodology and development of mathematical calculations (both novel and improved equations), data from the literature (the growth of the golden mussel as a function of infestation time) and an analysis of the dimensions (length and height) of a sample of mussels available in the laboratory were considered. These data were used to calculate the roughness generated by the mussel infestation in the pumping suction and discharger pipe, which was necessary to determine the loss of energy efficiency (load loss, power consumption, and cost of pumping) resulting from the increase in energy consumption for pumping. This methodology was applied to a pumping station representative of the Brazilian Amazon as a case study. The results show an average increase in economic indicators (consumption and cost of pumping) after the system undergoes bioinfestation. This total increase corresponded to 19% and 44% in the first and second years, respectively, achieving a stabilization of the increase in the cost of pumping at 46%, in the 30 months of operation. Our results demonstrate the pioneering nature of the proposal, since these are the first quantitative data on the energy efficiency of pumping systems associated with bioinfestation by the golden mussel. These results can also be used to estimate the increase in costs caused by golden mussel bioinfestation in the raw water pumping systems of other facilities. [ABSTRACT FROM AUTHOR]