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Energies
  • Article
  • Open Access

25 September 2019

Ocean Renewable Energy Potential, Technology, and Deployments: A Case Study of Brazil

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1
Ocean Engineering Department, Federal University of Rio de Janeiro, Rio de Janeiro 21941-914, Brazil
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Civil Engineering Department, Federal University of Rio de Janeiro, Rio de Janeiro 21941-907, Brazil
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Center for Global Sea Level Change (CSLC), New York University Abu Dhabi (NYUAD), Abu Dhabi PO Box 129188, UAE
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China Ship Scientific Research Center (CSSRC), Wuxi, Jiangsu 214082, China
This article belongs to the Special Issue Renewable Energy in Marine Environment

Abstract

This study, firstly, provides an up-to-date global review of the potential, technologies, prototypes, installed capacities, and projects related to ocean renewable energy including wave, tidal, and thermal, and salinity gradient sources. Secondly, as a case study, we present a preliminary assessment of the wave, ocean current, and thermal gradient sources along the Brazilian coastline. The global status of the technological maturity of the projects, their different stages of development, and the current global installed capacity for different sources indicate the most promising technologies considering the trend of global interest. In Brazil, despite the extensive coastline and the fact that almost 82% of the Brazilian electricity matrix is renewable, ocean renewable energy resources are still unexplored. The results, using oceanographic fields produced by numerical models, show the significant potential of ocean thermal and wave energy sources in the northern and southern regions of the Brazilian coast, which could contribute as complementary supply sources in the national electricity matrix.

1. Introduction

Only 14% of the world’s primary energy matrix originates from renewable resources (based on the 2016 database), and this value is about 25% for the electrical energy sector [1]. The immediate needs to limit climate change and achieve sustainable growth are two key drivers of global energy transformation. Consequently, it is estimated that the share of renewable energy sources in the electrical energy sector will increase from 25% in 2017 to 85% in 2050 [1], in which ocean renewable energy sources including wave, tidal, thermal, and the salinity gradient will be responsible for the 4% of the total electricity generation. However, new approaches to power system planning, system and market operations, and regulations and public policy will be required to obtain that goal. As the contribution of low-carbon electricity becomes significant and it becomes the preferred energy carrier, the share of electricity consumed in the end-use sectors will need to increase from approximately 20% in 2015 to 40% in 2050 [1]. Electricity generation using coal, oil, gas, hydroelectric, nuclear, and bioenergy is predicted to decline from 2015 to 2050. On the other hand, a rapid evolution associated with the use of renewables like wind, geothermal, solar, ocean renewable energy, and concentrated solar power (CSP) will likely be observed. International Renewable Energy Agency (IRENA) showed that the sources of renewable electricity in 2050 will be dominated by solar and wind power plants, highlighting significant growth associated with the geothermal, CSP, and ocean renewables.
Although Brazil is currently one of the world´s cleanest energy suppliers, there are some concerns associated with the country´s energy sustainability. An increasing demand for energy, mainly fossil fuels, expanding oil production, a bioenergy sector struggling with expansion, fast growth of energy-related greenhouse gas emissions, and energy efficiency performance deterioration are the current trends that put the future of the country’s sustainable energy performance at risk [2].
Brazil is the world’s eighth-largest economy with a population of close to 210 million and a land area expansion the size of about two times the European Union [2,3]. With a domestic energy supply of about 292.1 million tons of oil equivalent (Mtoe) in 2017, it is one of the largest energy producers in the world [4]. The Energy Research Office (EPE) of Brazil estimated a domestic electricity supply of 624.3 TWh in 2017, and this was mainly produced by the hydropower plants.
The Brazilian electrical and energy matrices are predominately based on renewable energy sources, which means that, in addition to having lower operating costs, a much lower greenhouse gas effect is emitted in association with energy production and consumption. For instance, in 2017, the total anthropogenic emissions of the Brazilian energy mix was estimated at approximately 435.8 million tons of equivalent carbon dioxide (Mt CO2-eq), of which the transport sector emitted the largest part (199.7 Mt CO2-eq) [4]. Based on the data presented by the International Energy Agency (IEA) [5], each Brazilian issued an average of 2.1 t CO2-eq, considering the production and consumption of energy in 2017. This is three times less than that of a European or Chinese citizen and about seven times less than an American citizen.
By meeting almost 45% of its primary energy demand from renewable resources, Brazil has the least carbon-intensive energy sector in the world [6]. Figure 1a shows the domestic energy supply breakdown for Brazil for 2017. Petroleum and oil products, with a share of 36.4%, had the largest contribution to energy supply, followed by sugarcane biomass (17%). Natural gas (13%) and hydraulic energy were other players in the energy matrix of Brazil. Black liquor contributed 50.6% of the “other renewables” sector, followed by wind (21.3%), biodiesel (19.7%), other biomasses including rice husk, elephant grass, and vegetable oil (6.5%), charcoal industrial gas (0.4%), biogas (1.1%), and solar energy (0.4%). The Brazilian electrical matrix, as shown in Figure 1b, was dominated by hydropower resources with a contribution of approximately 65.2%. The main Brazilian hydroelectric reservoirs are located in the Paraná River basin, South region, featuring the Itaipu plant, which is the second-largest hydroelectric power plant in the world with a capacity of 14 GW [7]. The hydroelectric power plants in Brazil are mostly concentrated in the Midwest, South, and Southeast regions. Several studies have discussed the benefits and challenges of the hydroelectric plants in Brazil [7,8,9,10]. Nevertheless, the remoteness and environmental sensitivity of a large part of the remaining resources are two hurdles that constrain the continued expansion of hydroelectric plants in Brazil [6].
Figure 1. (a) Domestic Brazilian energy supply and (b) electrical matrix breakdown in 2017.
Brazil already has a significant contribution of renewable energy in its energy and electricity matrix; however, there is an inestimable untapped potential for energy supply from the oceans. Although nearly 80% of the Brazilian population lives near the coast, there has been no in-depth survey on the utility of ocean energy and its conversion into electricity. There have only been a handful of studies associated with the ocean renewable energy potential along the Brazilian coastline, and these have mainly focused on the wave and ocean current energy in some specific regions. Some examples of the studies related to the wave and current energy include those in [11,12,13,14,15,16], which focused on the South and Southeast regions of the Brazilian coast. Moreover, ocean thermal energy conversion (OTEC) resource evaluation of the Southern Brazilian continental shelf is presented in [17]. The EPE, through the National Energy Plan [18,19], established some general roadmaps related to the long-term plan of the Brazilian energy sector. Accordingly, the ocean energy resources, among other alternative energy sources, were suggested as a way to expand the Brazilian energy matrix in the coming decades. This was also emphasized by the National Agency of Electric Energy through a roadmap project performed by the Center of Management and Strategic Studies of Brazil in 2017 [20].

2. Targets, Materials, and Methods

In Brazil, mapping of the ocean renewable energy resources through a detailed survey of all resources is required to identify potential areas for exploration and, consequently, encourage the development of technologies through the implementation of socio-economically feasible and acceptable projects. Using this perspective, this article firstly presents an overview of the global potential of ocean renewable energy resources and the associated technologies for harnessing such energy. Then, in the second part, the global status of technology maturity is presented through a wide survey of projects, which are at different stages of development. This shows the current global installed capacity for different energy sources, as well as pointing out the more promising technologies through the global interest trend. The third part presents an assessment of the ocean renewable energy resources including ocean currents, waves, and thermal gradients along the Brazilian coastline. This is a preliminary effort aimed at indicating the potential energetic regions. Further detailed works are required to investigate these locations. The methodology applied in this study consists of the use of oceanographic fields produced by hydrodynamic models to estimate the potential of the energy resources. Modeling is performed for a data resolution (one regular horizontal grid) of 1/12° (~9 km). The study reveals the theoretical potential (available energy at sea and not what can be captured) of the resources as well as their seasonal and temporal variability. Finally, the main Brazilian projects are presented, and the challenges are discussed.

2.1. Study Area

The Brazilian coastline is more than 7400 km in length and is situated between 04°52′45″N (Oiapoque River) and 33°45′10″S (Chuí River). The marine areas under Brazilian jurisdiction include the Territorial Sea, with a limit of 12 nautical miles; the Exclusive Economic Zone (EEZ), with 12 to 200 nautical miles; and the Continental Shelf, which comprises the seabed that extends beyond the Territorial Sea, along the natural extension of the land territory off the continental shelf.
The extent of the Brazilian continental shelf varies along the coast, with a few kilometers (~8 km) near Bahia and up to 300 km on the coast of the State of Pará, with a range between 60 and 180 m [21,22]. The Brazilian coastline is characterized by intraseasonal fluctuations in the upper ocean circulation due to several dynamic processes, such as the local forcing dynamics, the remote forcing of winds via waveguide dynamics, the average flow instability, and the resonance as a function of the coastline geometry [23,24]. The ocean circulation is dominated by the Subtropical Turn (Equatorial South Current, SEC) and the Antarctic Circumpolar Current [25]. The SEC is responsible for transporting the water from the Benguela Current to the Brazilian platform (about 10°S and 20°S), where it passes through a fork in the North Brazil Current (NBC) and the Brazil Chain (BC) to the south. Due to this circulation, the western margin of the tropical South Atlantic is a particularly interesting region for the observation of thermohaline circulation [21,22,23,24,26].
As illustrated in Figure 2, the study area included the Brazilian coastline inside the EEZ, which is divided into four regions A, B, C and, D, according to both hydrodynamic and atmospheric characteristics. Table 1 shows the regions and the corresponding latitudes.
Figure 2. Brazilian coastline and the main marine areas delimited.
Table 1. Regions of the Brazilian coast considered in this study.

2.2. Model Description

2.2.1. Ocean Current and Thermal Gradient Energy

The datasets for ocean current velocities and temperature were obtained (surface down to 5500 m) from the numerical model product available for the CMEMS (Copernicus Marine Environment Monitoring Service) center. The applied product is a high-resolution global analysis and forecasting system that uses the NEMO (3.1) ocean model [27]. It consists of part of the Operational Mercator global ocean analysis and forecast daily system, which was initiated on December 27, 2006. The dataset has one regular horizontal grid with a 1/12° (~9 km) resolution based on the tripolar ORCA grid [28], 50 vertical levels with 22 layers within the upper 100 m from the surface, bathymetry from ETOPO1 [29], and atmospheric forcings from the ECMWF (European Centre for Medium-Range Weather Forecasts). Additionally, it uses a data assimilation scheme, in which the initial conditions for numerical ocean forecasting are estimated by joint assimilation of the altimeter data, in situ temperature, salinity vertical profiles, and satellite sea surface temperature.
- Ocean current energy
Near-surface (~5 to 50 m) u and v components of velocity from January 1, 2007 to December 31, 2017 were used as a subset of the area corresponding to the Brazilian coastline (25°W–55°W and 6°N–34°S).
The ocean current power can be calculated as the amount of marine-hydrokinetic energy that flows through a unit cross-sectional area oriented perpendicular to the current direction per unit time [30] expressed as follows:
P         = 1 2 ρ S 3 ,
where P is the current power density in ( W / m 2 ), ρ is the density of seawater (defined as 1025 kg/m3), and S is the flow speed (in m/s). In practice, only a fraction of this energy can be harnessed. The underwater turbine efficiency has a typical range from 35% to 50% [31]. Additionally, a mean peak current of more than 2 m/s is necessary for commercial power generation [32].
- Thermal gradient energy
Gridded daily seawater temperature (°C) model output with 50 vertical layers and ~9 km in horizontal resolution was used to analyze the temperature difference (ΔT (°C)) between the surface warm water and the deeper cold water. It was assumed that the superficial water intake pipe was located at about 20 m and the deepest point in the vertical depth stratification was approximately 1000 m. At specific locations (each grid cell), we calculated the gross power ( P g r o s s ) following the methodology described by [33,34]. The OTEC gross power can be expressed as the product of the evaporator heat load and the conversion efficiency of the gross OTEC [34]:
P g r o s s = Q c w ρ c p 3 ε t g γ 16 ( 1 + γ ) T Δ T 2 ,    
γ = Q w w Q c w ,        
where γ is the flow rate ratio calculated for a 10 MW OTEC plant in which Q w w = 45   m 3 / s and Q c w = 30   m 3 / s are the warm surface water and the cold deep water flow rates, respectively [35]. ΔT is the difference in temperature between the surface layers and deeper layers, and T is the absolute temperature at the surface (in Kelvin) (20 m). ρ and ε t g represent the water density, which was equal to 1025   kg / m 3 , and the turbo-generator efficiency fixed at 0.75, respectively. c p is the specific heat of seawater and has a value of 4000   J . kg 1 . K 1 .
A considerable amount of the P g is consumed to pump the large seawater flow rates through the OTEC plant. The net power P n e t should be calculated, which is usually about 30% of the P g [36,37]. The P n e t can be expressed by the following equation considering Δ T d e s i g n = 20   and the other losses presented in [34]:
P n e t = Q c w ρ c p ε t g 8 T { 3 γ 2 ( 1 + γ ) Δ T 2 0.18 Δ T 2 d e s i g n 0.12 ( γ 2 ) 2.75 Δ T 2 d e s i g n } .

2.2.2. Wave Energy

The wave dataset was obtained using the operational global ocean analysis and forecast system of Météo-France that is available for the CMEMS (Copernicus Marine Environment Monitoring Service) center. The model had a horizontal resolution of 1/12° (~9 km) and 3-hourly instantaneous fields of integrated wave parameters. The global wave system of Météo-France is based on the third-generation wave model MFWAM. It uses the computing code ECWAM-IFS-38R2 with a dissipation term [38]. The 2-min gridded global topography data ETOPO2/NOAA were used to generate the model’s mean bathymetry. The dataset uses three years of data to estimate the wave climatology along the Brazilian coastline (between 2015 and 2018). The power density P was calculated using the significant wave height Hs and the wave energy period Te as follows:
P = ρ g 2 64 π H s 2 T e      
where ρ and g represent the seawater density (1025 kg.m–3) and gravity acceleration (9.806 m.s–2), respectively; Hs is the significant height (m); and Te is the energy wave period (s). This simplified expression uses deep-water approximation [39], which fits well most of the modeled domains; however, more sophisticated techniques as well as in situ measurements are required to precisely determine the shallow water wave climate.

2.3. Metrics

The variability of the available ocean renewable energy in time is an important issue due to its impact on the capacity factor, which, consequently, affects the economy of the ocean energy system. Two different metrics were used to address the seasonal and temporal variability of the Brazilian coastline. The seasonal variability (SV) index [40] can be expressed as follows:
S V = P S , m a x P s , m i n P y e a r ,
where   P s , m i n and P S , m a x are the mean wave power of the least and the most energetic seasons, respectively, and the P y e a r is the annual mean power. Greater values of SV imply a larger seasonal variability; however, it should be noted that this is the variability of the energy resources relative to their mean level on a three-month seasonal time scale [40]. The temporal variability of the energy at a site or region can be evaluated by the coefficient of variation (COV) [40], which is expressed as
C O V ( P ) = S D ( P ( t ) ) m e a n   ( P ( t ) ) = [ ( P P ¯ ) 2 ¯ ] 0.5 P ¯ ,
where SD is the standard deviation, and the over-bar denotes the time-averaging. A COV equal to zero leads to a fictitious power time series with absolutely no variability, while COV (P) = 1 and 2 imply that the standard deviation of the time series is equal to and twice the mean value, respectively.

4. Case Study of Brazil

4.1. Resource Assessment Results

4.1.1. Ocean Current Energy

Figure 13 and Figure 14 show the spatial variation of the ocean current resources along the Brazilian coast in terms of the annual and seasonal average current speed ( m / s ) and power density ( W / m 2 ). As shown in Figure 13, the maximum annual average can be observed in the north equatorial margin of Brazil with a velocity of 1.52 m/s. This region is influenced by the NBC. These regions are located at a distance of between 120 and 300 km of the coastline. The same pattern can be observed considering the seasonal distribution. A maximum speed value of 1.67 m/s occurs during autumn. It can be seen that the speed values barely reach 2 m/s, which is recommended for commercial ocean current energy extraction [32]. The current speed values are not significant (less than 0.7 m/s) for the regions A and B. They occur due to the BC flow and are higher during the spring. Figure 14 shows the power density ( W / m 2 ), calculated using Equation (1), across the Brazilian coastline. As expected, following the speed values, region D represents the most energetic area, and power density values higher than 500 W / m 2 can be observed for some areas. Table 3 contains the average values of the seasonal mean power as well as the SV and COV values. The seasonal average values for regions D and C show that, in contrast to the regions A and B, the current power density is higher during austral autumn and winter compared to austral summer and spring. This is due to the seasonal climatological behavior of the NBC [25]. The fact that the power density of the region D is significantly higher than that of other regions indicates that the values of SV and COV are less important when the objective is to determine the best region for exploring the ocean current energy. However, these values are important for techno-economic studies of the corresponding energy extracting technologies in the North region.
Figure 13. Annual and seasonal (summer, autumn, winter, and spring) mean surface current speed (m/s) at the Brazilian coastline between January 1, 2007 and December 31, 2017.
Figure 14. Annual and seasonal (summer, autumn, winter, and spring) mean power density (W/m2) at the Brazilian coastline between January 1, 2007 and December 31, 2017.
Table 3. Average values of the ocean current power density (W/m2), standard deviation (±), seasonal variability (SV), and coefficient of variation (COV) for each coastline region—A, B, C and D—for each season (summer, autumn, winter, and spring) between January 1, 2007 and December 31, 2017.

4.1.2. Wave Energy

Figure 15 shows the average annual and seasonal wave power density values. The hindcast shows the variability of the energy resource and provides a holistic view of the wave climate along the Brazilian coast. It can be observed that the most energetic wave areas are located near the regions A and B coasts with a power value between 20 and 25   kW / m . This is intensified during the autumn and winter seasons. This fact is directly related to the increase in the occurrence of extratropical cyclones that generate larger waves that propagate toward these Brazilian regions. The nearshore areas of region A (areas with a water depth of less than 100 m) have values close to 20 kW/m for almost the entire year. This is mainly due to the preponderance of south winds combined with the shoreline orientation that induces strong swells near the coast. The average values of the SV and COV related to the wave power were calculated and are illustrated in Table 4 for five different bathymetries of 25, 50, 100, 150, and 200 m along the Brazilian coast. It can be observed that, independently of the water depth, the seasonal variability (SV) of the regions A and B is always smaller than that of the regions D and C. On the other hand, the minimum COV occurs in the region C, while the region D has a greater COV than the other regions. However, the differences between the COV values of the region C, when compared with those in the regions A and B, are small and decrease as the water depth increases from 25 to 200 m. The region C has the smallest wave power variability during the year, which may lead to a higher capacity factor, while the regions A and B are the areas with the most energetic waves, allowing the deployment of the devices with higher installed capacity. A trade-off between the WEC nominal power and capacity factor as well as other local characteristics such as water depth should be considered to determine the proper locations for deploying wave farms.
Figure 15. Annual and seasonal (summer, autumn, winter and spring) mean wave power density (k W/m2) at the Brazilian coastline between January 1, 2015 and December 31, 2017.
Table 4. Average values of wave seasonal variability (SV) and coefficient of variation (COV) considering five different bathymetries (25, 50, 100, 150 and 200 m) for each region—A, B, C and D—between January 1, 2015 and December 31, 2017.
The available wave power for the Brazilian coastline was calculated at an average distance of 128 km from the coast (Table 5). Accordingly, a total available wave power of approximately 91.8 GW was estimated considering a total coastline length of about 7491 km (an approximate value without coastline details). It should be noted that this value is an estimation of the theoretical potential of the Brazilian wave power. In practice, only a fraction of this value can be extracted by the wave energy devices, which depends on different issues such as technical challenges, environmental impacts, economy, deferent use of the sea area, and social impacts. Nevertheless, only one-fifth of this potential is equal to approximately 35% of the Brazilian electricity demand in 2017 [183].
Table 5. Available wave power of the Brazilian coastline.

4.1.3. Ocean Thermal Energy

Figure 16a shows the annual average Δ T   ( ) between the water depth of 20 and 1000 m along the Brazilian coast. The results show that, except for the extreme South below 27   ° S , the yearly average ΔT is always about 20 °C or higher along the Brazilian coast. The average gross power of a 10 MW OTEC plant (see Section 2.2.1) was calculated for 12 locations along the coastline. The selected points were located approximately at a distance between 30 and 200 km to the shore and had an annual average ΔT at between 20 and 1000 m of water depth of more than 20   . Figure 16b illustrates the annual variation in the gross power for the considered points. A greater average annual gross power, represented by the red solid line, can be observed for the regions D and C comparing to the regions A and B. Moreover, the results show smoother power production for the regions D and C comparing to the regions A and B. Table 6 shows the characteristics of the selected points as well as the P g r o s s and P n e t .
Figure 16. (a) Annual mean ΔT (°C) between 20 and 1000 m and (b) the annual ocean thermal energy conversion (OTEC) Gross Power Density (PG in MW) at a depth of 1000 m considering the period between January 1, 2007 and December 31, 2017.
Table 6. Gross and net power estimation for the selected points along the Brazilian coastline.
Figure 17 illustrates the seasonal mean ΔT ( ) between the water depths of 20 and 1000 m, for a bathymetry of 1000 m, across the Brazilian coastline. The black line represents a ΔT of 20   . It can be observed that, for the regions A and B, the water depth in which the mean ΔT = 20 °C is achieved, varies between 500 m in summer and 700–1000 m in other seasons. On the other hand, in the regions D and C, a mean ΔT of 20 °C can be reached in a water depth of about 500–700 m throughout the year. From a technical point of view, less structural challenges would be expected when bringing the cold water from a depth of 500 m rather than from 1 km.
Figure 17. Seasonal (summer, autumn, winter, and spring) mean ΔT (°C) between 20 and 1000 m for the bathymetry of 1000 m (for regions A, B, C and D) across the Brazilian coastline latitude considering the period between January 1, 2007 and December 31, 2017. The black line corresponds to a ΔT of 20 °C.

4.2. Deployments in Brazil

The first deployment of an ocean renewable energy converter in Brazil occurred in 1934 when the French engineer Georges Claude used an ocean thermal energy source to produce ice for the residents of Rio de Janeiro. His plant ran into problems and stopped working off the coast of Rio de Janeiro due to fatigue of its long intake tubes [184]. Studies associated with ocean renewable energy in Brazil began in 2001 at the Federal University of Rio de Janeiro (UFRJ), focusing on wave and tidal energy. Some other universities have also started working in this field, such as the Federal University of Maranhão (UFMA), the Federal University of Santa Catarina (UFSC), the Federal University of Pará (UFPA), and the Federal University of Itajubá (UNIFEI).
There are three main ocean renewable energy projects being carried out in Brazil with different technology readiness levels. The first one is the COPPE (The Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering) hyperbaric wave converter developed by the UFRJ, which has reached the prototype stage. A full-scale single device of the technology was installed in 2011 in Pecém port of Ceará state located in the northeast of Brazil. The device was decommissioned after 6 months of operation due to the port extension project. The second project is a nearshore wave energy converter, also developed by the UFRJ, which will be installed in relatively shallow water (water depth of 25–30 m) off the Rio de Janeiro coast. The technology is at the R&D stage and is undergoing medium-scale laboratory tests. The last project is the tidal range project of the Bacanga River estuary located in São Luís of Maranhão state in North Brazil. Although the discussion about the tidal energy extraction in this region is relatively old, the project is still at an early stage of development as it is waiting for finance. The following sections describe the characteristics and statuses of the mentioned projects.

4.2.1. COPPE Hyperbaric Wave Converter

As illustrated in Figure 18, this device is composed of a floating body connected to the pumping modules, a hydrodynamic accumulator, a hyperbaric chamber, and a generating unit. The vertical motion of the floating body due to the wave body interactions drives the pump actuator which displaces the water inside the closed circuit to a hydro-pneumatic accumulator. The accumulator is connected to a hyperbaric chamber, which has previously been pressurized. Then, the pressurized water drives a hydraulic turbine coupled to an electrical generator. The hyperbaric chamber works as an energy storage system, which smooth the power fluctuations due to the oscillatory nature of sea waves. The applied pressure is in the range of 250−400 m of water column (m.wc) [185].
Figure 18. A schematic of the COPPE/UFRJ (Federal University of Rio de Janeiro) hyperbaric wave converter [185].
Additionally, a discrete control scheme was applied to the system to improve power production by adjusting the PTO parameters without wave measurement [186]. The experimental tests were performed at the Ocean Technology Laboratory (LabOceano) of the UFRJ. Figure 19 shows the medium-scale model at a ratio of 1:10 which was tested under regular and irregular wave conditions corresponding to the predominant wave climate at the location of installation [187,188]. As a result of the experimental tests, a capture width ratio of between 19% and 36% was observed for the wave energy converter.
Figure 19. COPPE hyperbaric wave converter: (a) medium-scale model with a ratio of 1:10 at LabOceano [187]: (b) installed full-scale prototype.
A full-scale prototype with a capacity of 100 kW was deployed at the Pecém port in Northeast Brazil (Figure 19b). The device was installed on two concrete bases, 12 m in length, built on a breakwater. The oscillating part, which consists of a floater, 10 m in diameter, and a mechanical arm, 22 m in length, is connected to two skids mounted on the concrete bases.

4.2.2. COPPE Nearshore WEC

The system is a point absorber WEC type with a capacity of 50 kW that consists of an oscillating body and a bottom-mounted support structure. The oscillating part is a floating conical cylinder which is allowed to move only in the heave direction (Figure 20). The fixed structure consists of four columns with very small diameters relative to the wavelengths (no diffraction). The structure is mounted on the seabed through a concrete base. Eight roller bearings facilitate oscillation of the buoy in the vertical direction (heave). They are placed on the top and bottom of the cylindrical section.
Figure 20. Components of the COPPE nearshore WEC.
The PTO system is located on the topside deck and consists of a gearbox and a rotational generator (Figure 21). The vertical motion of the buoy is transferred through a central rod (heave stem) to the gearbox. Then, the pulley converts the vertical movement into rotation that is adequate for the electrical generator. A backstop system unifies the rotation direction using freewheels. This implies that the buoy can drive the PTO system either upwards or downwards. A solid cylindrical flywheel is used to amplify the rotational inertia as well as smooth the delivered energy to the generator. Additionally, the PTO system includes a gearbox that multiplies the rotational speed so that it is adequate for power generation.
Figure 21. Schematic view of the power take-off (PTO) system.
The location that has been considered for installation of the WEC is near to a small island called “Ilha Rasa”. The location’s water depth is about 20 m, and its distance from shore (Copacabana beach, Rio de Janeiro, Brazil) is about 14 km. The predominant wave climate of the region is a peak period of T p = 9.6   s and a significant height of H s = 1.33   m . Shadman et al. [189] showed that a very large buoy is required to maximize the power absorption in a region like nearshore Rio de Janeiro, where the predominate wave periods are beyond 7 s. This might lead to higher costs, which could make the project economically infeasible. Hence, a specific control called “latching”, presented originally by Budal and Falnes [190], was applied on the WEC to overcome this challenge. Latching is a mechanical control method that tunes the natural period of the buoy to the predominate wave period of the sea site by halting and releasing the buoy at its motion extremum. As a result, larger buoy motion amplitude and velocities can be achieved, leading to higher power production. Eventually, the latching control enables a smaller buoy with a smaller natural period to be tuned with such a wave climate [191]. A hydraulic system is designed and tested for latching the oscillating buoy.
Experimental tests of small-scale models, shown in Figure 22, were performed in a wave and current channel (LOC) at the COPPE/UFRJ. The hydrodynamic behavior of the buoy was studied by applying different modeling scales including 1:17, 1:20, 1:30, and 1:40. Additionally, a strategy was developed to investigate the effect of latching control on the WEC.
Figure 22. Experimental tests of the COPPE nearshore WEC in a wave channel: (a) 1:17 scaled model, (b) instruments for data acquisition.

4.2.3. Tidal Power Plant of the Estuary of Bacanga

The largest tidal ranges in Brazil are located on the North coast including the coastal areas of Maranhão, Pará, and Amapá. For instance, a tidal energy potential of 22 TWh/year has been estimated for Maranhão state [192]. Some studies have addressed the exploitation of such energy in Brazil [193,194]. As Figure 23a illustrates, the Bacanga basin is 10,219 ha in size, which includes the estuarine body of water and the Bacanga lake. The reservoir capacity is about 40 million cubic meters at an elevation of +4.5 m, corresponding to the spring tide level [192]. As shown in Figure 23b, the dam includes an 800 m embankment rock which is filled with clay material. Additionally, the dam has two sluice gate systems types of radial and stop-log that were installed in 1974 and 1980, respectively. There are three radial sluice gates with widths of approximately 12.5 m. In the case of a fully open gate, a water height level of 4.5 m is registered for each radial gate. This value is about 3 m for the stop-log gates, which are flat and operate vertically, with widths of 2.85 m.
Figure 23. (a) The Bacanga Estuary, and (b) aerial image of the radial and stop-log sluice gates [192].
Considering some restrictions, including a reservoir water level limit of +2.5 m, Neto et al. [192] proposed a new model for the tidal power plant in which the three radial sluice gates were replaced by the modern and appropriate version for automatic operation, which excluded the necessity of using stop-log type gates to control the reservoir maximum limit. Considering the Kaplan turbine with double regulation provided by ANDRITZ HYDRO [195], they estimated an annual energy production of slightly larger than 14 GWh/yr for the power plant.

5. Discussion and Open Question

The present cost of ocean renewable energy cannot complete with that of grid-connected renewables. The alternative, nowadays, in addition to the development of more optimized projects, is to look for new markets where electricity generation options are either scarce or expensive, for example the oil and gas industry, aquaculture, defense, and the demands from isolated communities. In the particular case of Brazil, there is a concentration of power generation, mostly from hydroelectric plants, located in the South and Southeast regions. It has been demonstrated that a significant amount of ocean renewable energy featuring an ocean thermal gradient is located in the regions D and C (see Figure 2). In these regions, an annual electricity production of 0.8 TWh per year has been calculated, considering only six OTEC plants with 10 MW installed power, as presented in this paper. Accordingly, considering an annual average of 15 MW, 20 OTEC plants would be sufficient to supply approximately 10% of the total residential electricity consumption of the Northeast region of Brazil, which was estimated to be approximately 27.059 TWh in 2017 [183]. This implies that such renewable energy resources could be harnessed as a supplementary alternative for these regions, especially when there is a power generation drop due to seasonal rain shortage. Additionally, the low seasonal and temporal variability of the ocean renewable resources along the Brazilian coast could provide stable power production throughout the year, with substantial capacity. The supply chain associated with ocean renewable technologies is still incipient worldwide. The increasing prototype deployments may promote the association of local supply chains with the global suppliers of specific equipment such as submarine cables, electrical connectors, turbines, and generators. In Brazil, the supply chain would consist of companies already operating in the offshore oil and gas sector. This is a very robust sector, which will be able to meet the demands of the ocean renewable energy sector. The synergy of the long-established offshore oil and gas sector and the new ocean renewable energy sources could represent a crucial factor for the success of the new industry. Updated technologies must be incorporated, especially digital ones associated with artificial intelligence, control, and robotics to provide competitive services for inspection and maintenance, reducing the operational costs. New materials, such as the composites associated with innovative floating structures and installation methods, can also contribute to the competitiveness of the new sector in terms of the electricity cost. In Brazil, the large number of hydropower plants and the complex grid system also present opportunities for the implementation of ocean renewable energy sources. Hydropower plants could be designed as storage components of the whole electrical system, combining a better water supply with clean and efficient power generation throughout the country. The substitution of oil and gas-based power plants for ocean renewables would modify the national energy matrix substantially, reinforcing sustainably oriented electricity generation.

6. Conclusions

This paper, as a preliminary approach, has presented an assessment of ocean renewable energy resources, including wave, ocean current and thermal gradient energy, along the Brazilian coastline. The results show considerable ocean currents, thermal gradients, and wave energy in the regions D, C and A, respectively. A maximum annual average velocity of 1.52 m/s, which represents a power density of approximately 500 W / m 2 , was observed for the ocean current energy in the region D near the equatorial margin of Brazil. However, the distance of the resource to the coastline, between 120 and 300 km, is an obstacle to its commercialization. The total theoretical potential of wave energy is estimated to be 91.8 GW along the coastline. The most energetic waves occur in the region A, following by the regions C, B, and D, with average power values of 21.1, 13.8, 12.4, and 7.4 kW/m, respectively. In the region C, the wave resource has the least temporal variability compared with the other regions; nevertheless, the differences are small, and they decrease with an increasing water depth. The results revealed an annual average ocean thermal gradient, between the water depths of 20 and 1000 m, of more than 20 °C for latitudes above 27 ° S . A mean thermal gradient of 20 °C between the upper layers and water depth between 500 and 700 m can be achieved throughout the year in the regions D and C. This could facilitate the process of bringing cold water from the deep sea, compared with the usual water depth of 1000 m.
The paper also presented an overview of the potential technologies and their statuses of development related to ocean renewable energy sources worldwide. Although available studies indicate different values for the global resource potential, they converge in presenting the ocean thermal gradient as being the most energetic resource followed by waves, salinity gradients, and tides. The TRL and the status of the current projects imply that the global interest tends toward tidal current and wave devices.
Large-scale installations, learning-curves, and innovation are necessary to make the cost of energy competitive with solar and onshore wind energy production. About 27% of the current projects are at the pre-deployment phase and, optimistically, will be deployed in the open sea in the next three years. Apart from tidal range technology, which is already close to the commercialization stage, research, development, and demonstration projects have been led by universities and startups, mostly by taking advantage of public financing. Nevertheless, in the last five years, large industry players and utilities have started carrying out activities and financing in the sector. This is an important step towards speeding up technology commercialization due to the new players’ capability to execute utility-scale projects.

Author Contributions

Conceptualization, M.S.; Formal analysis, M.S. and D.F.; Methodology, M.S. and D.F.; Project administration, M.S.; Resources, L.P.d.F.A.; Software, D.F.; Supervision, L.L., C.L. and S.F.E.; Visualization, C.S. and Z.W.; Writing—original draft, M.S., C.S. and Z.W.; Writing—review & editing, L.P.d.F.A., L.L., C.L. and S.F.E.

Funding

This research received no external funding.

Acknowledgments

The authors acknowledge CNPq, the Ministry of Science, Technology, Innovation and Communication/Brazil, for supporting the research activities of the authors. Additionally, the first author highly appreciates the Instituto Nacional de Ciência e Tecnologia—Energias Oceânicas e Fluviais (INEOF) for supporting his research activities. The third author acknowledges David Holland and the Center for Global Sea Level Change from New York University Abu Dhabi for supporting her research work.

Conflicts of Interest

The authors declare no conflict of interest.

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