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This study introduces a comprehensive analysis of offshore wind resource potential in Trinidad and Tobago, leveraging both the Wind Atlas Methodology (WAM) and the numerical wind atlas methodologies to address the region’s sparse wind measurement data. Utilizing atmospheric re-analysis data, specifically the ERA5 dataset, in conjunction with the Weather Research and Forecasting (WRF) model, a generalized wind climates (GWCs) for Trinidad and Tobago was generated. These GWCs, refined with topographical and roughness data, guide the siting of offshore wind farms within the Exclusive Economic Zone (EEZ), considering water depths and proximate onshore terrain influences. The study quantifies the economic feasibility of offshore wind through both a levelized cost of electricity (LCOE) analysis and by evaluating the value of redirected natural gas to the petrochemical industry. The LCOE, though currently higher than subsidized domestic electricity rates, is projected to decrease significantly by 2035. Notably, the value of displaced natural gas for petrochemical production offers substantial economic benefits, with potential payback periods for offshore wind investments well under a decade when considering 2021 methanol and ammonia prices. These findings underscore the strategic significance of offshore wind in Trinidad and Tobago’s energy mix. By transitioning to renewable energy sources, the nation can mitigate reliance on fossil fuels for power generation while optimizing natural gas usage in high-value sectors.

Introduction

The intensifying impacts of climate change, coupled with a growing global energy demand, underscore the urgent need for a transition to sustainable energy sources. This transition necessitates a move away from traditional fossil fuels toward renewable alternatives [1]. Among the available renewable energy technologies, offshore wind stands out as a particularly promising solution due to its abundant resources, decreasing costs, and technological advancements [2]. This is especially relevant for small island developing states (SIDS) and fossil fuel-producing countries seeking pathways to energy security and decarbonization in a changing energy landscape.

For SIDS, vulnerability to climate change impacts alongside a heavy reliance on imported fossil fuels creates economic instability and undermines energy security [3]. Fossil fuel-producing nations face the challenge of diversifying their economies and aligning with global climate commitments while addressing their traditional reliance on fossil energy resources [4]. Offshore wind energy presents a compelling opportunity for both SIDS and fossil fuel-producing countries to address these challenges and transition towards a more sustainable future.

The offshore wind sector has witnessed remarkable technological advancements in recent years, propelling its growth as a mainstream energy source. Larger and more efficient turbines have significantly increased energy generation capacity [5]. The development of floating foundations has opened up vast areas of deeper waters for offshore wind development, overcoming geographical limitations [6]. These advancements, combined with innovations in energy storage solutions, are enhancing the reliability and flexibility of offshore wind power, contributing to greater grid integration.

Alongside technological progress, the cost of offshore wind energy has plummeted over the past decade. A combination of economies of scale, supply chain optimization, and competitive auctions has driven down costs [3]. In some markets, offshore wind is now cost-competitive with conventional energy sources, making it an economically viable alternative.

The success of offshore wind is evident in established markets across Europe, North America, and emerging markets in Asia. In Europe, the United Kingdom boasts the largest installed offshore wind capacity globally. Countries like Denmark and Germany have been early pioneers, setting ambitious targets and driving industry growth [7]. North America, while starting later, is witnessing a surge in offshore projects, with states along the Atlantic coast setting major development goals [8]. In Asia, China has emerged as the global leader in new offshore wind installations, with rapid expansion in recent years [2]. These successes demonstrate the technical and economic feasibility of offshore wind on a large scale.

It is crucial to acknowledge the economic dependence of many fossil fuel-producing countries on traditional energy sectors. The transition to renewable energy sources such as offshore wind raises understandable concerns about potential disruptions to existing industries and employment. However, it’s important to recognize that offshore wind energy offers significant opportunities for these countries to address these concerns and chart a sustainable path forward.

Offshore wind development can stimulate the creation of new industries and diverse job opportunities. The manufacturing, installation, operation, and maintenance of offshore wind farms require a wide range of skills, including engineering, construction, logistics, and maritime expertise [9]. These jobs can often align with the transferable skills found within the existing fossil fuel workforce, facilitating economic diversification.

Moreover, investing in offshore wind projects can attract significant investment, both domestically and internationally. The growing focus on sustainability and commitments to net-zero emissions by corporations and investors are shifting capital flows towards renewable energy projects [4]. Fossil fuel-producing countries can capitalize on this trend by positioning themselves as hubs for offshore wind development.

Crucially, offshore wind provides an avenue for fossil fuel-producing countries to align with global sustainability trends and decarbonization goals. By reducing reliance on fossil fuels and increasing renewable energy generation, these countries can mitigate carbon emissions and demonstrate their commitment to addressing the climate crisis [10]. This positive environmental action enhances their international reputation and can open doors to new partnerships and trade opportunities.

A growing body of research examines the offshore wind potential of both SIDS and fossil fuel-producing countries. However, a critical review of this literature is necessary to identify common themes while pinpointing areas where further investigation is warranted.

Technical studies on offshore wind energy have been conducted to evaluate various aspects of this renewable energy source. These studies include experiments on the performance and aerodynamic forces of wind turbines in deep seabeds [11]. Real-time models have been developed to simulate offshore wind turbine generators, allowing for testing and control functions such as low-voltage ride-through and reactive power support [12]. Additionally, research has been done on the transmission and grid connection of large offshore wind generation, with a focus on VSC-HVDC transmission technology as a potential solution [13]. Furthermore, studies have been carried out to assess the technical potential of offshore wind energy in the United States, considering factors such as spatial siting constraints and capacity density [14]. These technical studies provide valuable insights and support for the development and operation of offshore wind generation.

Feasibility studies have been conducted to explore the technical, economic, and environmental aspects of offshore wind projects. These studies consider factors such as electrical export connection, logistics, installation methods, and supply chain requirements. The use of HVDC cable has been found to be economically advantageous for offshore wind farms located more than 50 km from the coast [15]. Technical risks associated with installation strategies have been identified and analyzed, with the aim of optimizing planning and logistics to reduce costs and minimize risks during marine operations [16]. Hybrid power generation concepts, combining wind turbines with gas turbine generators, have been developed to reduce maintenance costs, fuel consumption, and carbon dioxide emissions, resulting in better economic benefits compared to conventional methods [17]. Methodologies have been defined to analyze the economic feasibility of floating offshore wind farms, taking into account various factors such as bathymetry, platform characteristics, and wind speed [18]. Feasibility studies have also been conducted in specific regions, such as Vietnam, to assess the economic, technical, and environmental efficiency of offshore wind power projects and identify support policies and investment obstacles [19].

Offshore wind policy studies and frameworks have been explored in several papers. One paper examines the interplay between offshore wind projects (OWPs) and fisheries within a climate change context, aiming to identify the key challenges arising from their interaction and co-existence [20]. Another paper outlines an analytical framework that guides the examination of policy mixes and diffusion of wind power in Denmark, Finland, Norway, and Sweden, with emphasis on the period 2010–2020 [21]. A case study of the Republic of Ireland analyzes the political challenges facing offshore wind deployment and the battle of ideas between alternative policy approaches [22]. A paper proposes a new risk assessment framework for offshore wind-energy-resource development, considering wind resources, the natural environment, and the geopolitical and humanistic environment [23]. Lastly, the paper emphasizes the need for a framework to characterize and quantify the scientific data addressing the conflict between offshore wind farms and fisheries, considering ecological, economic, cultural, and institutional impacts [24].

Financing models for offshore wind projects, including public-private partnerships, green bonds, and international funding mechanisms, have been explored in the literature. Judge et al. developed a model that allows for detailed financial analysis of offshore wind farms, considering different business models and financing structures [25]. Koukal and Breitner proposed a decision support tool for analyzing the project value of offshore wind energy projects within the framework of project financing, using a cash-flow model and Monte Carlo simulation to consider project risks [26]. Ozkan and Duffey highlighted the need for comprehensive analysis tools to evaluate offshore projects, taking into account site-specific factors, complex financing structures, and uncertain permitting and payment schedules [27]. Stekli and Cali explored the potential of using Distributed Ledger Technology (DLT) to crowdsource project finance for offshore wind projects, discussing the shift towards a decentralized energy system and the impact of crowdfunded equity on the levelized cost of electricity (LCOE) [28].

Methodology

This paper utilizes the Wind Atlas Methodology (WAM) to determine the offshore wind resource for Trinidad and Tobago. The wind atlas methodology was developed and used initially for the creation of the European Wind Atlas [29]. The WAM is illustrated in Fig. 1. An observational wind atlas or a generalized wind climate (GWC) is based on observed wind climates from a (dense) network of meteorological stations or, alternatively, it is a wind atlas with a geographical validity limited to the immediate surroundings of the mast (or masts) at which the observations for the wind atlas were made [30].

Fig. 1. The Wind Atlas Methodology. Inputs: (i) measured time-series of wind speed and direction. (ii) terrain topography–elevation, roughness, and obstacles. Outputs: (i) a generalized regional wind climate for the specific location. Application: energy production estimate for wind farms in the region near the meteorological station [29].

Numerical wind atlas methodologies have been devised to solve the issues of insufficient wind measurements, which is the case for Trinidad and Tobago, which renders wind resource mapping efforts through observational methodologies problematic. A so-called downscaling approach is applied, connecting the large-scale, long-term global data sets via meso- and microscale modelling to the smaller-scale local wind climates in each area. Fig. 2 shows a schematic diagram illustrating how the mesoscale modelling results are combined to give regional wind climates in the numerical wind atlas system.

Fig. 2. The numerical wind atlas methodology [30].

The large-scale wind climate data is provided by atmospheric re-analysis data, and the ERA5 dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used for the simulation period 2008–2017. The data are located on a grid with a spacing of approximately 30 km. This data is used to force the Weather Research and Forecasting (WRF) mesoscale model using a grid spacing of 3 km. A generalization process on this data is done performed on the WRF mesoscale model data. The result is a set of generalized wind climates that have the same spacing as the mesoscale data that was used to create them. The GWC data that was used in the model and subsequent analysis presented in this paper was obtained from the Global Wind Atlas version 3.0. The GWC data, in addition to Shuttle Radar Topography Mission (SRTM) topography data and digitized roughness data from Google Earth were input into the microscale modelling software WAsP to produce wind resource maps of offshore locations in Trinidad and Tobago. Wind farm locations were located offshore, with the highest resource potential, within 60 m of water depth and within the Exclusive Economic Zone (EEZ) of Trinidad and Tobago. Fig. 3 displays the five (5) offshore wind farm locations. The onshore terrain for offshore locations within a 15 km radius was included in the microscale modelling as the onshore terrain would influence the offshore wind resource map. The power and thrust curves from the IEA 15-Megawatt Offshore Reference Wind Turbine [31] was used in the offshore wind farms to obtain the annual energy production, turbine wake, and capacity factor. WAsP, an industry-standard software for wind resource assessment, siting, and energy yield calculations, estimates wind farm wake losses using several models and inputs.

Fig. 3. Offshore wind farm locations. N–North coast, E–East coast, S–South Coast, W–West Coast and T–Tobago.

WAsP uses the thrust coefficient and power curves of the wind turbines and the wind farm layout to estimate the annual energy production and the wake losses for each turbine in the farm. The result is the net annual energy production of each wind turbine, which accounts for the gross production minus the wake losses. The wake effect decay constant (k) for offshore applications was used as k is 0.04. The PARK2 model was used to calculate the wind farm wake effects.

Results and Discussion

The simulations using WAsP were carried out on the five locations illustrated in Fig. 3. The four coastal regions in Trinidad, East, South, West, and North, and the coastal waters of Tobago. The highest wind resource, as identified in the wind resource map for Tobago, was selected.

Figs. 4 and 5 display the wind speed and power density distribution for the five offshore wind sites. The highest wind speed and power density are obtained at the north coast site. The largest variation in wind speed and power density is located at the south coast location. The south coast location also has the second highest wind speeds and power density. The least variation in wind speed and power density is found at the west coast location. The west coast location is offshore of the largest industrial estate and petrochemical plants in Trinidad.

Fig. 4. Wind speed distribution at the offshore wind farm locations.

Fig. 5. Power density distribution (W/m2) at the offshore wind farm locations.

Fig. 6 compares the wind speed index for each offshore location to the daily electricity demand curve for Trinidad and Tobago. Trinidad and Tobago’s peak electricity demand occurs at around 7 pm, with general high electricity demand lasting between 6 pm and 9 pm daily. The west coast location produces its highest wind index between the 6 pm and 9 pm time period and best matches the peak electricity demand for Trinidad and Tobago when compared to the other locations.

Fig. 6. Daily wind index for offshore sites compared to a typical daily electricity demand in Trinidad and Tobago: (a) Typical daily electricity demand for Trinidad and Tobago, (b) Wind Index for the wind farm location on the east coast of Trinidad. (c) Wind Index for the wind farm location on the south coast of Trinidad. (d) Wind Index for the wind farm location on the west coast of Trinidad. (e) Wind Index for the wind farm location on the north coast of Trinidad. (f) Wind Index for the wind farm location on the Northeast coast of Tobago.Source: Global Wind Atlas and Trinidad and Tobago Electricity Commission (T&TEC).

Fig. 7 presents the wind farm locations, number of turbines, and the wind rose for each turbine, as well as an estimate of the wake loses, in red. The west coast location (Fig. 7b) is the only location where the prevailing wind is from inland. This is because the trade winds that affect the local climate are from the northeast and travel in land before reaching the offshore west coast location.

Fig. 7. The capacity and number of turbines for wind farms in Trinidad and Tobago: (a) East coast wind farm. Wind Farm: 420 MW (28 Turbines); (b) West Coast wind farm. Wind Farm: 750 MW (50 Turbines); (c) North Coast wind farm. Wind Farm: 510 MW (34 Turbines); (d) Southwest Trinidad. Wind Farm: 300 MW (20 Turbines); (e) the northeast coast wind farm in Tobago. Wind Farm: 555 MW (37 Turbines).

Table I presents a summary of the simulation results. The highest capacity factor is found at the north coast location, followed by the south coast. The largest wind farm is at the west coast location. This is because the wind resource is consistent throughout a large offshore area. The smallest offshore wind farm is located on the south coast; the exclusive economic zone is the smallest at this location, and as a result, the wind turbines are closer together, which is evident in the very high wake losses at this location.

Wind farm location Number of turbines Installed capacity (MW) Gross annual energy production (GWh) Net annual energy production (GWh) Wake loss (%) Capacity factor (%)
East coast 28 420 1249.521 1209.687 3.19 33.9
South coast 20 300 1115.768 1038.482 6.93 42.4
West coast 50 750 2241.231 2149.462 4.09 34.1
North coast 34 510 1900.084 1807.982 4.85 42.5
Tobago 37 555 1761.111 1690.758 3.99 36.2
Table I. Energy Production, Wake Losses and Capacity Factors for Offshore Wind Farms in Trinidad and Tobago

Levelized Cost of Electricity (LCOE)

The cost of fixed-bottom offshore wind turbines is expected to decrease to around 2,100/kW by 2035, with a range of $USD 2,100/kW to $USD 2,750/kW. The levelized cost of energy for a fixed bottom project could decrease to 53.1/MWh by 2035, with a range of 48.4/MWh to 59.7/MWh [32]. The long-term cost reduction potential of fixed-bottom offshore wind is quantified to be 28 ± 3 €/MWh by 100 GW cumulative capacity [33]. The cost reduction is attributed to technological improvements, economies of scale, and the maturation of supply chains [34]. The 2022 capital cost for offshore wind is given as $USD 4,640/kW [35]. This cost is for fixed-bottom offshore projects in the US.

Based on projects commissioned over the last five years, Operation and Maintenance (O&M) costs account for between USD 0.017/kWh and USD 0.030/kWh, with the lower cost range observed in established markets in Europe and China and the higher cost ranges in less-established markets where O&M supply chains have not been fully set up, e.g., the Republic of Korea (which also has lower weighted average capacity factors [36].

Using the values provided in Table II and the LCOE formula below, the LCOE for the wind farms in 2035 is calculated:

Value
Period years 20
Discount rate (%) 8
Capital cost ($/kW) in 2022 4640
Projected capital cost ($/kW) in 2035 2100
O&M cost ($/kWh) 0.03
Cost escalation rate (%) 2
Table II. Values Used in the LCOE Calculation

(1)LCOE=C+∑t=0nOMt×EPt(1+r)tTGwhere

LCOE is the levelized cost of electricity ($/kWh),

C is the total initial capital costs ($),

TG is the total electricity generated over the life of the project (kWh),

OMt is the operation and maintenance cost at year t, which includes the escalation rate ($/kWh),

EPt is the electricity production in year t (kWh),

r is the discount rate,

n is the number of years of the project lifespan.

The average domestic electricity cost in Trinidad and Tobago, which is subsidized by a below-market natural gas price, is relatively low at $USD 0.05/kWh. The LCOE using the 2022 capital cost for the offshore wind farms, presented in Fig. 8, is between 3.67 and 3.03 times the average domestic electricity rate in Trinidad and Tobago. The LCOE using the projected 2035 capital cost for offshore wind is between 1.1 and 0.96 (lower than the domestic rate) times the average domestic electricity rate.

Fig. 8. The Levelized cost of electricity for the offshore wind farms in 2022. The current average cost of domestic electricity is $0.05/kwh.

Offshore Wind and the Local Petrochemical Industry

Trinidad and Tobago has one of the largest petrochemical industries in Latin America and the Caribbean (LAC). Major petrochemical exports are ammonia, methanol, and urea [37]. The electricity sector in Trinidad and Tobago is almost exclusively based on power generation from natural gas. Fig. 10 illustrates that investing and deploying large amounts of renewable energy will displace and redirect natural gas away from the power generation sector to the higher-value petrochemical industry, a significant source of national revenue and foreign exchange.

The previous section focused on the levelized cost of electricity; however, the value proposition of offshore wind is not only for emission-free electricity production but also the redirection of natural gas to the petrochemical industry. This section quantifies the value of offshore wind in the context of redirected natural gas being used in the local petrochemical industry.

Table III presents data derived from electricity, methanol, and ammonia sales and natural gas utilization for each commodity [37].

Description 2020 ($USD) 2021 ($USD)
1 mmscf of natural gas generates Electricity sales $5,067.36 $4,779.86
1 mmscf of natural gas used for Ammonia production $5,996.31 $14,636.55
1 mmscf of natural gas used for Methanol production $7,957.80 $14,026.35
Table III. The Cost of 1 mmscf of Natural Gas When Used for Electricity Production,Ammonia Production and Methanol Production

The results presented, along with the annual net electricity production for each wind farm, are used to produce the results displayed in Fig. 9.

Fig. 9. The Levelized cost of electricity for the offshore wind farms in 2035. The current average cost of domestic electricity is $USD 0.05/kWh.

Fig. 10. Traded value of ammonia and methanol for 2020 and 2021 if the offshore wind farms were operational and redirected natural gas away from power generation to the petrochemical sector.

Fig. 9 reveals that 1 kWh of electricity generated by offshore wind, which redirects the equivalent natural gas away from power generation to the petrochemical sector, is worth $USD 61.8 in 2020 and $USD 160.17 in 2021 for ammonia and $USD 82.02 in 2020 and $USD 153.59 in 2021 for methanol.

The payback period for the 2022 cost of the capital investment of the offshore wind farms is provided in Fig. 11. The higher ammonia and methanol trade values in 2021, as a result of increased global and local economic activity post-pandemic, resulted in a payback period between 8.2 and 10.5 years.

Fig. 11. The payback period for a 2022 capital investment in offshore wind farms using the traded value of ammonia and methanol for 2020 and 2021.

Recommendation and Conclusion

The highest capacity factor for offshore wind can be found offshore of the north coast of Trinidad. The wind resource area is also relatively large, yielding a wind farm of around 510 MW if 15 MW offshore wind turbines are used. However, as illustrated in Fig. 12, the onshore of this location is mountainous, far from industrial estates, and without an existing electricity transmission infrastructure. Utilizing this location would require electrical grid infrastructure upgrades to accommodate power generation. The daily wind index at this location also does not match the daily peak electricity demand. The west location has the second lowest capacity factor; however, onshore of this location is the industrial estate with the petrochemical plants. The grid infrastructure upgrades at this location would be less than the other sites, and the daily wind index best matches the daily electricity demand. An additional study that investigates the local cost of electrical infrastructure upgrades onshore of the north coast location and the other locations would be required as part of a suite of wind prospecting studies.

Fig. 12. Trinidad and Tobago’s electricity transmission network, in green [38].

The levelized cost of electricity (LCOE) using current offshore wind capital cost is between 3.67 and 3.03 times the subsidized average domestic electricity rate. The LCOE improves when using 2035 capital cost projects to between 1.1 and 0.96 times the subsidized average domestic electricity rate. For offshore wind, it takes up to nine years, on average, from the awarding of a lease to the full commissioning of a project [39]. The LCOE for an offshore wind project in Trinidad and Tobago would be closer to the 2035 LCOE estimate than the 2022 LCOE estimate.

When considering the value of the redirected natural gas from power generation to petrochemical production, 2022 offshore wind capital investments would see a payback period of between 8.2 and 10.1 years when using 2021 ammonia prices and between 8.5 and 10.5 years when using 2021 methanol prices.

This study identifies offshore of the north and west coast of Trinidad as potential sites for an offshore wind resource assessment. The study also quantifies the importance of not only considering the LCOE for offshore wind but the value of the redirected natural gas for petrochemical production.

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