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International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 06, June 2019, pp. 95-119 . Article ID: IJMET_10_06_006 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=6 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication OFFSHORE WIND RESOURCE ASSESSMENT OFF THE SOUTH AFRICAN COASTLINE Freddie L. Inambao and Kumaresan Cunden School of Mechanical Engineering, University of Kwa-Zulu Natal Durban, South Africa ABSTRACT The world is undergoing a paradigm shift as more people are becoming aware of energy consumption patterns, reinforcing the need for developing cleaner and more sustainable ways to generate electrical energy. Globally, the development of onshore wind farms is sometimes impeded by factors such as aesthetic impact, acceptance by the public, the threats to surrounding biodiversity, noise from the power plant and possible land use conflicts. Due to these concerns, offshore wind plants have been developed. Offshore wind energy is generally greater in comparison to that of onshore wind energy because the wind speeds offshore are generally higher and more constant with fewer obstructions to the wind resource. The offshore wind potential for South African coastal regions was investigated and analysed in this study. Various factors such as shipping routes, oil and gas exploration fields and possible transmission connection points were taken into consideration before selecting four data collection sites. The predominant wind direction, mean wind speed, wind shear and spatial geographic information was analysed for each site. The sites’ wind direction did not have any similarities, with each site having its own prevailing wind directions. Within the 50 m hub height, Site 2 showed the best potential based on the power density. Site 1 and Site 3 showed similar power densities to each other with Site 4 showing the lowest power density. The distance to shore ranged from 200 km to 500 km with a steep continental shelf drop to a depth of approximately 3 000 m. The study conducted shows that there is offshore wind potential off the coast of South Africa. Energy generated by this method could assist South Africa to increase access to energy, reduce expensive transmission line losses to coastal provinces, and assist the country to transition towards a more sustainable future energy mix in line with developed nations. Keywords: Offshore wind, Resource Assessment, WAsP. Cite this Article: Freddie L. Inambao and Kumaresan Cunden, Offshore Wind Resource Assessment Off the South African Coastline, International Journal of Mechanical Engineering and Technology, 10(6), 2019, pp. 95-119. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=6 http://www.iaeme.com/IJMET/index.asp 95 editor@iaeme.com Freddie L. Inambao and Kumaresan Cunden 1. INTRODUCTION The world is undergoing a paradigm shift as more people are becoming aware of energy consumption patterns, reinforcing the need for cleaner ways to generate electrical energy. The International Renewable Energy Agency (IRENA) is an intergovernmental organisation which supports countries in their efforts to attain a more sustainable energy future. Figure 1 was constructed using IRENA’s Renewable Energy Statistics databases [1]. The trend in Figure 1 indicates rapid growth in the installed renewable energy capacity over the past decade across all renewable resources. Figure 1 Total global renewable energy installed capacity During the first five years of the millennium the European market dominated the renewable energy portfolio. However, the Asian and the North American markets have now gained significant market share. Figure 2 depicts the evolution of the renewable energy capacity market share across the major continents of the world. Asia has now taken the lead with the most installed renewable capacity comprising 39.85 % (204.6 GW) of the market in comparison to the Europeans with 33.2 % (170.6 GW) [1]. Figure 2 Market share of renewable capacity 2000-2016 Onshore wind and solar photovoltaic (PV) technologies have experienced the largest amount of growth over the last decade in relation to other renewable technologies, as seen in Figure 3 [1]. This can be attributed to the maturity of technologies and rapid advancements in the respective fields of study, as well as the ease of deployment in comparison to larger thermal plants such as bioenergy and geothermal power plants. http://www.iaeme.com/IJMET/index.asp 96 editor@iaeme.com Offshore Wind Resource Assessment Off the South African Coastline Figure 3 Renewable energy technology growth In many regions of the world, the development of onshore wind farms are sometimes impeded by factors such as visual impact, acceptance by the public, threats to the surrounding biodiversity, noise from the power plant and possible land use conflicts [2]. The multiple permutations of these conflicts are likely to hinder the future development of onshore wind farms. Due to these possible future impacts, as well as the added benefit of increased specific production (1) (kWh/kWP), major developments in the world are moving towards offshore wind farms [3, 4]. The potential of offshore wind energy is greater than that of onshore wind energy. This is because the wind speeds found offshore are generally higher and more constant with less obstructions to the wind resource. Added to this, there are the fewer concerns regarding noise pollution, aesthetic imact and most other types of land-based turbine restrictions [5]. The development of offshore windfarms has led to an increase in turbine swept areas from larger turbine blades resulting in an increase in generator capacity harvesting more energy per square meter. Though the advantages are numerous, some of the disadvantages of offshore wind energy development include expensive marine foundations and the high costs of onshore electrical grid integration [3]. For the purpose of comparison, Figure 4 shows the contribution of energy produced by both areas of supply, normalised by the installed capacity during that period. Europe contributes a large amount to the growth of offshore wind installations because of limited land area available for onshore developments [6], [7]. The largest offshore wind farm in the United Kingdom was commissioned in 2012 and is the London Array, consisting of a total of 630 MW of generation capacity. A further 370 MW is planned for phase 2 development [8]. China’s first commercial offshore wind project is located close to the Donghai Bridge in Shanghai totalling 102 MW in capacity with grid supply since June 2010 [9], [10]. http://www.iaeme.com/IJMET/index.asp 97 editor@iaeme.com Freddie L. Inambao and Kumaresan Cunden Figure 4 (a) Installed capacity; (b) Normalised production This paper aims to evaluate offshore wind energy potential for the development of a conceptual offshore wind energy power plant facility off the South African coast. The investigation aims to understand the average wind speed, dominant wind direction and wind shear effects of particular locations in the region. Shipping routes and relevant bathymetry will be investigated to better understand the environmental conditions which need to be overcome before development of an offshore wind farm. 2. LITERATURE REVIEW Before developing the methodology for the offshore wind resource evaluation, an understanding of best practice was required. Murthy and Rahi [11] conducted a review of offshore wind energy assessments regarding the main characteristics required for a resource assessment. Their work outlined the various methodologies used for wind power projects and the uncertainties associated with wind energy assessments. The paper gave a basic understanding of wind behaviour through periods of change (diurnal, seasonal, monthly and annual). The authors state that a minimum data log of 1 meteorological year is required for an assessment, however, more data would lead to a more accurate estimation of energy potential for the given region. Sharma and Ahmed [12] conducted research on the wind energy potential for the Fiji islands of Kadavu and the Suva Peninsula. The authors gathered mean wind speeds and predominant wind directions for each site based on 18 month and 12 month investigation periods respectively. Wind shear effects were also investigated to understand the variation of shear http://www.iaeme.com/IJMET/index.asp 98 editor@iaeme.com Offshore Wind Resource Assessment Off the South African Coastline force with respect to height. The authors utilised the WAsP simulation tool to simulate a high resolution (5 km2) resource map for both regions. The result of the simulations showed a good potential for wind energy production. Lima et al. [13] sought to estimate the offshore wind energy potential for Ceara in Brazil in an effort to increase the maturity of the offshore wind energy sector. The study utilised the Regional Atmospheric Modeling System (RAMS) to estimate the average wind speed, direction and power density for the area. The study considered the bathymetry and the shipping traffic for the Ceara region. The authors evaluated the average wind speed for three periods consisting of El Nina, El Ninõ and Neutral years, each of which were evaluated through seasonal changes. The results showed an average wind speed of 8 m/s and a power density of roughly 720 W/m2 no matter what the period. Werapun et al. [5] conducted an offshore energy potential study for southern Thailand. The study followed a similar methodology to the previous authors’ utilising a 120m high meteorological mast measuring data at different heights along the mast. The average wind speed was seemingly low (4.28 m/s) with the dominant wind direction stemming from the North which resulted in wind power density being 85 W/m2. The area was simulated using the WAsP simulation tool for nine base cases for wind farm layout and the authors found that the capacity factors of the simulation ranged from 0.98 % to 2.68 %. Kim et al. [14] investigated the potential for offshore wind farm site selection aimed at finding the feasibility of an offshore wind farm site around the coastal regions of the Jeju islands, South Korea. The evaluation categories in this study were: energy production and economics, protected areas, human marine activities, and the marine ecology of the area. The researchers concluded that the number of feasible areas for offshore deployment was low when utilising all factors of all the categories in comparison to just using the energy potential and economics of the region alone. Mahdy and Bahaj [15] identified that there is a global gap regarding the assessment of offshore wind potential sites and thus proposed a new methodology of assessment for potential offshore sites. The methodology was based on the analytical hierarchy process in conjunction with spatial assessment within a GIS domain. The methodology was developed with the aim of assisting the scaling up of renewable energy from 1 GW to 7.5 GW in Egypt by 2020. The authors hypothesised that the increase in renewable energy would come from larger offshore wind installed capacity. Areas identified were potential sites around the Red Sea which was duly estimated to be able to accommodate 33 GW of installed capacity. The researchers concluded that the methodology which was developed could be applicable globally to produce adequate offshore wind suitability maps for potential wind power locations. 3. METHODOLOGY The main aim of this study was to identify an ideal offshore location to situate a large floating offshore wind farm to supply coastal regions of South Africa with clean renewable energy. The conceptual assessment of this task was conducted based on methodologies found in the literature. The methodology was governed by three criteria for site selection: impact on shipping routes, spatial proximity to the electrical grid, and possible impact on future offshore oil and gas exploration. Meteorological data set was obtained from the Global Wind Atlas which was developed by the Technical University of Denmark, Department of Wind Energy [16], in WAsP data file format. The data set consisted of 624 individual meteorological points containing wind resource data (Figure 5). The wind resource data was interpreted using WAsP simulation software. The data set contained wind resource data for 12 sectored wind roses at each location and associated wind profile frequency distributions at 3 hub heights of 0 m, 50 m and 200 m respectively. http://www.iaeme.com/IJMET/index.asp 99 editor@iaeme.com Freddie L. Inambao and Kumaresan Cunden The analysis of the wind vector data was first filtered by understanding the prevalent wind direction through evaluating the wind rose generated for the dataset. The wind rose along the eastern coastline of the country exhibited two distinct wind directions – either stemming from the north north east or from the south south west. Figure 5 Meteorological data points Once the resource data was obtained, the shipping routes were overlaid to gauge high and low-density shipping paths (Figure 6). The potential sites were located in positions where there was little to no marine traffic. The shipping routes were constructed using images obtained from the Marine Traffic website [17]. It is evident that the South African coast line experiences a high volume of marine traffic. Figure 6 Shipping routes [17] The second criterion was spatial proximity to the national electrical grid. The transmission electrical grid was sourced from the Africa Electrical Transmission Network (AICD) and implemented in Google Earth as shown in Figure 7 [18]. The coastal ports of South Africa are located at points a, b and c which represent the KwaZulu-Natal, Eastern Cape and Western Cape provinces respectively [19]. http://www.iaeme.com/IJMET/index.asp 100 editor@iaeme.com Offshore Wind Resource Assessment Off the South African Coastline Figure 7 Transmission electrical grid South Africa [18] From the Eskom transmission expansion plan 2016 to 2025 [19] it was found that point KwaZulu-Natal, Eastern Cape and Western Cape provinces in Figure 7 would increase by 841 MW, 609 MW and 656 MW respectively over the 10-year period. As the bulk of the power stations supplying the country are located inland, the transmission losses incurred while transmitting energy to coastal regions are high. It was hypothesised that an offshore wind farm would be able to minimise transmission losses by supplying energy to coastal regions. Added to this was the resultant decrease in the loading on the onshore electrical grid. This may allow for future capital to be transferred from many smaller distribution scale grid upgrades to prioritised transmission upgrades so as to address unserved customers or planned grid expansion. The third criterion was the location of offshore oil and gas fields. Although countries are reforming to move away from fossil fuels, the commodity trading business around oil and gas of any particular country has significant benefit to that country’s economy. Potential sites were identified in areas where there would be minimal impact on exploration of the area by interested organisations / companies. Figure 8 depicts the offshore oil and gas identified sites within the coastal region of South Africa [20]. Figure 8 Offshore oil and gas – identified sites [20] http://www.iaeme.com/IJMET/index.asp 101 editor@iaeme.com Freddie L. Inambao and Kumaresan Cunden Potential sites for offshore wind farms were assessed based on all the above-mentioned criteria. Figure 9 shows the identified potential offshore sites. The meteorological points have a spatial resolution of roughly 50 km x 60 km. Site 1 and 2 slightly overlap with two of the identified oil and gas areas, however, this was only due to the nature of the resolution of meteorological data. Figure 9 Identified potential sites Once each site’s simulated wind data was analysed from each of the meteorological points within the selected boundaries, an average wind speed for hub heights 50 m, 100 m and 200 m was calculated. Wind speed is a key factor in site analysis as it is indicative of the potential within the region for energy extraction. 4. SITE INVESTIGATION & ANALYSIS This section of the investigation analyses each of the potential sites which were assumed based on the above methodology and depicted in Figure 9 above. Wind resource data was difficult to acquire. The use of satellite imagery tools (ASCAT, QuickSCAT, RapidSCAT etc.) did not contain relevant data which could be readily used for the analysis of the wind potential at the chosen sites. The International Renewable Energy Agency (IRENA) data was more suitable. Irena is a free, online portal for the high-level assessment of renewable energy resource potential at a chosen location / site [21]. The wind resource data was obtained from the Technical University of Denmark’s (DTU) Global Wind Atlas portal which uses data from IRENA [16]. Data from this source was also used to develop the Wind Atlas of South Africa – WASA [16] which was developed for onshore wind analysis of the South African coastline by various South African research bodies such as the CSIR, South African Weather Services, University of Cape Town and the DTU Department of Wind Energy. The wind atlas was constructed using various onshore meteorological sites in conjunction with conventional forecasting tools such as the WAsP wind simulator. The online portal allows for the rough selection of points for data collection. The potential sites were mapped as estimated polygon shapes based on the co-ordinates of each of the boundary points. The resultant wind statistical data was downloaded in WAsP format to be analysed further. Wind speed and wind direction were analysed for each of the sites depicted in Figure 9. http://www.iaeme.com/IJMET/index.asp 102 editor@iaeme.com Offshore Wind Resource Assessment Off the South African Coastline 4.1. Wind Direction 4.1.1. Site 1 Site 1 is located off the eastern coast of Durban, roughly 200 km offshore from the Durban harbour in a south east direction or 115º bearing. The site has an estimated perimeter of 600 km and an estimated surface area of ± 21 000 km2. Figure 10 is a graphical representation of Site 1. The site encompassed 11 of the meteorological data points obtained from DTU Global Wind Atlas [16]. Figure 10 Potential – Site 1 A wind rose is a vector plot which denotes direction and frequency respectively. A wind rose developed from the wind resource data comprises 12 sectors where Sector 1 encompasses a bearing of 345º to 15º and thus the midpoint for Sector 1 of the wind rose plots was 0º with a 15º arc span on either side (Figure 11). Once a common understanding of the demarcation of the sector boundaries was developed, the sectors within the wind rose were utilised as means of reference to establish which direction the wind stemmed from for all the potential sites under investigation. Figure 11 Site 1 – Wind rose plots http://www.iaeme.com/IJMET/index.asp 103 editor@iaeme.com Freddie L. Inambao and Kumaresan Cunden The most predominant wind directions were found to be Sectors 2 and 8 of each of the wind roses for Site 1. The average wind speed for the area was calculated based on the mean wind speeds of each of the meteorological stations analysed. The average wind speed for hub heights 50 m, 100 m and 200 m were 9.19 m/s, 9.25 m/s and 9.34 m/s respectively. 4.1.2. Site 2 Site 2 is a larger site than Site 1. It is located roughly 300 km south of Port Elizabeth. It has an estimated perimeter reading of 1 250 km and an estimated surface area of ± 79 000 km2. The site is located in a potential retroflection zone (2) for ocean currents as found by Cunden [22]. Figure 12 is a graphic representation of the potential of Site 2. As seen in Figure 9, Site 2 has minimum shipping route impacts but may lie on a possible potential oil and gas field. From the meteorological data collected, the site comprised 36 individual meteorological data points which were analysed at various hub heights. Figure 12 Potential – Site 2 Within Site 2, the prevailing wind direction was found to be in Sectors 3, 4, 9, 10, and 11 (Figure 13). This indicates that the wind direction changes through an annual cycle. The average wind speed for hub heights 50 m, 100 m and 200 m were 9.47 m/s, 9.55 m/s and 9.68 m/s respectively. Figure 13 Site 2 – Wind rose plots http://www.iaeme.com/IJMET/index.asp 104 editor@iaeme.com