Temperature and Wind Distribution Effects on Wind Energy Production in Adrar Region (Southern Algeria)

The hottest transitions occur in the summer, as we notice during this period the peak of electricity consumption in Adrar, where the electricity network must use all kinds of energy, especially the wind energy produced by Cabertein wind farm. We evaluated the effect of temperature and wind distribution on the energy produced by one of Gamesa G52 wind turbines, and this was done by studying the wind distribution and determining the number of hours per year according to five cases. Finally, to estimate the monthly produced energy, we used a logical temperature equation, and then we determined the seasonal and annual energy. Low winds are the only reason why wind turbines are unable to produce electricity for a monthly period ranging from 152 An hour (May) to 274 hours (September), meaning that the seasonal production stop, for this reason, ranges between 590 hours (spring) and 779 hours (summer), with an average of 2736 hours per year, while temperatures did not constitute an obstacle to electricity production except. In three months for a short period of 2 hours (June and July) and 22 hours (August), affecting production in the summer season, with an estimated time of 26 hours.

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Wake and Turbulence Analysis for Wind Turbine Layouts in an Island

E3S Web of Conferences ◽

10.1051/e3sconf/20186406010 ◽

2018 ◽

Vol 64 ◽

pp. 06010

Author(s):

Bachhal Amrender Singh ◽

Vogstad Klaus ◽

Lal Kolhe Mohan ◽

Chougule Abhijit ◽

Beyer Hans George

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Energy Production ◽

Wind Farm ◽

Full Length Paper ◽

Turbulence Analysis ◽

Wake Model ◽

Wind Resources

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.

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Wind-farm layout optimisation using a hybrid Jensen–LES approach

10.5194/wes-2016-15 ◽

2016 ◽

Cited By ~ 1

Author(s):

Vahid S. Bokharaie ◽

Pieter Bauweraerts ◽

Johan Meyers

Keyword(s):

Wind Turbines ◽

Energy Production ◽

Wind Farm ◽

Rectangular Domain ◽

Hybrid Combination ◽

Wake Interaction ◽

Large Eddy ◽

Wind Distribution ◽

Online Tuning

Abstract. Given a wind-farm with known dimensions and number of wind-turbines, we try to find the optimum positioning of wind-turbines that maximises wind-farm energy production. In practise, given that optimisation has to be performed for many wind directions and taking into account the yearly wind distribution, such an optimisation is computationally only feasible using fast engineering wake models such as, e.g., the Jensen model. These models are known to have accuracy issues, in particular since their representation of wake interaction is very simple. In the present work, we propose an optimisation approach that is based on a hybrid combination of Large-Eddy Simulations (LES) and the Jensen model, in which optimisation is mainly performed using the Jensen model, and LES is used at a few points only during optimisation for online tuning of the wake-expansion coefficient in the Jensen model, and for validation of the results. An optimisation case study is considered, in which the placement of 30 turbines in a 4 by 3 km rectangular domain is optimised in a neutral atmospheric boundary layer. Both optimisation for single wind direction, and multiple wind directions are discussed.

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Wind-farm layout optimisation using a hybrid Jensen–LES approach

Wind Energy Science ◽

10.5194/wes-1-311-2016 ◽

2016 ◽

Vol 1 (2) ◽

pp. 311-325 ◽

Cited By ~ 7

Author(s):

Vahid S. Bokharaie ◽

Pieter Bauweraerts ◽

Johan Meyers

Keyword(s):

Wind Turbines ◽

Energy Production ◽

Wind Farm ◽

Rectangular Domain ◽

Eddy Simulation ◽

Wake Interaction ◽

Large Eddy ◽

Wind Distribution ◽

Online Tuning

Abstract. Given a wind farm with known dimensions and number of wind turbines, we try to find the optimum positioning of wind turbines that maximises wind-farm energy production. In practice, given that optimisation has to be performed for many wind directions, and taking into account the yearly wind distribution, such an optimisation is computationally only feasible using fast engineering wake models such as the Jensen model. These models are known to have accuracy issues, in particular since their representation of wake interaction is very simple. In the present work, we propose an optimisation approach that is based on a hybrid combination of large-eddy simulation (LES) and the Jensen model; in this approach, optimisation is mainly performed using the Jensen model, and LES is used at a few points only during optimisation for online tuning of the wake-expansion coefficient in the Jensen model, as well as for validation of the results. An optimisation case study is considered, in which the placement of 30 turbines in a 4 km by 3 km rectangular domain is optimised in a neutral atmospheric boundary layer. Optimisation for both a single wind direction and multiple wind directions is discussed.

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Syria’s wind resources: Outlook for the Future

E3S Web of Conferences ◽

10.1051/e3sconf/202015706032 ◽

2020 ◽

Vol 157 ◽

pp. 06032

Author(s):

Ahmad Al Jamil ◽

Gennady Sidorenko

Keyword(s):

Wind Turbines ◽

Power Factor ◽

Performance Indicators ◽

Energy Cost ◽

Energy Production ◽

Wind Farm ◽

Electricity Production ◽

Economic Potential ◽

Wind Speeds ◽

Wind Resources

15 locations with wind speeds of more than 5 m/s were explored among 24 locations across Syria. Wind data from these locations was analyzed using the Weibull distribution, along with 15 different turbines. Three performance indicators were calculated and compared between each other: annual energy production, power factor (θ) and energy cost (z). The economic potential was calculated and the economic efficiency of wind turbines was studied on the basis of optimization of wind farm parameters that helped to find an option that provides the lowest price for electricity production on wind turbines. The study reveals that E70 71m 2300kw is the optimal turbine in all areas (from the places under consideration), both in terms of the highest efficiency and the lowest energy cost. The results show that the area of Sokhna has the largest economic potential because of the big space suitable for the establishment of wind turbines. Using the proposed wind farm scenario until 2030 is able to cover the deficit by 7.22%.

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Wealth of Wind and Visitors: Tourist Industry Attitudes towards Wind Energy Development in Iceland

Land ◽

10.3390/land10070693 ◽

2021 ◽

Vol 10 (7) ◽

pp. 693

Author(s):

Anna Dóra Sæþórsdóttir ◽

Margrét Wendt ◽

Edita Tverijonaite

Keyword(s):

Land Use ◽

Wind Energy ◽

Wind Turbines ◽

Wind Farm ◽

Service Providers ◽

Wind Farms ◽

Energy Development ◽

Tourism Industry ◽

Land Use Conflicts ◽

Wind Energy Development

The interest in harnessing wind energy keeps increasing globally. Iceland is considering building its first wind farms, but its landscape and nature are not only a resource for renewable energy production; they are also the main attraction for tourists. As wind turbines affect how the landscape is perceived and experienced, it is foreseeable that the construction of wind farms in Iceland will create land use conflicts between the energy sector and the tourism industry. This study sheds light on the impacts of wind farms on nature-based tourism as perceived by the tourism industry. Based on 47 semi-structured interviews with tourism service providers, it revealed that the impacts were perceived as mostly negative, since wind farms decrease the quality of the natural landscape. Furthermore, the study identified that the tourism industry considered the following as key factors for selecting suitable wind farm sites: the visibility of wind turbines, the number of tourists and tourist attractions in the area, the area’s degree of naturalness and the local need for energy. The research highlights the importance of analysing the various stakeholders’ opinions with the aim of mitigating land use conflicts and socioeconomic issues related to wind energy development.

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A Comparative Assessment for the Potential Energy Production from PV Installation on Residential Buildings

Sustainability ◽

10.3390/su122410344 ◽

2020 ◽

Vol 12 (24) ◽

pp. 10344

Author(s):

Sameh Monna ◽

Adel Juaidi ◽

Ramez Abdallah ◽

Mohammed Itma

Keyword(s):

Potential Energy ◽

Energy Production ◽

Residential Buildings ◽

Electricity Consumption ◽

Residential Building ◽

Electricity Production ◽

Energy Sustainability ◽

Pv Systems ◽

Residential Units ◽

Future Consumption

This paper targets the future energy sustainability and aims to estimate the potential energy production from installing photovoltaic (PV) systems on the rooftop of apartment’s residential buildings, which represent the largest building sector. Analysis of the residential building typologies was carried out to select the most used residential building types in terms of building roof area, number of floors, and the number of apartments on each floor. A computer simulation tool has been used to calculate the electricity production for each building type, for three different tilt angles to estimate the electricity production. Tilt angle, spacing between the arrays, the building shape, shading from PV arrays, and other roof elements were analyzed for optimum and maximum electricity production. The electricity production for each household has been compared to typical household electricity consumption and its future consumption in 2030. The results show that installing PV systems on residential buildings can speed the transition to renewable energy and energy sustainability. The electricity production for building types with 2–4 residential units can surplus their estimated future consumption. Building types with 4–8 residential units can produce their electricity consumption in 2030. Building types of 12–24 residential units can produce more than half of their 2030 future consumption.

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Effect of Wind Turbine Classes on the Electricity Production of Wind Farms in Cyprus Island

Conference Papers in Energy ◽

10.1155/2013/750958 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 2

Author(s):

Yiannis A. Katsigiannis ◽

George S. Stavrakakis ◽

Christodoulos Pharconides

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Energy Production ◽

Wind Farms ◽

Electricity Production ◽

Wind Speeds ◽

Wind Potential

This paper examines the effect of different wind turbine classes on the electricity production of wind farms in two areas of Cyprus Island, which present low and medium wind potentials: Xylofagou and Limassol. Wind turbine classes determine the suitability of installing a wind turbine in a particulate site. Wind turbine data from five different manufacturers have been used. For each manufacturer, two wind turbines with identical rated power (in the range of 1.5 MW–3 MW) and different wind turbine classes (IEC II and IEC III) are compared. The results show the superiority of wind turbines that are designed for lower wind speeds (IEC III class) in both locations, in terms of energy production. This improvement is higher for the location with the lower wind potential and starts from 7%, while it can reach more than 50%.

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Tourist Viewshed Externalities and Wind Energy Production

Agricultural and Resource Economics Review ◽

10.1017/age.2017.18 ◽

2017 ◽

Vol 46 (2) ◽

pp. 224-241 ◽

Cited By ~ 6

Author(s):

Jacob R. Fooks ◽

Kent D. Messer ◽

Joshua M. Duke ◽

Janet B. Johnson ◽

Tongzhe Li ◽

...

Keyword(s):

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Energy Production ◽

Hotel Room ◽

Negative Effect ◽

The Impact ◽

Large Wind

This study uses an experiment where ferry passengers are sold hotel room “views” to evaluate the impact of wind turbines views on tourists’ vacation experience. Participants purchase a chance for a weekend hotel stay. Information about the hotel rooms was limited to the quality of the hotel and its distance from a large wind turbine, as well as whether or not a particular room would have a view of the turbine. While there was generally a negative effect of turbine views, this did not hold across all participants, and did not seem to be effected by distance or hotel quality.

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Inter-annual variability of wind climates and wind turbine annual energy production

10.5194/wes-2018-48 ◽

2018 ◽

Author(s):

Sara C. Pryor ◽

Tristan J. Shepherd ◽

Rebecca J. Barthelmie

Keyword(s):

Standard Deviation ◽

Wind Energy ◽

Wind Turbine ◽

Energy Production ◽

Wind Farm ◽

Wind Farms ◽

Wind Speeds ◽

Annual Variability ◽

Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

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Offshore wind energy – South Africa’s untapped resource

Journal of Energy in Southern Africa ◽

10.17159/2413-3051/2020/v31i4a7940 ◽

2020 ◽

Vol 31 (4) ◽

pp. 26-42

Author(s):

Gordon Rae ◽

Gareth Erfort

Keyword(s):

South Africa ◽

Wind Energy ◽

South African ◽

Electricity Generation ◽

Wind Farm ◽

Energy Resource ◽

Electricity Consumption ◽

Offshore Wind ◽

Offshore Wind Energy ◽

Multi Criteria Evaluation

In the context of the Anthropocene, the decoupling of carbon emissions from electricity generation is critical. South Africa has an ageing coal power fleet, which will gradually be decommissioned over the next 30 years. This creates substantial opportunity for a just transition towards a future energy mix with a high renewable energy penetration. Offshore wind technology is a clean electricity generation alternative that presents great power security and decarbonisation opportunity for South Africa. This study estimated the offshore wind energy resource available within South Africa’s exclusive economic zone (EEZ), using a geographic information system methodology. The available resource was estimated under four developmental scenarios. This study revealed that South Africa has an annual offshore wind energy production potential of 44.52 TWh at ocean depths of less than 50 m (Scenario 1) and 2 387.08 TWh at depths less than 1 000 m (Scenario 2). Furthermore, a GIS-based multi-criteria evaluation was conducted to determine the most suitable locations for offshore wind farm development within the South African EEZ. The following suitable offshore wind development regions were identified: Richards Bay, KwaDukuza, Durban, and Struis Bay. Based on South Africa’s annual electricity consumption of 297.8 TWh in 2018, OWE could theoretically supply approximately 15% and 800% of South Africa’s annual electricity demand with offshore wind development Scenario 1 and 2 respectively.

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