Developing a successful wind power plant is a complex, multi-stage process requiring meticulous technical analysis and strategic planning from concept to completion. Our project development services guide investors and developers through every critical stage, ensuring each project is technically sound, financially viable, and fully compliant with all regulatory requirements.
In wind power plant projects, it is crucial to select a site with both high energy potential and reduced constraint to minimise the time between site selection and the construction phase.
The point of connection to the electricity grid is determined to define the project’s integration path.
Areas predicted to be high energy potential are identified using mesoscale wind atlases, measurements taken at nearby stations, and production data from operational wind farms.
Preliminary micrositing and energy production assessment studies are conducted using estimated wind resources and site boundaries. A preliminary feasibility study determines production values, market-based costs, and project payback period, considering implementation conditions.
Standards: IEC61400-50-1:2022, IEC61400-50-2:2022, FGW TG6, MEASNET Procedure v3, IEC61400-15-1, ISO/IEC Guide 98-3:2008
High energy production estimates are the most important factor in determining project financing conditions. Another factor as important as wind speed in achieving high energy production estimates is uncertainty. In order to keep the uncertainties calculated as a result of an analysis conducted in accordance with FGW and MEASNET standards to a minimum, the measurement campaign must be designed by expert engineers in accordance with the standards.
Conventional
Systems where local sensors are positioned on pipe or lattice measurement towers to collect wind speed and direction parameters are referred to as conventional wind measurement systems.
Systems that measure data at the point where they are installed and transmit the measured data to a data storage device via electrical signals using cables are called local sensors. Two types of local measurement devices that stand out are cup anemometers and sonic anemometers. Sonic anemometers provide data with higher accuracy than cup anemometers. However, cup anemometers are less expensive than sonic anemometers.
Cup anemometers operate entirely on a mechanical system. As they are a local system, a station is constructed at the desired measurement height and anemometers are mounted on it. Sonic anemometers are less affected by environmental factors compared to cup anemometers.
All devices used must comply with the standards defined by WMO, ISO, IEC, FGW, and MEASNET.
Remote Sensing (LIDAR/SODAR)
According to IEC61400-12-1 standards, measurements are required at different levels up to the tower height for wind turbine performance and wind resource assessment according to MEASNET and FGW standards.
In the 1990s, turbines with an average tower height of 50 m were used, and it was possible to measure wind using tubular towers. By 2010, tower heights had reached 80 m, necessitating the use of lattice wind measurement stations.
After 2010, with tower heights exceeding 100 metres, the installation costs of lattice towers increased. Consequently, remote sensing LIDAR/SODAR systems became economically viable and began to be used as an alternative for measurements at 100 metres and above.
The most important consideration in measurement campaigns designed using remote sensing systems is that while LIDAR/SODAR alone is sufficient for measurement in areas where homogeneous wind flow is expected , in areas where heterogeneous wind flow is expected, continuous verification with a reference cup anemometer is required.
While SODAR systems stand out for their cost-effectiveness, LIDAR systems have proven themselves as a technology that is less affected by environmental conditions and provides more stable measurements in complex sites. For more detailed information on remote sensing technology, please consult USENS.
Tower structures connected by rod wires, particularly those used for wind measurement, are negatively affected by seasonal temperature changes. In steel structures anchored to foundations with multiple wires, the verticality of the mast is compromised due to expansion or contraction occurring at different rates in each wire. The resulting distortion in the station’s alignment can cause changes in the side arm angles, tilt in the side arms, and even in extreme cases the collapse of the station.
Periodic maintenance, performed at intervals determined by the station type, should correct structural deterioration at the station, extending its lifespan while also improving measurement quality. Tilts occurring in the arms to which the speed sensors are attached cause errors of up to 5% in wind energy predictions.
Wind Resource Assessment
Accurate assessment of the wind resource is crucial for all stakeholders involved in financing renewable energy projects, which are supply-driven. It is essential to work with an experienced and independent expert to minimise the error between energy production assessments made using methods compliant with MEASNET and FGW standards and the actual production results.
A site visit is necessary to accurately model the terrain and vegetation cover of the site. During the site visit, the wind measurement tower and equipment are also inspected. During the inspection, the compliance of the measurement station with the IEC 61400-50-1 standard and the angles of the side arms and lightning rod are examined. The side arm angles are of great importance for verifying the direction sensor measurements.
After filtering out measurement data considered to be erroneous, intra-station and inter-station data synthesis (if possible) is performed to increase the data coverage. The correlation between the long-term data sets of sufficient quality and the measurement data collected on site is checked, and the potential for use as a long-term source is investigated.
In the final stage of the analysis, the vertical profile of wind speed is derived using measurement data, and this profile is used to calculate the wind resource at hub height. The calculated average wind speed, extreme wind speeds and turbulence intensity values are used to determine the site class.
For remote sensing systems to be used in wind farm energy production assessment studies, the flow must be homogeneous in the volume where measurements are taken. Remote sensing systems can be used in moderately complex terrains where the flow is not homogeneous, provided that CFD correction and/or verification with a conventional measurement station is performed. The algorithm to be used for CFD correction must have proven itself in tests conducted on different complexity classes, and these tests must be reported in detail to verify the accuracy of the algorithm.
In areas of medium and high complexity, it is not appropriate to use remote sensing systems to measure the wind source alone with today’s technology. However, even in such areas, they can be used alongside conventional measurement systems to reduce vertical extrapolation uncertainties.
In power plants where production data is available for 12 months or more, the production data itself provides the best input for determining the wind resource in that area. The 10-minute resolution SCADA data from the wind turbines is used in the assessment.
After filtering out data considered erroneous, turbine-to-turbine data synthesis (where possible) is performed to increase the data coverage. Wind speed and Production data is scaled to a longer period if a long-term data source of sufficient quality is available.
Wind farms may have been constructed in different phases. Changes in the number of turbines affect production losses experienced by the turbines. In sites where such changes have occurred, a detailed loss study should be carried out, taking into account the commissioning date of each turbine.
Availability rates should be reviewed using historical data. The formula defined in the türbine supply agreement is used for this purpose.
As a result of the study, long-term wind frequency distribution, gross energy production, power curve and loss factors (availability, electrical efficiency, turbine performance, environmental and constraint-related) are calculated for each turbine location.
The frequency distribution at tower height obtained using SCADA data can be used as input for the energy production assessment study or SCADA analysis results can be used to correct the flow model created using wind measurement data.
Standards: IEC61400-50-1:2022, IEC61400-50-2:2022, IEC61400-50-3:2022, IEC 61400-12-6:2022, IEC61400-26-1:2019, FGW TG6, MEASNET Procedure v3, IEC61400-15-1, ISO/IEC Guide 98-3:2008
Manufacturers define the basic design requirements to ensure the structural integrity of wind turbines. In sites where the site climate conditions meet these requirements, an adequate level of protection against damage from all loads will be provided throughout the planned service life. The meteorological parameters calculated at the measurement locations as summarised below shall be modelled at tower height at the turbine points to determine whether the turbine types under assessment are suitable for the site.
Micro-siting and Energy Production Assessment
The calculation steps for Micro-siting and Energy Production Assessment of a wind power plant are listed below.
Using meteorological measurements collected at one or more points on the project site, the wind speed frequency distribution at tower height—by direction and air density—is calculated. The main inputs for the flow model, including contour elevation, roughness, forest maps and obstacles, must be digitised with high accuracy.
In complex terrain, the error in establishing wind flow using a linear model is high, resulting in high uncertainty in energy production estimates. It is possible to significantly reduce uncertainties by supporting energy production estimates with a non-linear flow model. For turbines in operation, the flow model can also be calibrated by evaluating SCADA data with a 10-minute resolution in areas where production data is available.
Based on the wind resource map, the planned project capacity, site class and other constraints are taken into account, and the optimal turbine layout for the project site is created. In studies conducted for capacity increase, the wake effect of the planned turbines on the existing power plant and the associated additional losses must be evaluated, taking into account the interaction with the existing wind turbines in the plant.
Gross energy production is estimated by calculating long-term energy production for each turbine point, excluding losses. The main factors causing the losses are calculated as summarised below. Net energy production estimates are obtained by reducing the losses from the gross energy estimate. For sites where production data for turbines in operation is available, actual losses are calculated by evaluating SCADA data with a 10-minute resolution.
The uncertainties associated with each step of the analysis and defined losses are calculated. Each uncertainty component is then combined according to its relationship with the others to calculate the total uncertainty in the annual energy production estimate and the probability distribution (Probability of exceedence).
Standards: IEC61400-1:2019, IEC61400-12-5:2022, IEC61400-26-1:2019, IEC61400-12-4:2020, IEC 61400-50 series, FGW TG5, FGW TG6, FGW TG10, MEASNET Procedure v3, IEC61400-15-1, ISO/IEC Guide 98-3:2008
The variation in energy production over the 8,760 hours of the year is calculated by following the steps below. The uncertainty in the calculation of hourly energy production is much higher than that in the calculation of annual energy production. Standards: IEC61400-1:2019, IEC61400-12-5:2022, IEC61400-26-1:2019, IEC61400-12-4:2020, FGW TG6, MEASNET Procedure v3, IEC61400-15-1, ISO/IEC Guide 98-3:2008
Using the selected long-term source, the speed and direction data is extended to cover a period of at least 20 years.
A theorectical year that best represents the extended time series is calculated to obtain a wind speed and direction data set covering 8760 hours.
Air-density-corrected wind speed and direction series are obtained for each turbine using direction-dependent flow model coefficients.
Gross energy is calculated per turbine using the 8,760-hour series, with plant output summed and adjusted for electrical efficiency losses.
Net energy production is calculated by applying direction-dependent losses, like wake and sector effects, and seasonal losses such as icing based on temperature and humidity.
Wind power plant production may be constrained for the reasons summarised below.
Losses due to limitations are predicted using hourly energy production for factor 1 and 3. For factor 2, sectoral limitations are applied to each turbine depending on turbine technology and approach distances, and losses due to this are predicted.
Standards: IEC61400-1:2019, IEC61400-12-5:2022, IEC61400-26-1:2019, IEC61400-12-4:2020, FGW TG6, MEASNET Procedure v3, IEC61400-15-1, ISO/IEC Guide 98-3:2008
Environmental or social constraints (bats, noise, flicker etc.)
Sectoral restrictions due to interaction between wind turbines
Grid limits in wind and hybrid energy production plants
This is specified in the "List of Information and Documents Required for EPDK Preliminary Licence and Licence Applications". These documents are submitted to the institution in a complete manner, with the necessary work carried out and document approvals obtained.
The site boundary is established in accordance with the "Technical Assessment Regulation" published by EIGM, using the turbine layout or wind potential maps created for the project site.
During the completion of construction permits for RES projects, opinions must be obtained from the relevant institutions. uSens prepares the application files and shares the document tracking numbers with the Employer after submitting them to the institutions. Upon request, the status of applications is monitored monthly, and after opinions are obtained from all institutions, a summary of the restriction status is shared with the Employer.