ENERGY YIELD ASSESSMENT

Transcription

1 Module ENERGY YIELD ASSESSMENT Gerhard J. Gerdes Workshop on Renewable Energies November 14-25, 25 Nadi, Republic of the Fiji Islands Contents power curve of wind turbine and international regulations for power curve measurements using power curve and wind data to determine energy output of a turbine at measurement site and measurement height using flow models to calculate wind and energy for different sites and height extension of results to long term time periods possible errors 2

2 Power curve overview practical power output curves follow the power in the wind curve up to the rated wind speed when rated output power is reached power curve generally dependent of mode of output control (stall pitch) rated wind speed (here 13 m/s) v rated or v nominal 3 Rules for power curve and wind speed measurements IEC (International Energy Commission) - international FGW (Fördergesellschaft Wind Energie: Support Society Wind Energy national German rules (= IEC with extra conditions) MEASNET - international (= IEC with extra conditions) IEA (International Energy Agency) Recommendation for wind speed measurements (outdated) generally rules for power measurements (relatively easy to fulfil) and wind speed measurements (more difficult) 4

3 Differences in power curves Electrical power, kw Calculated power curve 2 Measured power curve Wind speed at hub height, m/s Measured power curve and power curve given by manufacturer 5 Air density effect on power curves - stall 7 Power [kw] 6 Std.-Conditions kg/m kg/m kg/m Wind Speed [m/s] 6

4 Air density effect on power curves - pitch 7 Power [kw] 6 Std.-Conditions kg/m kg/m kg/m Wind Speed [m/s] 7 Calculation of wind turbine output two important prerequisites: thoroughly measured and evaluated wind data for the site(s) in question, and an exactly measured power curve, according to international standards, so that turbines on the world market can be compared but still for both power curve and wind data evaluation error margins exist, which make an absolute certainty for output estimation impossible in addition annual variations of wind resource for a given region can be substantial (+/- 2 % normal, up to 4 % ) 8

5 Power output estimation needed: power curve of wind turbine (generally in 1 m/s wind classes) wind speed frequency of the site (also in 1 m/s wind classes) simple multiplication in practice, spreadsheet calculation is easy AEP = Annual Energy Production E i = Energy per wind speed class i f i = Frequency of wind speed class i = Power WTG in a wind speed class i P i AEP = Ei = f i P i 9 Typical power curve 3 kw (table) v [m/s] Power Output (elec.) Power Coefficient Wind Class [kw] cp [ - ] wind class 1 from to 1 m/s; wind class 2 from 1 to 2 m/s, etc. also called bins c p,max = 42 % rated wind speed v rated = 13.5 m/s 1

6 Wind speed frequency distribution 12 1 Frequency [h/year] Total Hours per Year 876h/a Weibull parameters: k = 2, A = 6.7 m/s equals v avg = 6. m/s v Wind speed [m/s] avg = average wind speed 11 Typical power curve 3 kw 35 3 Power [kw] Wind Speed [m/s] 12

7 Energy production per wind speed bin 9' 8' 7' Annual Energy Yield kWh/a Energy [kwh] 6' 5' 4' 3' 2' 1' Wind speed [m/s] 13 Calculation of annual energy yield based on measurement Wind Wind Power frequency Energy [m/s] [mph] [kw] [h/year] [kwh/year] 1 2,2, 372,, 2 4,5, 72,, 3 6,7 3,7 941, 3481,7 4 8,9 1, 177, 177, 5 11,2 21,6 117, 23911,2 6 13,4 38,3 146, 461,8 7 15,7 62,4 92, ,2 8 17,9 93,1 759,5 779,5 9 2,1 132,6 592, 78499,2 1 22,4 181,8 435, 7983, 11 24,6 23,5 33, , ,8 269,3 21, , 13 29,1 29,5 127,5 3738, ,3 3, 77,5 2325, 15 33,6 35, 45, 13725, 16 35,8 35, 25, 7625, 17 38, 35, 15, 4575, 18 4,3 35, 7, 2135, 19 42,5 35, 3, 915, 2 44,7 35, 1,8 549, 21 47, 35,,8 244, 22 49,2 35,,3 91, ,4 35,,1 3, ,7 35,,, 25 55,9 35,,, Total 876 h kwh Frequency [h/year] Power [kw] Energy [kwh] ' 8' 7' 6' 5' 4' 3' 2' 1' Wind speed [m/s] Wind Speed [m/s] Wind speed [m/s] 14

8 Further calculations are needed From measurement height to turbine hub height From measurement site to different wind turbine sites for a planned wind farm From one year measurement period to long-term estimation 15 Measurement and long-term behaviour of wind speed Wind speed is typically measured on potential wind turbine sites for a limited period of time short-term measurement (e.g. 1 year) For the purpose of energy yield assessment this has to be done with high accuracy. To estimate energy production not only for the time of the measurement but for a longer time, information on the long-term behaviour of the wind must be used: Long-term correction has to be performed The quality of this long-term data can be lower than for the short-term measurement The quality of the long-term measurement should be stable in time 16

9 Measurement concept including long term comparison 17 Long term variation of the annual average wind speed 18% Normalised Average Production vwind_hub-height 16% 1 years sliding average (production) 14 m/s 12 m/s 14% 1 m/s 12% 8 m/s 1% 8% 6% 4% years of data 6 m/s 4 m/s 2 m/s m/s 18

10 Long Term Correlation with Measurement - Correlation - Prediction (MCP) - Method Reference-Site: Reference-Site: Available Availablelong longterm termdata + short shortterm termdata (time (time series) series) Prognosis-Site: Prognosis-Site: Average Averagetime time compatibel compatibelto to referenz-site referenz-site Measure Correlation Correlation (Regression) (Regression) of of twelve twelve sectors sectorseach each3 3 degree degree Prediction of of long longterm windspeed distribution at at prognosis-site Correlate Predict 19 Extended energy yield assessment for wind farms The evaluation of a wind speed measurement results in an energy yield, which is valid for the measurement period and the measurement height only To transfer the measurement to other sites in a wind farm area and to different heights, a micrositing model is required To extend the wind speed evaluation results to a longer time period than the measurement period, a long term correlation method is required 2

11 Transfer to different sites and height transfer to different locations h2 h1 measurement site transfer to different height (h1 to h2) 21 Methods of energy yield assessment in in situ situ wind wind measurements meteorological long long term term data data long long term term correlation micro micro --siting siting--model energy energy yield yield prediction 22

12 Wind atlas method resulting in energy yield Roughness description Obstacle description Orography description Meteorological data data Power Power curve curve calculation of of expected annual energy yield yield Power [kw] Wind Speed [m/s] Annual Annual Energy Energy Production Production AEP AEP 23 Influence of wind speed deviations on energy production A small deviation of the average wind speed around 5 m/s results in large deviation of annual energy production (AEP): wind speed deviation AEP deviation v avg = 5 m/s 1 % 2 % 2 % 45 % v avg = average wind speed 24

13 Sources of possible uncertainties Meteorological input data: Gaps in the recorded data Poor or not calibrated anemometer Damaged or malfunctioning sensors Change of obstacles in the vicinity of the met mast (trees, buildings, etc.) Calculation methods: Not suitable for complex terrain Input of roughness, obstacles and orography 25 Sources of possible uncertainties Power curve: Theoretical curve Inaccuracy of the measurements Losses: Wind farm efficiency Availability of the turbines Electrical losses / efficiencies 26

14 How to perform an energy yield assessment 1 select site for WT(s) installation access (roads, bridges, narrow through roads grid (distance, voltage, capacity) general infrastructure (lorries and cranes) perform a wind speed measurement evaluate data in generating wind speed distribution get a measured, certified WT power curve calculate energy yield from the distribution, if met-mast is located at the proposed turbine site otherwise a wind turbine siting model has to be used retrieve long-term wind data from a nearby met-station best is hourly data over 1 years or more otherwise: two wind rose tables (e.g. wind frequency in 25 wind speed classes versus 12 wind direction sectors) first table for short-term measurement duration second table for long-term measurement duration 27 How to perform an energy yield assessment 2 inspect long-term measurement-station take with you detailed map, compass, camera and GPS, if available determine exact location by means of GPS or detailed map make picture from met-mast make picture 36 around the met-mast (for landscape description), clearly identify North direction ask for height of tower or estimate make a sketch of all obstacles in the neighbourhood (estimate distance, angle and height) indicate kind (bush, tree, building) perform long term correction to gain long-term energy yield GPS = geographical positioning system 28

15 Wind speed data evaluation software: General information on wind energy: 29