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UI IE 4550 - Power Quality Lecture

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4/27/20091Andrew KusiakIntelligent Systems Laboratory2139SeamansCenterPower QualityThe University of Iowa Intelligent Systems Laboratory2139 SeamansCenterThe University of Iowa Iowa City, Iowa 52242 - [email protected]: 319-335-5934 Fax: 319-335-5669http://www.icaen.uiowa.edu/~ankusiakOutline Power ramps Reactive power Optimization power qualityThe University of Iowa Intelligent Systems Laboratory ConclusionPower Ramps Variable winds Different horizons wind farm power – time function, e.g.:weeksThe University of Iowa Intelligent Systems Laboratoryweeks days  hours (of interest at present time) minutes Definition PRR (Power ramp rate): measure of the degree of the power change during a certain time interval[kW/min]()()Pt T PtPRRT()()Pt T PtThe University of Iowa Intelligent Systems Laboratory[%/min] t is the current time T is the time interval of the power change NPP (nameplate power) is the power of the wind farm()()100%Pt T PtPRRTNPP4/27/20092Data Description 133.5 MW rated power wind farm SCADA collected data is stored at 10-minute intervals (10-minute average data)The University of Iowa Intelligent Systems Laboratory(g) Model built of 3568 data points  Tested on 887 data pointsData DescriptionData set Start Time Stamp End Time Stamp Description1 1/1/06 1:40 AM 1/31/06 11:50 PM Total data set; 4455 observationsThe University of Iowa Intelligent Systems Laboratory2 1/1/06 1:40 AM 1/25/06 8:00 PM Training data set; 3568 observations3 1/25/06 8:10 PM 1/31/06 11:50 PM Test data set; 887 observationsT + 10 Min Power Prediction(10-min Ahead Predictions)The University of Iowa Intelligent Systems LaboratoryMetrics Used in PRR Prediction• AE: Absolute error•is the observed PRR is the predictedˆAEyyˆyyThe University of Iowa Intelligent Systems Laboratory•is the observed PRR, is the predicted PRRUnits: kW/min or %/minyy4/27/20093T + 10 min PRR Prediction(10-min Ahead Predictions)The University of Iowa Intelligent Systems LaboratoryThe unit of PRR is kW/min (135.5 MW rated power)Statistics for PRR of Top 15% of Wind Farm CapacityAEkW/min %/minMean191.701 0.1435957The University of Iowa Intelligent Systems LaboratoryStd183.894 0.1377486Max1091.341 0.8174832Min0.016 0AE = Absolute Error (135.5MW rated power)Statistics for PRR of Mid-range 20% of Wind Farm PowerAEkW/min %/minMean467.627 0.351The University of Iowa Intelligent Systems LaboratoryStd481.195 0.361Max3556.387 2.664Min8.131 0.006AE = Absolute Error (135.5 MW rated power)SummaryThe results presented were prepared in a short time for illustrative purposesThe results presented can be greatly improvedThe University of Iowa Intelligent Systems LaboratoryThe results presented can be greatly improved Confidence index is possible to develop4/27/20094Power Quality : power factor; : active power measured in W (Watts);222cosPPFSSPQPSPFPPSQThe University of Iowa Intelligent Systems Laboratory : apparent power measured in volt-amperes (VA); : reactive power measured in reactive volt-amperes (Var);  : phase angle between current and voltage. SQPower Factor0501001502002503003504004501 16 31 46 61 76 91 106 121 136 151 166 181 196 211Active power (kW) 00.20.40.60.811.21 16 31 46 61 76 91 106 121 136 151 166 181 196 211Power factor10 - minute dataThe University of Iowa Intelligent Systems Laboratory10 - minute data22.533.544.555.566.571 163146617691106121136151166181196211Wind speed (m/s)10 - m inute dataPSQPower quality improvement• Power factor is a comprehensive metric to power quality.• The controllable variables of wind turbine adjust the generator load, and thus the low power factor could be idhh fi hhiThe University of Iowa Intelligent Systems Laboratoryincreased, then the power factor impacts the harmonic distortion and transient overvoltage in the power system. • The ideal goal of wind turbine is to set power factor as one or unit power factor; however, power factor is hard to control, and thus it is usually far below one in electricity industry. Metrics for dynamic models• : predicted corresponding parameters; bdlf di t dthˆAE y y1()NiAE iMAEN1(() )1NiAE i MAEStdNˆyThe University of Iowa Intelligent Systems Laboratory•: observed values of corresponding parameters, and they could be the active power, power factor and rotor speed;• : the number of test data points used to validate the performance of the dynamic MISO models; • The small value of the MAE and Std implies a superior prediction performance of the wind turbine models.yN4/27/20095Optimization frameworkThe University of Iowa Intelligent Systems LaboratoryData descriptionData set Start Time Stamp End Time Stamp Description1 7/01/08 12:00 AM 7/31/08 11:50 PM Total data set; 4466 observations27/01/08 12 00 AM7/24/08 12 00 AMT i i d 3457 b iThe University of Iowa Intelligent Systems Laboratory27/01/08 12:00 AM7/24/08 12:00 AMTraining data set; 3457 observations3 7/25/08 12:10 AM 7/31/08 11:50 PM Test data set; 1009 observationsLow wind speed scenario77.588.5(m/s)The University of Iowa Intelligent Systems Laboratory44.555.566.51 1325374961738597109121133145Wind speed 10-minute data Optimal vs original active power 400500600700800ower (kW)The University of Iowa Intelligent Systems Laboratory01002003004001 1325374961738597109121133145Activve poOpt ima l Po wer Origina l Power4/27/20096Optimal vs original power factor 60708090100orThe University of Iowa Intelligent Systems Laboratory01020304050601 1325374961738597109121133145Power factoOpt im al PF Origina l PFOptimal vs original blade pith angle23456gle ( °)The University of Iowa Intelligent Systems Laboratory-3-2-10121 1325374961738597109121133145Picth angOptim a l PA Original PAOptimal vs original generator torque40506070torqueThe University of Iowa Intelligent Systems Laboratory0102030401 13 25 37 49 61 73 85 97 109 121 133 145Gen era to r tOptima l Torque Original TorqueOptimal vs original rotor speed15161718(rpm)The University of Iowa Intelligent Systems Laboratory10111213141 13 25 37 49 61 73 85 97 109 121 133 145Rotor speed Opt imal roto r sp eed Origina l rotor speed4/27/20097High wind speed scenario1010.51111.5d (m/s )The University of Iowa Intelligent Systems Laboratory88.599.51 1325374961738597109121133145wind speed10-minute dataOptimal vs original power output11001200130014001500er (kW)The University of Iowa


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