Well-Being Analysis of Wind Integrated Power Systems

The paper presents well-being analysis of wind integrated electric power generating systems. An approach is presented for calculating well-being indices which gives much faster results than previously published methods. The link between the unit commitment risk criterion (UCRC) and system healthy state probability (HSPC) is illustrated using two different test systems. The method should prove useful in the decision making process of choosing an appropriate UCRC. The proposed approach extends the application of probabilistic techniques in operating reserve evaluation and determination.

[1]  Roy Billinton Criteria used by Canadian utilities in the planning and operation of generating capacity , 1988 .

[2]  R. Billinton,et al.  Considering load-carrying capability and wind speed correlation of WECS in generation adequacy assessment , 2006, IEEE Transactions on Energy Conversion.

[3]  Wenyuan Li,et al.  Reliability Assessment of Electric Power Systems Using Monte Carlo Methods , 1994 .

[4]  Roy Billinton,et al.  A basic framework for generating system operating health analysis , 1994 .

[5]  R. Billinton,et al.  A Reliability Test System for Educational Purposes-Basic Data , 1989, IEEE Power Engineering Review.

[6]  S. Watson,et al.  Short-term prediction of local wind conditions , 1994 .

[7]  M. Lange,et al.  Physical Approach to Short-Term Wind Power Prediction , 2005 .

[8]  Michael Milligan,et al.  Wind Energy and Power System Operations: A Survey of Current Research and Regulatory Actions , 2002 .

[9]  Paul Giorsetto,et al.  Development of a New Procedure for Reliability Modeling of Wind Turbine Generators , 1983, IEEE Transactions on Power Apparatus and Systems.

[10]  Roy Billinton,et al.  Reliability evaluation of power systems , 1984 .

[11]  Ronald N. Allan,et al.  Bibliography on the Application of Probability Methods in Power System Reliability Evaluation 1996-1999 , 1984 .

[12]  Gregor Giebel,et al.  The State-Of-The-Art in Short-Term Prediction of Wind Power. A Literature Overview , 2003 .

[13]  Erik Lundtang Petersen,et al.  Wind power meteorology. Part I: climate and turbulence , 1998 .

[14]  Lars Landberg,et al.  Wind Power Meteorology , 1997 .

[15]  R. Billinton,et al.  Time-series models for reliability evaluation of power systems including wind energy , 1996 .

[16]  Bipul Karki Operating reserve assessment of wind integrated power systems , 2010 .

[17]  Mahmud Fotuhi-Firuzabad,et al.  Generating system operating health analysis considering stand-by units, interruptible load and postponable outages , 1994 .

[18]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[19]  L. T. Anstine,et al.  Application of Probability Methods to the Determination of Spinning Reserve Requirements for the Pennsylvania-New Jersey-Maryland Interconnection , 1963 .

[20]  R Billinton,et al.  Effect of hourly wind trends on the peak load-carrying capability of wind-integrated power systems , 2008, 2008 40th North American Power Symposium.

[21]  Roy Billinton,et al.  Capacity reserve assessment using system well-being analysis , 1999 .

[22]  E.F. El-Saadany,et al.  One Day Ahead Prediction of Wind Speed and Direction , 2008, IEEE Transactions on Energy Conversion.

[23]  Roy Billinton,et al.  Unit Commitment Risk Analysis of Wind Integrated Power Systems , 2009 .

[24]  Roy Billinton,et al.  Security considerations in composite power system reliability evaluation , 1991 .

[25]  Ulrich Focken,et al.  Short-term prediction of the aggregated power output of wind farms—a statistical analysis of the reduction of the prediction error by spatial smoothing effects , 2002 .

[26]  Roy Billinton,et al.  A reliability framework for generating unit commitment , 2000 .

[27]  Lars Landberg,et al.  Short-term prediction of the power production from wind farms , 1999 .