Maximizing Firm Wind Connection to Security Constrained Transmission Networks

Prudent use of existing transmission capacity could be achieved by an optimal allocation of wind capacity to distinct transmission nodes. The statistical interdependency of geographically separate wind sites and the partially-dispatchable nature of wind power require a collective analysis of all potential wind farms over an extended time-frame in any optimized transmission planning study. The methodology presented in this paper separates this large optimization problem into smaller subtasks, including a year-long sequential time series hourly integer unit commitment, a linear dc load-flow network model with hourly security constraints, and a linear programming optimization model to estimate the maximum firm wind energy penetration for a given network. A novel maximal- vector based constraint redundancy analysis is employed to significantly reduce the linear programming optimization dimensionality. Firm wind capacity connections are facilitated in this paper - i.e., those to which wind curtailment to manage congestion is not applicable within a typical system ¿planning¿ timeframe analysis. Each bus is allocated firm capacity on the basis of maximizing the possible firm wind energy penetration in the transmission system as a whole, while preserving traditional network security standards.

[1]  E. Vittal,et al.  Varying penetration ratios of wind turbine technologies for voltage and frequency stability , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[2]  J. Edward Jackson,et al.  A User's Guide to Principal Components: Jackson/User's Guide to Principal Components , 2004 .

[3]  Heike Brand,et al.  WILMAR: A Stochastic Programming Tool to Analyze the Large-Scale Integration of Wind Energy , 2009 .

[4]  M. O'Malley,et al.  Unit Commitment for Systems With Significant Wind Penetration , 2009, IEEE Transactions on Power Systems.

[5]  G. Papaefthymiou,et al.  Using Copulas for Modeling Stochastic Dependence in Power System Uncertainty Analysis , 2009, IEEE Transactions on Power Systems.

[6]  Integration of wind power into Alberta’s electric system and market operation , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[7]  Franco P. Preparata,et al.  Sequencing-by-hybridization revisited: the analog-spectrum proposal , 2004, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[8]  Chun-Lien Su Probabilistic load-flow computation using point estimate method , 2005, IEEE Transactions on Power Systems.

[9]  S.T. Lee,et al.  Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion , 2004, IEEE Transactions on Power Systems.

[10]  C. Chellappan,et al.  A heuristic approach for identification of redundant constraints in linear programming models , 2006, Int. J. Comput. Math..

[11]  C.D. Vournas,et al.  Application of interruptible contracts to increase wind-power penetration in congested areas , 2004, IEEE Transactions on Power Systems.

[12]  Donald Kossmann,et al.  Shooting Stars in the Sky: An Online Algorithm for Skyline Queries , 2002, VLDB.

[13]  C. W. Taylor Power System Voltage Stability , 1993 .

[14]  Seungjin Choi,et al.  Independent Component Analysis , 2009, Handbook of Natural Computing.

[15]  Philip E. Gill,et al.  Practical optimization , 1981 .

[16]  Jarek Gryz,et al.  Maximal Vector Computation in Large Data Sets , 2005, VLDB.

[17]  Danny Pudjianto,et al.  The new transmission arrangements in the UK , 2009, 2009 IEEE Power & Energy Society General Meeting.

[18]  J. Dulá,et al.  A new procedure for identifying the frame of the convex hull of a finite collection of points in multidimensional space , 1996 .

[19]  Yoshiyuki Kono,et al.  Dynamic voltage support with the rector SVC in California’s San Joaquin Valley , 2008, T&D 2008.

[20]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[21]  Dick Duffey,et al.  Power Generation , 1932, Transactions of the American Institute of Electrical Engineers.

[22]  Philip G. Hill,et al.  Power generation , 1927, Journal of the A.I.E.E..

[23]  D. J. Burke,et al.  Optimal firm wind capacity allocation to power systems with security constraints , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[24]  S.T. Lee For the Good of the Whole , 2007, IEEE Power and Energy Magazine.

[25]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[26]  Dorota Kurowicka,et al.  Integration of stochastic generation in power systems , 2006 .

[27]  W. Marsden I and J , 2012 .

[28]  J. Dulá Geometry of optimal value functions with applications to redundancy in linear programming , 1994 .

[29]  B. Klockl Multivariate Time Series Models Applied to the Assessment of Energy Storage in Power Systems , 2008, Proceedings of the 10th International Conference on Probablistic Methods Applied to Power Systems.