A chance constrained programming approach to transmission system expansion planning

The transmission system plays a critical role in providing access to all participants in a competitive electricity market for supply and delivery of electric power. Deregulation of the power industry brings many new challenges to the transmission system optimal planning problem, such as how to handle uncertain factors concerning the locations and capacities of new power plants as well as the demand growth for the transmission system planning period studied. Although the transmission system optimal planning problem has been extensively studied, available standard optimization models and methods cannot well solve this problem for the competitive electricity market environment with many uncertain factors involved. Given this background, a new method for the optimal transmission system expansion planning based on chance constrained programming is presented in this paper with several uncertain factors such as the locations and capacities of new power plants as well as demand growth well taken into account. A stochastic optimization model is first formulated under the presumption that the locations and capacities of new power plants and future load demands could be modeled as specified probability distributions. A method is then presented for solving the optimization problem using the well-known Monte Carlo simulation method and genetic algorithm. Finally, a numerical example is served for illustrating the essential features of the developed model and method.

[1]  Ruben Romero,et al.  Transmission system expansion planning by an extended genetic algorithm , 1998 .

[2]  K. E. Bollinger,et al.  Applications of artificial intelligence in power systems , 1997 .

[3]  R. Yokoyama,et al.  Transmission expansion planning using neuro-computing hybridized with genetic algorithm , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[4]  X. Wang,et al.  Modern power system planning , 1994 .

[5]  Vincent Del Toro,et al.  Electric Power Systems , 1991 .

[6]  A. Charnes,et al.  Chance-Constrained Programming , 1959 .

[7]  Milan S. Ćalović,et al.  A new decomposition based method for optimal expansion planning of large transmission networks , 1991 .

[8]  A. R. Abdelaziz,et al.  Genetic algorithm-based power transmission expansion planning , 2000, ICECS 2000. 7th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.00EX445).

[9]  João Tomé Saraiva,et al.  Impact on some planning decisions from a fuzzy modelling of power systems , 1993 .

[10]  J. M. Areiza,et al.  Transmission network expansion planning under an improved genetic algorithm , 1999 .

[11]  Francisco D. Galiana,et al.  Expert systems in transmission planning , 1992, Proc. IEEE.

[12]  J. L. Ceciliano,et al.  Transmission network planning using evolutionary programming , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[13]  A. Ekwue,et al.  Transmission System Expansion Planning by Interactive Methods , 1984, IEEE Power Engineering Review.

[14]  Laura Bahiense,et al.  A Mixed Integer Disjunctive Model for Transmission Network Expansion , 2001 .

[15]  Fushuan Wen,et al.  Transmission planning and investment under competitive electricity market environment , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[16]  H. M. Merrill,et al.  Conflicting objectives and risk in power system planning , 1993 .

[17]  R. S. Chanda,et al.  Application of computer software in transmission expansion planning using variable load structure , 1994 .

[18]  Mario Pereira,et al.  Application Of Sensitivity Analysis Of Load Supplying Capability To Interactive Transmission Expansion Planning , 1985, IEEE Transactions on Power Apparatus and Systems.

[19]  R. Hackam,et al.  New Transmission Planning Model , 1989, IEEE Power Engineering Review.

[20]  Ahmed H. El-Abiad,et al.  Transmission Planning Using Discrete Dynamic Optimizing , 1973 .

[21]  H. Rudnick.  Planning in a Deregulated Environment in Developing Countries: Bolivia, Chile, and Peru , 1996, IEEE Power Engineering Review.

[22]  Marija D. Ilic,et al.  A global planning methodology for uncertain environments: application to the Lebanese power system , 1995 .

[23]  Fushuan Wen,et al.  Transmission network optimal planning using the tabu search method , 1997 .

[24]  M. V. F. Pereira,et al.  A New Benders Decomposition Approach to Solve Power Transmission Network Design Problems , 2001, IEEE Power Engineering Review.

[25]  Baoding Liu,et al.  Uncertain Programming , 1999 .

[26]  Ruben Romero,et al.  Parallel simulated annealing applied to long term transmission network expansion planning , 1997 .

[27]  Hyde M. Merrill,et al.  Risk and uncertainty in power system planning , 1991 .