|
|
|
| Interior-Exterior Point Method for Optimal Power Flow |
| Zhao Hongshan, Chen Bo |
| North China Electric Power University Baoding 071003 China |
|
|
|
|
Abstract Interior point method (IPM) has good global convergence, but the rate of convergence would become slow when the trajectory obtains into the neighborhood of the solution at ill-condition. Exterior point method (EPM) can converge to the optimal solution with 1.5-Q-superlinear rate under the standard second-order optimality conditions. The paper proposes an interior-exterior point method (IEPM) for optimal power flow (OPF). The IEPM OPF combines the advantages of IPM and EPM, and has fast global convergence and superlinear local convergence. When the convergence rate of IPM OPF drops to a certain level, the IEPM OPF switches to EPM. The IEPM OPF is numerically implemented and tested on several IEEE test systems and an actual 685 buses system. Numerical simulating results show that the algorithm of IEMP OPF has both the fast global convergence and the fast local convergence.
|
|
Received: 23 November 2009
Published: 04 March 2014
|
|
|
|
|
|
[1] Olofsson M, Andersson G, Soder L. Linear programming based optimal power flow using second ordersensitivities[J]. IEEE Transactions on Power Systems, 1995, 10(3): 1691-1697.
[2] Momoh J A, El Hawary M E, Adapa R, et al. A review of selected optimal power flow literature to 1993 Part I: Nonlinear and quadratic programming approach- hes[C]. IEEE Transactions on Power Systems, 1999, 14(1): 96-104.
[3] Amerongen R A. Optimal power flow solved with sequential reduced quadratic programming[J]. Electrical Engineering, 1988, 71(3): 213-219.
[4] Sousa A A, Torres G L. Globally convergent optimal power flow by trust-region interior-point methods[C]. Power Technology, 2007: 1386-1391.
[5] Wei H, Sasaki H, Kubokawa J, et al. Interior point nonlinear programming for optimal power flow problems with a novel data structure[J]. IEEE Transactions on Power Systems, 1998, 13(3): 870- 877.
[6] Torres G L, Quintana V H. An interior point method for nonlinear optimal power flow using voltage rectangular coordinates[J]. IEEE Transations on Power Systems, 1998, 13(4): 1211-1218.
[7] Momoh J A, El Hawary M E, Adapa R. A review of selected optimal power flow literature to 1993 Newton, linear programming and interior point methods[J]. IEEE Transactions on Power Systems, 1999, 14(1): 105-111.
[8] Wei Yan, Juan Yu, Yu D, et al. A new optimal reactive power flow model in rectangular form and its solution by predictor corrector primal dual interior point method[J]. IEEE Transactions on Power Systems, 2006, 21(1): 61-67.
[9] 史继莉, 邱晓燕. 人工智能在最优潮流中的应用综述[J]. 继电器, 2005, 33(16): 85-89.
[10] Jabr R A, Coonick A H, Cory B J. A primal-dual interior point method for optimal power flow dispatching[J]. IEEE Transactions on Power Systems, 2002, 17(3): 654-662.
[11] Yan X, Quintana V H. An efficient predictor- corrector interior point algorithm for security- constrained economic dispatch[J]. IEEE Transactions on Power Systems, 1997, 12(2): 803-810.
[12] Momoh J A, Koessler R J, Bond M S, et al. Challenges to optimal power flow[J]. IEEE Transactions on Power Systems, 1997, 12(1): 444- 455.
[13] Griva I, Polyak R A. Primal-dual nonlinear rescaling method with dynamic scaling parameter update[J]. Mathematical Programming, 2006, 106(2): 237-259.
[14] Griva I, Polyak R A. 1.5-Q-superlinear convergence of an exterior point method for constrained optimization [J]. Journal of Global Optimization, 2008, 40(4): 679-695. |
|
|
|
2010, Vol. 25 
