© The Institution of Engineering and Technology
Three measures, namely, the adaptive barrier update strategy, the filter-line-search method and the feasibility restore phase, are simultaneously introduced in the conventional primal–dual interior point method (IPM) framework to enhance the robustness of existing optimal power flow algorithms when applied to systems with considerable number of flexible AC transmission system (FACTS) devices. First, an adaptive barrier parameter strategy is employed to update the barrier parameter after the current μ-barrier problem solved to certain accuracy. Second, a filter-line-search procedure is introduced to generate the next iterate. Third, the algorithm initiates a feasibility restore phase as a remedy in case of getting stuck at a non-optimal point. Comparative case studies with previous algorithms on both standard test systems and large-scale real-world systems demonstrate the novel algorithm outperforms conventional IPMs in robustness and efficiency.
References
-
-
1)
-
13. Bertsekas, D.P.: ‘Nonlinear programming’ (Athena Scientific, Belmont, 1999).
-
2)
-
14. Bertsekas, D.P.: ‘Projected Newton methods for optimization problems with simple constraints’, SIAM J. Control Optim., 1982, 20, pp. 221–246 (doi: 10.1137/0320018).
-
3)
-
17. Gondzio, J.: ‘Multiple centrality corrections in a primal–dual method for linear programming’, Comput. Optim. Appl., 1996, 6, pp. 137–156 (doi: 10.1007/BF00249643).
-
4)
-
10. Wächter, A., Biegler, L.T.: ‘On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming’, Math. Program., 2006, 106, pp. 25–57 (doi: 10.1007/s10107-004-0559-y).
-
5)
-
7. Duan, C., Fang, W., Jiang, L., Niu, S.: ‘FACTS devices allocation via sparse optimization’, IEEE Trans. Power Syst., 2015, pp, (99), pp. 1–12 (doi: 10.1109/TPWRS.2015.2433891).
-
6)
-
3. Granville, S.: ‘Optimal reactive dispatch through interior point methods’, IEEE Trans. Power Syst., 1994, 9, pp. 136–146 (doi: 10.1109/59.317548).
-
7)
-
9. Wächter, A., Biegler, L.T.: ‘Line search filter methods for nonlinear programming: motivation and global convergence’, SIAM J. Optim., 2005, 16, pp. 1–31 (doi: 10.1137/S1052623403426556).
-
8)
-
5. Torres, G.L., Quintana, V.H.: ‘On a nonlinear multiple-centrality-corrections interior-point method for optimal power flow’, IEEE Trans. Power Syst., 2001, 16, pp. 222–228 (doi: 10.1109/59.918290).
-
9)
-
16. Mehrotra, S.: ‘On the implementation of a primal–dual interior point method’, SIAM J. Optim., 1992, 2, pp. 575–601 (doi: 10.1137/0802028).
-
10)
-
6. Capitanescu, F., Wehenkel, L.: ‘Experiments with the interior-point method for solving large scale optimal power flow problems’, Electr. Power Syst. Res., 2013, 95, pp. 276–283 (doi: 10.1016/j.epsr.2012.10.001).
-
11)
-
15. Capitanescu, F., Glavic, M., Ernst, D., et al: ‘Interior-point based algorithms for the solution of optimal power flow problems’, Electr. Power Syst. Res., 2007, 77, pp. 508–517 (doi: 10.1016/j.epsr.2006.05.003).
-
12)
-
4. Wu, Y., Debs, A.S., Marsten, R.E.: ‘A direct nonlinear predictor-corrector primal–dual interior point algorithm for optimal power flows’, IEEE Trans. Power Syst., 1994, 9, pp. 876–883 (doi: 10.1109/59.317660).
-
13)
-
2. Zhifeng, Q., Deconinck, G., Belmans, R.: ‘A literature survey of optimal power flow problems in the electricity market context’. Power Systems Conf. and Exposition, 2009. PSCE ‘09, IEEE/PES, Seattle, WA, 2009, pp. 1–6.
-
14)
-
1. Zhang, X., Rehtanz, C., Pal, B.: ‘Flexible AC transmission systems: modelling and control’ (Springer, 2006).
-
15)
-
36. Zimmerman, R.D., Murillo-Sanchez, C.E., Thomas, R.J.: ‘MATPOWER: steady- state operations, planning, and analysis tools for power systems research and education’, IEEE Trans. Power Syst., 2011, 26, (1), pp. 12–19 (doi: 10.1109/TPWRS.2010.2051168).
-
16)
-
8. Nocedal, J., Wächter, A., Waltz, R.A.: ‘Adaptive barrier update strategies for nonlinear interior methods’, SIAM J. Optim., 2009, 19, pp. 1674–1693 (doi: 10.1137/060649513).
-
17)
-
12. Fletcher, R., Leyffer, S.: ‘Nonlinear programming without a penalty function’, Math. Program., 2002, 91, pp. 239–269 (doi: 10.1007/s101070100244).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2015.0623
Related content
content/journals/10.1049/iet-gtd.2015.0623
pub_keyword,iet_inspecKeyword,pub_concept
6
6