### Abstract

This paper presents a new interior point nonlinear programming algorithm for optimal power flow problems (OPF) based on the perturbed KKT conditions of the primal problem. Through the concept of the centering direction, we extend this algorithm to classical power flow (PF) and approximate OPF problems. For the latter, CPU time can be reduced substantially. To efficiently handle functional inequality constraints, a reduced correction equation is derived, the size of which depends on that of equality constraints. A novel data structure is proposed which has been realized by rearranging the correction equation. Compared with the conventional data structure of Newton OPF, the number of fill-ins of the proposed scheme is roughly halved and CPU time is reduced by about 15% for large scale systems. The proposed algorithm includes four kinds of objective functions and two different data structures. Extensive numerical simulations on test systems that range in size from 14 to 1047 buses, have shown that the proposed method is very promising for large scale application due to its robustness and fast execution time.

Original language | English |
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Title of host publication | IEEE Power Industry Computer Applications Conference |

Place of Publication | Piscataway, NJ, United States |

Publisher | IEEE |

Pages | 134-141 |

Number of pages | 8 |

Publication status | Published - 1997 |

Event | Proceedings of the 1997 20th IEEE International Conference on Power Industry Computer Applications - Columbus, OH, USA Duration: 1997 May 11 → 1997 May 16 |

### Other

Other | Proceedings of the 1997 20th IEEE International Conference on Power Industry Computer Applications |
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City | Columbus, OH, USA |

Period | 97/5/11 → 97/5/16 |

### Fingerprint

### ASJC Scopus subject areas

- Hardware and Architecture
- Electrical and Electronic Engineering

### Cite this

*IEEE Power Industry Computer Applications Conference*(pp. 134-141). Piscataway, NJ, United States: IEEE.

**Interior point nonlinear programming for optimal power flow problems with a novel data structure.** / Wei, Hua; Sasaki, H.; Kubokawa, J.; Yokoyama, R.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE Power Industry Computer Applications Conference.*IEEE, Piscataway, NJ, United States, pp. 134-141, Proceedings of the 1997 20th IEEE International Conference on Power Industry Computer Applications, Columbus, OH, USA, 97/5/11.

}

TY - GEN

T1 - Interior point nonlinear programming for optimal power flow problems with a novel data structure

AU - Wei, Hua

AU - Sasaki, H.

AU - Kubokawa, J.

AU - Yokoyama, R.

PY - 1997

Y1 - 1997

N2 - This paper presents a new interior point nonlinear programming algorithm for optimal power flow problems (OPF) based on the perturbed KKT conditions of the primal problem. Through the concept of the centering direction, we extend this algorithm to classical power flow (PF) and approximate OPF problems. For the latter, CPU time can be reduced substantially. To efficiently handle functional inequality constraints, a reduced correction equation is derived, the size of which depends on that of equality constraints. A novel data structure is proposed which has been realized by rearranging the correction equation. Compared with the conventional data structure of Newton OPF, the number of fill-ins of the proposed scheme is roughly halved and CPU time is reduced by about 15% for large scale systems. The proposed algorithm includes four kinds of objective functions and two different data structures. Extensive numerical simulations on test systems that range in size from 14 to 1047 buses, have shown that the proposed method is very promising for large scale application due to its robustness and fast execution time.

AB - This paper presents a new interior point nonlinear programming algorithm for optimal power flow problems (OPF) based on the perturbed KKT conditions of the primal problem. Through the concept of the centering direction, we extend this algorithm to classical power flow (PF) and approximate OPF problems. For the latter, CPU time can be reduced substantially. To efficiently handle functional inequality constraints, a reduced correction equation is derived, the size of which depends on that of equality constraints. A novel data structure is proposed which has been realized by rearranging the correction equation. Compared with the conventional data structure of Newton OPF, the number of fill-ins of the proposed scheme is roughly halved and CPU time is reduced by about 15% for large scale systems. The proposed algorithm includes four kinds of objective functions and two different data structures. Extensive numerical simulations on test systems that range in size from 14 to 1047 buses, have shown that the proposed method is very promising for large scale application due to its robustness and fast execution time.

UR - http://www.scopus.com/inward/record.url?scp=0030655464&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030655464&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0030655464

SP - 134

EP - 141

BT - IEEE Power Industry Computer Applications Conference

PB - IEEE

CY - Piscataway, NJ, United States

ER -