Abstract
A chance constrained programming model is built to the stochastic optimal power flow problem (S-OPF) considering load probabilistic distributions. Based on the interior point method for deterministic optimal power flow (D-OPF) and probabilistic load flow method, a heuristic solution approach is proposed to solve the model. This approach makes use of the results of D-OPF and checks if the chance constraints are satisfied through obtaining distributions of the chance constrained variables. If a chance constraint is violated, new upper and lower bounds to the corresponding variable are formed based on the distribution and equivalent chance constraint of the variable. Then a new D-OPF with loads equal to their expect values is solved. The iteration terminates till all the chance constraints are satisfied. Tests on a 5-bus system and the IEEE 118-bus system show the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Pages (from-to) | 14-18+44 |
| Journal | Dianli Xitong Zidonghua/Automation of Electric Power Systems |
| Volume | 31 |
| Issue number | 16 |
| State | Published - 25 Aug 2007 |
Keywords
- Chance constrained programming
- Interior point method
- Load probabilistic distribution
- Optimal power flow
- Probabilistic power flow
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