AI Summary & Key Takeaways
AI InsightA significant reduction in the computational efforts is experienced.
📌 3 Key Takeaways
Abstract
The modeling and evaluation of enormous numbers of contingencies are the most challenging impediments associated with composite power system adequacy assessment, particularly for large-scale power systems. Optimal power flow (OPF) solution, as a widely common approach, is normally employed to model and analyze each individual contingency as an independent problem. However, mathematical representations associated with diverse states are slightly different in one or a few generating units, line outages, or trivial load variations. This inherent attribute brings a promising idea to speed up the contingency evaluation procedure. In this paper, postoptimal analysis (POA), as a well-recognized technique to attack a set of similar problems with minimal effort, is adopted to solve the contingency OPFs. Instead of solving all similar problems independently, POA exploits the similarity among them and accelerates the solving procedure. The proposed method here derives a base case model and obtains its respective solution. Thereafter, the solution associated with a contingency is determined by imposing differences due to unit or line outages or load variation with respect to the base case solution. The proposed approach is applicable in both sorts of analytical and simulation-based evaluation methods. The Roy Billinton test system, the IEEE reliability test system, and the IEEE 118-bus test system are used to demonstrate the performance and efficiency of the proposed approach. A significant reduction in the computational efforts is experienced.
Özet
The modeling and evaluation of enormous numbers of contingencies are the most challenging impediments associated with composite power system adequacy assessment, particularly for large-scale power systems. Optimal power flow (OPF) solution, as a widely common approach, is normally employed to model and analyze each individual contingency as an independent problem. However, mathematical representations associated with diverse states are slightly different in one or a few generating units, line outages, or trivial load variations. This inherent attribute brings a promising idea to speed up the contingency evaluation procedure. In this paper, postoptimal analysis (POA), as a well-recognized technique to attack a set of similar problems with minimal effort, is adopted to solve the contingency OPFs. Instead of solving all similar problems independently, POA exploits the similarity among them and accelerates the solving procedure. The proposed method here derives a base case model and obtains its respective solution. Thereafter, the solution associated with a contingency is determined by imposing differences due to unit or line outages or load variation with respect to the base case solution. The proposed approach is applicable in both sorts of analytical and simulation-based evaluation methods. The Roy Billinton test system, the IEEE reliability test system, and the IEEE 118-bus test system are used to demonstrate the performance and efficiency of the proposed approach. A significant reduction in the computational efforts is experienced.