Security constrained optimal power flow (SCOPF) is a key operation function for modern power systems. In this study, a new bi-level optimisation approach is proposed to solve this problem considering a comprehensive SCOPF model, including, for example, valve loading effect, multi-fuel option and prohibited operating zone constraints of thermal units as well as AC network modelling and AC security constraints. Economic dispatch is solved in the lower level of the proposed approach and using its results as the initial solution, SCOPF is solved in the upper level with high convergence rate. For the both levels, a new enhanced gravitational search algorithm is suggested as the optimisation tool. The proposed bi-level approach is tested on 9-bus, IEEE 57-bus, IEEE 118-bus, IEEE 300-bus and polish 2746-bus test systems. Obtained results from the proposed approach for the test cases are compared with the results of other SCOPF solution methods and published literature figures. These comparisons confirm the validity of the developed approach.
Summary
Transformers as 1 of the most important and expensive equipment of power network are under continuous exposure of faults. Periodic examinations for detecting and locating trivial deformation occurrences are indispensable for preventing their unexpected outage and costly, time‐consuming repair procedure. The most crucial step for fault detection is obtaining parameters of the detailed model. Acquiring parameters of the detailed model (APDM) is a nonlinear, nonconvex, and large‐scale problem that requires a powerful method to be solved. This paper proposed a novel method that gains benefit from new efficient functions of Fourier series coefficient and phase functions, an adaptive version of the PSO and fast calculation of coupled network matrices, to solve the problem. Experimental results on 2.64 and 120 kV set of transformer windings, constructed for this study, verified the precision of the proposed method for discovering the position and severity of the disk space variation fault.
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