TAILIEUCHUNG - Iterative learning control of power flow calculation

In this paper convergence of the algorithm is global, and gives control of the convergence conditions and rigorous theoretical proof. | Send Orders for Reprints to reprints@ The Open Electrical Electronic Engineering Journal 2015 9 225-230 225 Open Access Iterative Learning Control of Power Flow Calculation Yinjun Zhang1 2 and Jianhuan Su2 Aeronautics and Astronautics Engineering Institute Air Force Engineering University Xi an 710038 Shanxi Province China 2School of Physics and Electrical Engineering Hechi University Yizhou GuangXi 546300 China Abstract The paper analyzes the flow calculation of power system using iterative learning algorithm to calculation the power flow compare with traditional improving Newton etc. algorithm Iterative learning algorithm has fast convergence can also be to achieve a high precision tracking. In this paper convergence of the algorithm is global and gives control of the convergence conditions and rigorous theoretical proof. Keywords Flow calculation iterative learning control power system. 1. INTRODUCTION The power system flow calculation is a basic power calculation for researching power system steady state. Its task is ensure the operational status of the whole system according to the operation conditions and network structure such as the voltage on each bus amplitude and phase power distribution and power loss etc. in the network. The results of power flow calculation are the basis for computation and fault analysis of power system stability 1 . Nearly 20 years the study power flow algorithm is still very active but most research revolves around improving the Newton method and the P-Q decomposition method performed. In addition with the development of artificial intelligence theory genetic algorithms artificial neural networks fuzzy algorithm is introduced gradually flow calculation 24 . However so far these new models and algorithms cannot replace Newton s method and P-Q decomposition method 5 6 position. Due to the size of the system 7 continues to expand the power of computing speed increasing demands parallel computing technology computer .

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