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Parameter Identification Of Hydro Generation System With Fluid Transients Based On Improved Genetic Algorithm, Lin Gao
Lin Gao
More accurate models are adopted for dynamic stability analysis of hydro generation systems but the parameters of these models are often estimated roughly. Inaccurate parameters may decrease the analysis accuracy improved by using an accurate model. An improved genetic algorithm is proposed in this paper to estimate the parameters of a hydro generation system model which contains a series of basic differential equations to represent the flow transients more accurately. The numerical and experimental results show good accordance between the actual systems and the identification results.
A New Framework For Power System Identification Based On An Improved Genetic Algorithm, Lin Gao
A New Framework For Power System Identification Based On An Improved Genetic Algorithm, Lin Gao
Lin Gao
Accuracy parameters of power system model are of great importance in stability and security evaluation or simulation. Some of the conventional methods may have inadequate adaptability or effectiveness for identification of different power systems. A general framework for power system identification is proposed based on an improved genetic algorithm with a logarithmic fitness function and an adaptive searching space. It can be used for most power system models (linear or nonlinear) and can readily be performed on different models just by rebuilt corresponding map lists between the parameters and the coefficients of the general model. The numerical experiment and practical …