Load Flow Calculation by Neural Networks

신경회로적인 전력조류 계산법에 대한 연구

This paper presents an algorithm to reduce the time to solve Power Equations using a Neural Net. The Neural Net is trained with samples obtained through the conventional AC Load Flow. With these samples, the Neural Net is constructed and has the function of a linear interpolation network. Given arbitrary load level, this Neural Net generates voltage magnitudes and angles which are linear interpolation of real and reactive powers. Obtained voltage magnitudes and angles are substituted to Power Equations, Real and reactive powers are found. Thus, a new sample is generated. This new experience modifies weight matrix. Continuing to modify the weight matrix, the correct solution is achieved. comparing this method with AC Load flow, this method is faster. If we consider parallel processing, this method is far faster than conventional ones.