A Fuzzy Rotor Resistance Updating Scheme for an IFOC Induction Motor Drive

(, )is the (, ) ij element of the inverse of the B-matrix, and Pm net( ) is the net power injection at location m. Note that mi repre- sents all () ms that are connected to i. The power flow, fi j S (, , ) ,i s de- fined as positive to avoid negative wheeling charges. e is a very small positive number used to prevent singularity. This model is the extension of the gaming model the author devel- oped earlier (3). We present a simple case study using the model. The test system is the IEEE 14-bus power flow test system (4). This system has two generators that are located at nodes one and two. Assume that generator one is owned by producer one and generator two by producer two. Linear nodal demand functions are used with ai 0( ) as the intercept of the price axis (see Table 2). Slopes of the linear demand functions are all one. The wheeling cost for each line is derived using the follow- ing formula: wh i j (, ) . =+ 10 uniform (-0.1, +0.1) where uniform() is a uniform random number generator. The solution technique for this gaming problem is similar to the one used in (3). That is, the mixed complementarity programming (MCP) technique is used. Due to the in- troduction of losses, however, the gaming problem becomes highly nonlinear (see (11)) and more difficult to solve. The successive approx- imation method is used to resolve the difficulty. The first approxima- tion starts from the gaming model incorporating the GLP method. In the successive iterations that follow, (11) is approximated using the fol- lowing CLP formula,