Abstract
This paper presents a new method for optimal frequency and voltage control in microgrids (MG) considering the mutual effect of line parameters on power transfer. In MGs each distributed generation (DG) has its special droop characteristics. When a load consumption change occurs in the MG, an imbalance between generation and consumption rises, thus a change occurs in the voltage and frequency of DGs according to their droop characteristics. In order to minimize oscillations of voltage and frequency, we have used optimal droop controller which is based on considering the mutual effects of transfer parameters on active and reactive powers. Since line parameters heavily affect the droop characteristics, these parameters are obtained optimally by the frog algorithm such that oscillations in voltage and frequency are minimized. In order to enhance the controlling scheme, effects of line resistance on reactive power changes and effects of line reactance on active power changes are also considered. Since enhanced droop control depends on line parameters, it cannot be implemented in large MGs; therefore, it is modeled by multi-layer perceptron neural networks. We have used the frog algorithm in order to train the perceptron network. The obtained results show satisfactory voltage and frequency control in various load level. In this paper, MGs are studied and simulated in an isolated state.
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