Grid Steady State Evaluation for Stochastic Nature of Renewables and Loads

The development of the electric power industry for the next 20-30 years provides a significant growth of generation from renewable sources, as well as improvement of the efficiency of distribution and consumer electric networks. In the structure of renewable generation, the output from wind and solar power plants generally exceeds the output from other renewable sources. The probabilistic-fuzzy nature of wind power and solar plants, as well as the stochasticity of the load power leads to random variability of voltage and power flows in the electrical networks of the system. The effect of random-indefinite variability of mode in the network may increase with the growth of power from wind and solar plants integrated into the system. In this paper we propose probabilistic fuzzy models that describe the power system state variability caused by the load and generation stochasticity. The proposed models are presented in the form of the Gauss fuzzy description with varying center and width for the membership functions of the mode parameters that determine the system state. It is shown that the proposed models allow for approximating the current and forecasting values of its parameters with a higher accuracy on the basis of simultaneous consideration of stochasticity and uncertainty in the variability of the power system state. The paper consists of introduction, which formulates the problem of modeling of the power system state, taking into account the stochasticity and uncertainty of its variability, in the form of a probabilistic fuzzy set; in the second section the procedure for the identifying the model structure of the probabilistic fuzzy set in relation to the description of the random variability of the system state caused by the load power stochasticity is proposed; in the third section an analysis of the simulation results of the power system state represented by the fuzzy description for the voltage vector and power flows in the network is provided.