Application of Data-Driven Tuned Fuzzy Inference System for Static Equivalencing of Power Systems with High Penetration of Renewable Energy

To reduce the complexity of multiarea power systems during flow study and security assessment, equivalencing external is essential. In this paper, are modeled as adaptive loads representing tie-line flows varying with system operating conditions. The fuzzy inference tuned by hybrid genetic-simulated annealing (HGSA-FIS) proposed to predict active reactive from forecasted renewable energy (RE) generation demand. performance equivalent has been evaluated an RTS-GMLC comparing results in internal before after under RE load demand scenarios. demonstrate robustness HGSA-FIS-based Furthermore, performs close ANN-based outperforms ANFIS-based equivalent. practically implement approach, neighboring operators required exchange only forecast data demand, needs be updated upon major grid changes.