Data Clustering-Driven Fuzzy Inference System-Based Optimal Power Flow Analysis in the Electric Networks Integrating the Wind Energy

The development of smart grids has led to an increased focus of the transmission and distribution network operators on the Optimal Power Flow (OPF) problem. The solutions identified for an OPF problem are vital to ensure the real-time optimal control and operation of electric networks and can help enhance their efficiency. In this context, the paper proposed an original solution to the OPF problem represented by the optimal voltage control from the electric networks integrating wind farms. Based on a fuzzy inference system (FIS), where the fuzzification process has been improved through the fuzzy K-means clustering, two approaches have been developed, representing novel tools for the OPF analysis. The FIS-based first approach considers the load requested at the PQ-type buses and the powers injected by the wind farms as the fuzzy input variables. Based on the fuzzy inference rules, the FIS determines the suitable tap positions for the power transformers to lead at the minimum active power losses. The second approach (I-FIS), representing an improved variant of FIS, calculates the steady-state regime to determine the power losses based on the suitable tap positions for the power transformers determined with FIS. A real 10-bus network integrating two wind farms has been used to test the two proposed approaches, considering comprehensive characteristic three-day tests to thoroughly highlight the performance under different injection active power profiles of the wind farms. The results obtained have been compared with those of the best methods in the constrained nonlinear mathematical programming used in the OPF analysis, sequential quadratic programming (SQP). The errors calculated throughout the analysis interval between the SQP-based approach, considered as the reference, and the FIS and I-FIS-based approaches were 5.72% and 2.41% for the first day, 1.07% and 1.19% for the second day, and 1.61% and 1.33% for the third day. The impact of the OPF by calculating the efficiency of the electric network revealed the average percentage errors between 0.04% and 0.06% for the FIS-based approach and 0.01% for the I-FIS-based approach.