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The real-time control of optimal power flow (OPF) in electric networks represents, in the last period, a challenge for the Distribution Network Operators (DNOs) and Transmission System Operators (TSOs) under the conditions of large-scale integration of renewable energy sources. The paper focused on the voltage management in the electric networks with wind farms connected, proposing a fast Successive Quadratic Programming (SQP)-based centralized control (CC) methodology of the on-load tap changers (OLTC) corresponding to the transformers from the electric substations, which can be included in the Optimal Power Flow (OPF) module of the Supervisory Control and Data Acquisition (SCADA) Master System. The SQP-CC aims to ensure an optimal voltage level inside a variation range, as narrow as possible, which leads to minimize power losses in the electric networks. Treating the OPF problem as an SQP problem and accelerating convergence using the conjugate reduced gradient method led to very few iterations and a fast computational time, recommending the implementation of the methodology for real-time work. The effectiveness of the SQP-CC was demonstrated in a test network having two voltage levels (220 and 110 kV) with two wind farms integrated, considering two scenarios, without and with wind farms connected. The optimal tap positions of the transformers led to very close voltage variations between the buses of the network, quantified through an average voltage drop between the initial and final buses by 0.004 pu compared with 0.031 pu recorded in the scenario with both wind farms injecting power into the network and without coordinated control of the OLTCs. The energy-saving was over 30% in both scenarios, 33.5% (without wind farms) and 41.27% (both wind farms injecting power in the network). These results highlighted the positive effects of the proposed SQP-CC methodology on the real-time optimal operation of the electric networks integrating wind farms.

A New SQP Methodology for Coordinated Transformer Tap Control Optimization in Electric Networks Integrating Wind Farms