%0 Journal Article 
%A Silva Quiñones, Rolando A.
%A Sánchez Sainz, Higinio
%A García Triviño, Pablo
%A Sarrias Mena, Raúl
%A Carrasco González, David
%A Fernández Ramírez, Luis Miguel
%T Optimal Control for On-Load Tap-Changers and Inverters in Photovoltaic Plants Applying Teaching Learning Based Optimization
%D 2025
%@ 2079-9292
%U http://hdl.handle.net/10498/38358
%X This research presents an optimized control strategy for the coordinated operation of parallel grid connected photovoltaic (PV) plants and an On Load Tap Changer (OLTC) transformer. The proposed framework integrates inverter-level active and reactive power dispatch with OLTC tap control through an Energy Management System (EMS) based on an improved Teaching Learning Based Optimization (TLBO) algorithm. The EMS minimizes operational costs while maintaining voltage stability and respecting electrical and mechanical constraints. Comparative analyses with Monte Carlo, fmincon, and conventional TLBO methods demonstrate that the optimized TLBO achieves up to two orders of magnitude faster convergence and higher robustness, enabling more reliable performance under variable irradiance and load conditions. Simulation and Hardware-in-the-Loop (HIL) results confirm that the coordinated OLTC inverter control significantly enhances reactive power capability and voltage regulation. The proposed optimized TLBO based EMS offers an effective and computationally efficient solution for dynamic energy management in medium scale PV systems, supporting grid reliability and maximizing renewable energy utilization.
%K Photovoltaic plants
%K On Load Tap Changer (OLTC) transformer
%K Energy Management System (EMS)
%K Teaching Learning Based Optimization (TLBO)
%~ Universidad de Cádiz