TLBO Tuned a Robust Fuzzy Control Structure for Load Frequency Control of a Hybrid Power System with Photovoltaic Source

Robustness and reliability are two of the most factors that identify the superior performance of a controller. Power system stability and control has always been and will continue to be a field that needs continuous attention from researchers due to the increase in the complexity of power systems. This is a consequence of the increase in the capacity and the high penetration of renewable energy resources. This study proposes a new Fuzzy Logic Control (FLC) design for Load Frequency Control (LFC) in power systems. The structure of this design offers a satisfactory level of reliability as well as excellent robustness performance. The proposed fuzzy design is employed as an LFC system in a hybrid dual area power system based on a photovoltaic renewable energy plant in area one and a thermal generation unit in area two. In order for achieving the best possible dynamic performance of the proposed structure, Teaching Learning Based Optimisation (TLBO) algorithm is suggested to optimally tune the scaling factor gains of the proposed fuzzy configuration, the well-known Integral Time Absolute Error (ITAE) objective function is considered for this matter. The superiority of the suggested fuzzy control design is investigated by conducting a comparative study between this design and other controllers based on different theories. Also, the robustness validation of the proposed fuzzy controller is examined against parametric uncertainties of the testbed hybrid power system. Simulation results revealed that the fuzzy Logic Controller introduced in this study is reliable, robust, superior and appropriately handled the problem of frequency variation.