Design of cascaded controller based on coyote optimizer for load frequency control in multi-area power systems with renewable sources. (April 2022)

• Record Type: Journal Article
• Authors: Abou El-Ela, Adel A.; El-Sehiemy, Ragab A.; Shaheen, Abdullah M.; Diab, Abd El-Gelil
• Is Part Of: Control engineering practice. Volume 121(2022)
• Publication Date: 2022-04
• Subjects: Cascaded controller -- Coyote algorithm -- multi-area power systems -- Load frequency control -- Photovoltaic -- Wind farm; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2021.105058
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: Electricity generation from renewable sources is on the rise. The irregular presence of these sources increases the frequency variations induced by the load variance. The penetration of renewable energy sources increases the instability of the integrated power grid due to decreased system inertia. Therefore, this paper presents an optimal controller design of proportional-derivative with filter cascaded-proportional-integral (PDn-PI) using an innovative coyote optimization algorithm (COA). The modelling of the renewable energy sources (RESs) of photovoltaic (PV) and wind farm interconnection is considered in the load frequency control (LFC). The COA is adopted and integrated with the PI/ PID/ cascaded PDn-PI controllers for the sake of optimally tuning and specifying their gains. Furthermore, the powerful performance of the proposed COA-tuned PDn-PI controller is validated, under all cases studied, not only over PI and PID controllers but also, over the previously reported approaches. To get complete picture of the string of victories gained by the proposed technique, the dynamical uncertainties of load demand and RESs are investigated in both models as third case. The simulation investigation reveals the robustness and superiority dynamic responses of the cascaded PDn-PI with COA in direct contrast to other approaches even under these uncertainties.