A Novel Grey Wolf Optimizer Based Load Frequency Controller for Renewable Energy Sources Integrated Thermal Power Systems

CAN Ö., Ozturk A., EROĞLU H., Kotb H.

ELECTRIC POWER COMPONENTS AND SYSTEMS, vol.49, no.15, pp.1248-1259, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 49 Issue: 15
  • Publication Date: 2022
  • Doi Number: 10.1080/15325008.2022.2050450
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Environment Index, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Page Numbers: pp.1248-1259
  • Keywords: automatic generation control, Grey Wolf Optimization, load frequency control, PI-(1+DD) controller, renewable energy sources, thermal power system, PV system, wind energy system, heuristic techniques
  • Recep Tayyip Erdoğan University Affiliated: Yes


The frequency value should be kept constant to ensure and maintain synchronization in power systems. When the balance between generation and load is interrupted, the frequency value increases or decreases. This frequency deviation may lead to serious problems in the power system. Therefore, a design of a controller is required to keep the system frequency and tie-line power variations within specified limits, which is called automatic generation control (AGC) or load frequency control (LFC). This paper aims to determine the optimal controller parameters used in the LFC for a two-area non-reheat thermal power system integrated with various renewable energy sources (RES) such as photovoltaic (PV) and wind energy systems. The proposed controller is a PI-(1 + DD) controller which is a combination of proportional, integral, and double derivative controllers. The optimal gains of the proposed controller are determined by the Grey Wolf Optimization (GWO) algorithm. Moreover, the performance of the PI-(1 + DD) controller is tested under various scenarios such as different step load perturbations, random load changes, system parameters and RES variation. The results show that the PI-(1 + DD) controller provides an improvement of about 40% in system frequency overshoot and about 45% in settling time compared to other controllers.