Regular Article

Enhancing decentralized frequency regulation approach in mixed source of generation diversified with wind and PV integration deploying artificial gorilla troops algorithm

¹ Department of Electrical and Electronics Engineering, SR University, Warangal, Telangana 506371, India
² Centre for Emerging Energy Technologies, SR University, Warangal, Telangana 506371, India

^* Corresponding author: b.vedik@gmail.com

Received: 29 February 2024
Accepted: 18 June 2024

Abstract

Nowadays, the penetration of renewable energy sources, mainly wind and solar photovoltaic systems, into the existing power systems, destabilizes the grid, especially in the aspect of frequency regulation. AGC is one of the most important tasks in this mixed-generation environment to maintain the balance between the generated and consumed electricity, thus keeping the system frequency at an acceptable level. Therefore, AGC needs to be optimized for the noisy and volatile output of RESs. AGTA is a recent optimization method developed based on the social foraging behavior of gorillas, being a sophisticated way of exploration and exploitation. Therefore, the method is implemented in AGC. By mimicking the social behaviour and foraging strategy, the group gives rise to a new technique for enhancing the efficiency and response of the AGC system in light of wind and PV energy generation variation. A two-area power system model has been formulated characterized by the existence of wind and PV generation in addition to the conventional sources of the power system. This model is meant to simulate diverse situations to give an idea as regards the capability of the new algorithm to enhance grid stability and adaptability. The simulated results show that the proposed AGTA significantly surpasses other conventional optimization methods for AGC and results in an effective frequency control strategy. it confirms the potential of the AGTA from a new perspective in providing a feasible option for decentralized frequency regulation in a multi-generation landscape.