A comprehensive study on energy management, sensitivity analysis, and inertia compliance of feed-in tariff in IEEE bus systems with grid-connected renewable energy sources
Sadasiva Behera,
Sumana Das,
B.S.S. Ganesh Pardhu,
Ram Ishwar Vais,
Naladi Ram Babu,
Sanjeev Kumar Bhagat,
Mohammed Alharbi,
Wulfran Fendzi Mbasso
Affiliations
Sadasiva Behera
Department of Electrical Engineering, Meerut Institute of Engineering and Technology, Meerut, India, 250005
Sumana Das
Department of Electrical and Electronics Engineering, MLR Institute of Technology, Dundigal, Hyderabad, India, 500043
B.S.S. Ganesh Pardhu
Department of Electrical and Electronics Engineering, Aditya University, Surampalem, East Godavari, Andhra Pradesh, India, 533437
Ram Ishwar Vais
Department of Electrical Engineering, Rajkiya Engineering College Sonbhadra, UP, India
Naladi Ram Babu
Department of Electrical and Electronics Engineering, Aditya University, Surampalem, East Godavari, Andhra Pradesh, India, 533437; Corresponding author.
Sanjeev Kumar Bhagat
Department of Electrical Engineering, Sandip University, Sijoul, Madhubani, Bihar, India, 847235
Mohammed Alharbi
Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia
Wulfran Fendzi Mbasso
Laboratory of Technology and Applied Sciences, University Institute of Technology, University of Douala, PO Box: 8698, Douala, Cameroon; Corresponding author.
The need to incorporate renewable energy generators (REGs) into the electrical grid has become increasingly crucial due to the push for a more sustainable environment. This study advocates an innovative strategy for optimizing inertia-integrated generation and transmission expansion planning (GTEP) to implement feed-in tariffs (FiT). The application of the GAMS CPLEX solver to the model, which tested on an IEEE 6/IEEE 16 system, reveals that using FiT results in a 12.1 % drop in system cost ($599 million to $526 million) and a 7.91 % rise in total system inertia. Sensitivity analysis highlights the correlation between increased REG integration and FiT payment reduction at 50 % penetration. The model outperforms soft computing optimization techniques, showcasing rapid convergence and computational efficiency. The proposed model's validated superiority in rapid convergence and computational efficiency is demonstrated by comparing its results with those obtained from other soft computing optimization techniques.
