Optimizing Energy Management in a Renewable Energy-based Microgrid With Built-in Frequency Support Features

• Published in: International Conference on Advanced Mechatronic Systems pp. 19 - 24
• Main Authors: Gbadega, Peter Anuoluwapo, Abolaji Balogun, Olufunke
• Format: Conference Proceeding
• Language: English
• Published: IEEE 26.11.2024
• Subjects: and Squid game optimizer (SGO); Frequency control; Frequency support; Games; Heuristic algorithms; Microgrids; Optimal energy management; Plug-in electric vehicles; Plug-in electric vehicles (PEVs); Power system reliability; Power system stability; Renewable energy sources; Resilience; Vehicle-to-grid; Vehicle-to-grid (V2G)
• ISSN: 2325-0690
• DOI: 10.1109/ICAMechS63130.2024.10818799

The growing adoption of Plug-in Electric Vehicles (PEVs) is expected to challenge the stability of electricity networks due to increased demand. However, Vehicle-to-Grid (V2G) technology offers a solution by enabling PEVs to provide ancillary services that enhance grid stability and reliability. This paper introduces an optimal power management system with built-in frequency support capabilities, leveraging the Squid Game Optimizer (SGO) algorithm to determine the optimal power exchange between PEV batteries and the grid throughout the day. The study further explores the potential of PEVs to provide frequency support through a frequency-PEV load droop control approach, which dynamically adjusts the PEV's power output in response to frequency deviations. After the need for frequency support is met, the SGO algorithm reschedules the PEV's operations, ensuring that all pre-set objectives and constraints are satisfied. This dual-purpose approach optimizes energy management within a renewable energy-based microgrid and contributes to maintaining grid frequency stability, thereby enhancing the resilience and efficiency of future power systems.