Modern Control Methods to Boost Microgrid’s Performance

Because the microgrid (MG) differs from traditional generators in its dynamic properties,, the greater penetration of RES-based MGs into the power system may have an impact on system stability. Therefore, it becomes crucial to evaluate the recently established dynamic stability issues and manage the power system’s operation in the context of growing microgrid penetration. This paper describes a microgrid system aided by renewable energy that uses an extreme learning machine (ELM)-based PID controller and superconducting magnetic energy system (SMES) storage. Microgrid contains two energy sources wind energy and PV solar panel. The energy generated by them is supplied to load and extra energy is stored in SMES. The PID controller is used in a feedback system to control the flow of energy. This research investigates in detail how the penetration of microgrids based on renewable energy affects the Stability and management of the multi-machine, multi-area system dynamically in a range of operational scenarios. A brief wind power prediction model based on ELM is developed. For this system, a new robust ELM-controlled PID-based power system stabilizer (PSS) is proposed. In spite of all the uncertainty, the system is guaranteed to stay stable by the ELM control technique. The ELM technique is used in order to optimize the controller’s parameters, and the resulting controller beats both regular PID and fractional order PID (FoPID) controllers in terms of performance. The controller’s ability to attenuate oscillations at low frequencies in a system with varying microgrid penetration percentages under varied operational settings and disturbances is evaluated using nonlinear time-domain simulations and many execution indicators.