No abstract

No abstract

Because of the lack of upstream grid support and low inertia, independent microgrids are very susceptible to load variations and uncertainty in the generation of renewable energy sources. Disruption of microgrid frequency stability causes severe damage to various system equipment and frequency-sensitive loads. By taking into account the effects of electric vehicles (EVs), this paper introduces an innovative control strategy with a master-slave configuration for frequency control of interconnected microgrids. In the proposed configuration, an integer-order controller serves as the master, while a merely fractional-order integrator acts as the slave controller. The master and slave controllers are concurrently optimized by the JAYA intelligent algorithm to achieve robust effectiveness. Additionally, nonlinearities in the system are implemented, such as diesel generator operating limits, signal controllers, and sending/receiving time delays. To assess the effectiveness of the proposed control strategy in a two-area microgrid, six basic scenarios are investigated: sudden load changes, perturbations at the inputs of renewable energy-based units, parametric uncertainties, time-delay effects as a nonlinear factor, complicated working conditions, and EVs impacts. Moreover, the controller’s performance on a simple closed-loop system has been carried out in order to confirm the viability of its practical implementation, and a comparison of experimental and simulation findings has also been provided. Studies demonstrate the proposed controller’s robustness as well as its fast-response capability. Besides, this controller features a simple structure that allows extra design flexibility.

This study investigates a hierarchical approach for modeling the mutual impacts of distribution network (DN) decisions and microgrids in a multi‐microgrid system under the cover of a two‐level problem. Due to the conflicting interests of decision‐makers in an active DN, the optimization problem has a hierarchical structure, with distribution companies (Discos) at the top attempting to maximize profits and microgrids at the bottom attempting to reduce costs. This study examines the relationship between the unpredictability of renewable energy sources and power demand. In this mechanism, the influence of the demand response program (DRP) is also considered an important aspect of intelligent systems. The two‐level nonlinear optimization problem has been transformed to a one‐level linear problem using dual theory and KKT conditions. According to the findings of the studies, even though cost reduction is the sole objective of scheduling in centralized mode, applying DRP to the system results in a 16% reduction in overall costs for the two‐level scheduling method, and a 22% reduction in daily costs when compared to two‐level scheduling without DRP.

No abstract

Modern electrical power system design will increase renewable energy sources (RES) dominance. Rotating masses, the main source of inertia in power systems, have been greatly decreased in renewable energy producing systems. Thus, load–frequency equilibrium is an important indicator of these systems' performance and safety. This work introduces a fractional‐order (FO) operator‐based cascade control structure for islanded microgrid (μG) load‐frequency control (LFC). The structure utilizes a tilt–FO derivative with filter (TFODn) in the first level to reduce noise. The second level implements the proportional integral (PI) controller's FO form (FOPI), making it a tilt–FO derivative with a filter cascaded to the FOPI controller (TOFDn‐FOPI). The optimal controller parameters for quick dynamic responses with low frequency fluctuation are determined using a unique cost function and prairie dog optimization (PDO) algorithm. The LFC control loops have frequency deviation‐based responsive loads (RL). Control signal delays, RES output changes, parameter uncertainties, and cyber vandalism are examined. Laboratory‐scale tests also assessed the controller's practicality. The proposed controller outperforms standard and FO type proportional integral derivative (PID) and PD‐PI controllers. The TFODn‐FOPI controller is suitable for complicated closed‐loop systems like islanded μGs due to its faster error clearing, reduced RL capacity, and superior time and frequency domain indicators.

No abstract

No abstract