The primary goal of enhancing automatic generation control (AGC) in interconnected multi-area power systems is to ensure high-quality power generation and reliable distribution during emergencies. These systems still struggle with consistent stability and effective response under dynamic load conditions despite technological advancements. This research introduces a secondary controller designed for load frequency control (LFC) to maintain stability during unexpected load changes by optimally tuning the parameters of a Proportional–Integral–Derivative (PID) controller using pelican optimization algorithm (POA). An interconnected power system for ith multi-area is modeled in this study; meanwhile, for determining the optimal PID gain settings, a four-area interconnected power system is developed consisting of thermal, reheat thermal, hydroelectric, and gas turbine units based on the ith area model. A sensitivity analysis was conducted to validate the proposed controller’s robustness under different load conditions (1%, 2%, and 10% step load perturbation) and adjusting nominal parameters (R, T_p, and T_ij) within a range of ±25% and ±50%. The performance response indicates that the POA-optimized PID controller achieves superior performance in frequency stabilization and oscillation reduction, with the lowest integral time absolute error (ITAE) value showing improvements of 7.01%, 7.31%, 45.97%, and 50.57% over gray wolf optimization (GWO), Moth Flame Optimization Algorithm (MFOA), Particle Swarm Optimization (PSO), and Harris Hawks Optimization (HHO), respectively.

Wind farm (WF) grid codes require wind generators to have low voltage ride through (LVRT) capability, which means that normal power production should be resumed quickly once the nominal grid voltage has been recovered. However, WFs with fixed-speed wind turbines with squirrel cage induction generators (FSWT-SCIGs) have failed to fulfill the LVRT requirement, which has a significant impact on power system stability. On the other hand, variable-speed wind turbines with doubly fed induction generators (VSWT-DFIGs) have sufficient LVRT augmentation capability and can control the active and reactive power delivered to the grid. However, the DFIG is more expensive than the SCIG due to its AC/DC/AC converter. Therefore, the combined use of SCIGs and DFIGs in a WF could be an effective solution. The design of the rotor-side converter (RSC) controller is crucial because the RSC controller contributes to the system stability. The cascaded control strategy based on four conventional PI controllers is widely used to control the RSC of the DFIG, which can inject only a small amount of reactive power during fault conditions. Therefore, the conventional strategy can stabilize the lower rating of the SCIG. In the present paper, a new control strategy based on fuzzy logic is proposed in the RSC controller of the DFIG in order to enhance the LVRT capability of the SCIG in a WF. The proposed fuzzy logic controller (FLC) is used to control the reactive power delivered to the grid during fault conditions. Moreover, reactive power injection can be increased in the proposed control strategy. Extensive simulations executed in the PSCAD/EMTDC environment for both the proposed and conventional PI controllers of the RSC of the DFIG reveal that the proposed control strategy can stabilize the higher rating of the SCIG.

Since rising worldwide energy consumption is anticipated with increasing rapid industrialization and urbanization, green energy sources have become the ineluctable choice among energy engineers, power engineers, and researchers for carbon-free and sustainable electric power generation. By integrating several energy sources, a hybrid renewable and sustainable power supply system (HRSPSS) has been created to solve the global warming problem. HRSPSS aims to develop contemporary electricity grids that benefit society, the environment, and the economy. However, there is a need for thorough assessment of these complex HRSPSSs for making the most use of renewable energy potential and carefully crafting suitable solutions. This paper provides a thorough investigation of the most effective methods for sizing, optimizing, controlling, and managing energy, as well as how to combine different renewable energy sources to create a hybrid sustainable power supply system. Information on several software simulation tools and optimization methods that have been used to support HRSPSS development, research, and planning is presented in this study. Additionally, this study covers energy management and control strategies that have been used to ensure efficient and optimal operation of HRSPSS. Furthermore, this article presents an extensive comparison among various strategies utilized in each area (sizing, optimizing, controlling, and managing energy) to provide conclusive remarks on the suitable strategies for respective applications. The outcome of this study will help various stakeholders in the energy sector to make appropriate decisions during the design, development, and implementation phases of a hybrid sustainable power supply system.

This paper presents a new intelligent control strategy to augment the low-voltage ride-through (LVRT) potential of photovoltaic (PV) plants, and the transient stability of a complete grid system. Modern grid codes demand that a PV plant should be connected to the main power system during network disturbance, providing voltage support. Therefore, in this paper, a novel fuzzy logic controller (FLC) using the controlled cascaded strategy is proposed for the grid side converter (GSC) of a PV plant to guarantee voltage recovery. The proposed FLC offers variable gains based upon the system requirements, which can inject a useful amount of reactive power after a severe network disturbance. Therefore, the terminal voltage dip will be low, restoring its pre-fault value and resuming its operation quickly. To make it realistic, the PV system is linked to the well-known IEEE nine bus system. Comparative analysis is shown—using power system computer-aided design/electromagnetic transients including DC (PSCAD/EMTDC) software—between the conventional proportional–integral (PI) controller-based cascaded strategy and the proposed control strategy to authenticate the usefulness of the proposed strategy. The comparative simulation results indicate that the transient stability and the LVRT capability of a grid-tied PV system can be augmented against severe fault using the proposed FLC-based cascaded GSC controller.

According to the grid code specifications, low voltage ride-through (LVRT) is one of the key factors for grid-tied wind farms (WFs). Since fixed-speed wind turbines with squirrel cage induction generators (FSWT-SCIGs) require an adequate quantity of reactive power throughout the transient period, conventional WF consisting of SCIG do not typically have LVRT capabilities that may cause instability in the power system. However, variable-speed wind turbines with doubly fed induction generators (VSWT-DFIGs) have an adequate amount of LVRT enhancement competency, and the active and reactive power transmitted to the grid can also be controlled. Moreover, DFIG is quite expensive because of its partial rating (AC/DC/AC) converter than SCIG. Accordingly, combined installation of both WFs could be an effective solution. Hence, this paper illustrated a new rotor-side converter (RSC) control scheme, which played a significant role in ensuring the LVRT aptitude for a wide range of hybrid WF consisting of both FSWT-SCIGs and VSWT-DFIGs. What is more, the proposed RSC controller of DFIG was configured to deliver an ample quantity of reactive power to the SCIG during the fault state to make the overall system stable. Simulation analyses were performed for both proposed and traditional controllers of RSC of the DFIG in the PSCAD/EMTDC environment to observe the proposed controller response. Overall, the presented control scheme could guarantee the LVRT aptitude of large-scale SCIG.

The growing popularity of electric vehicles on a worldwide scale leads to further research to monitor their performance. The use of Internet of Things (IoT) technology will make it easier to integrate the automated real-time monitoring system with the current electric vehicle technology. The great majority of electric vehicles use rechargeable lithium-ion batteries. Use of lithium-ion batteries creates an overcharging situation in the battery, which significantly decreases battery life. It also increases the possibility of disastrous safety risks due to fire. This paper develops an IoT-based battery management system to minimize hazardous situations. The battery monitoring system (BMS) notifies the user about the condition of the battery in real time.