The generation of energy by conventional systems leads to several environmental issues. Fuel Cell (FC), being a new renewable energy source, has emerged as one of the promising alternatives to obtain clean and efficient energy generation. This paper highlights the power quality enhancement of the grid connected FC through a boost converter and 25 level Cascaded H-Bridge (CHB) Multi-Level Inverter (MLI) using the classical PID controller. To drive the MLI connected to the grid for governing the Point of Common Coupling (PCC) voltage between the FC and the grid, two PID controllers have been utilized. The conventional evolutionary techniques such as Particle Swarm Optimization (PSO) and Squirrel Search Algorithm (SSA) are implemented to tune the PID controllers for dynamic operations. To further enhance the convergence speed of computation and precision of the classical techniques used, an Improved Squirrel Search Algorithm (ISSA) has been proposed in this work. The grid connected power network considered for study here is designed using MATLAB/Simulink environment. Moreover, the system is led to various rigorous voltage sag and swell conditions to test the effectiveness of the proposed controller. A detailed comparison between the conventional PID, PSO, SSA, and proposed ISSA techniques in voltage profile improvement, power quality enhancement, and reduced execution time has been featured. The results obtained highlight the proposed technique’s superiority over the classical methods in terms of improved dynamic voltage response, enhanced power quality, and reduced harmonics. The power quality indices are found out using Total Harmonic Distortion (THD) analysis. The values found out are well within the IEEE-547 indices for the proposed controller, thus justifying its real-time implementation.

This article introduces a method for managing energy in an isolated DC microgrid by utilizing a battery and a supercapacitor. The approach employs an artificial rabbits optimized neural network (ARONN) control system. The principal goal of this power management method is to meet the power demand while ensuring balanced production and consumption, along with maintaining a stable DC bus voltage. One notable advantage of this method is that its losses are accounted for during the design of power modulators, achieved through scheming the actual power accessible on the shared common bus. The isolated DC microgrid regulator combines the incremental conductance maximum power point tracking (MPPT) technique for maximizing power extraction from PV sources and ARONN control for managing the power modulator in the storage scheme. By effectively controlling the flow of power on the shared DC bus, the steadyness of the bus DC voltage is maintained with minimal error from the reference voltage. This approach also minimizes battery stress by directing low-frequency current control for the battery and higher-frequency current control for the supercapacitor. The efficiency of the suggested energy management and regulator strategies is confirmed by the outcomes obtained from the simulation.

Microgrids have emerged as a feasible solution for consumers, comprising Distributed Energy Resources (DERs) and local loads within a smaller geographical area. They are capable of operating either autonomously or in coordination with the main power grid. As compared to Alternating Current (AC) microgrid, Direct Current (DC) microgrid helps with grid modernisation, which enhances the integration of Distributed and Renewable energy sources, which promotes energy efficiency and reduces losses. The integration of energy storage systems (ESS) into microgrids has garnered significant attention due to the capability of ESS to store energy during periods of low demand and then provide it during periods of high demand. This research includes planning, operation, control, and protection of the DC microgrid. At the beginning of the chapter, a quick explanation of DC microgrids and their advantages over AC microgrids is provided, along with a thorough evaluation of the various concerns, control techniques, challenges, solutions, applications, and overall management prospects associated with this integration. Additionally, this study provides an analysis of future trends and real-time applications, which significantly contributes to the development of a cost-effective and durable energy storage system architecture with an extended lifespan for renewable microgrids. Therefore, providing a summary of the anticipated findings of this scholarly paper contributes to the advancement of a techno-economic and efficient integration of ESS with a prolonged lifespan for the use of green microgrids.

Integration of photovoltaic (PV) systems increases demand for DC microgrids (DCMGs). Stability of PV-based DCMG is enhanced by integrating battery storage into it. Addition of another energy storage element, i.e., supercapacitor (SC) further ameliorates battery’s longevity and dynamic stability of DC microgrid. Combination of battery and SC is known hybrid energy storage system (HESS). Control and power sharing of battery and SC play a significant role in HESS operation. Conventional constant frequency low pass filter-based HESS control can share dynamic power between battery and SC. However, the constant and slowdynamics of HESS control affect DC bus regulation and battery’s state-of-charge (SoC). To improve dynamic performance of HESS, this paper proposes, a SoC-based variable frequency low pass filter-based energy management strategy (EMS). Proposed EMS controls power splitting between battery and SC and reduces battery’s sluggishness under necessary conditions. Proposed strategy enhances dynamic DC bus stability, battery life and utilizes SC effectively. Proposed EMS is validated with Matlab simulation and real-time digital simulation.

This paper presents a technique of harmonic minimization from output voltage waveform of a reduced switch Multilevel Inverter (MLI) through an efficient bio inspired metaheuristic algorithm called Black widow optimization (BWO). The proposed reduced switch 13- level MLI scheme uses a single Photovoltaic (PV) source which can be suitable for grid integration. The proposed BWO algorithm minimizes the Total Harmonic Distortion (THD) of output voltage with low operational time compared to other existing nature based algorithms considering large searching area. The weighted THD (WTHD) of the output voltage is also minimized in order to reduce the effect of lower order harmonics from the output voltage in a greater extent. The convergence rate and level of accuracy of BWO algorithm is compared with two different bio inspired algorithms for justification. The MLI operation is carried out with fundamental frequency, minimizing the switching stress while lowering the power loss compared to PWM or Sinusoidal PWM switching schemes. A single PV panel with multi winding flyback converter is used for medium voltage application through reduced switch MLI, serving the purpose of both isolation and reduction of energy sources. Simulation and experimental analysis are carried out with online control technique using a three phase 13-level reduced MLI to validate the proposed concept on a practical system.