Micro Hydro Power Plants are a type of power production that uses the force of river flows or waterfalls to generate electricity. The generator generates current waves and harmonic voltage, which are distorted wave disturbances that cause fundamental frequency multiplication. The major goal of this work is to design a reliable, efficient, and innovative harmonic mitigation approach for a stand-alone micro hydroelectric system that is coordinated with a photovoltaic renewable energy system utilising an active power filter. We may pick the active filter highest harmonic to be suppressed using the magnitude information supplied for each harmonic component. A hybrid filtering approach to remove harmonics and a novel MOGA optimization technique are part of the suggested harmonics reduction solution. The goal of this article is to determine the optimum filter for decreasing harmonics in an induction generator. As the harmonic damper, two filters were chosen: a passive filter and an active power filter. The suggested MOGA control method is compared to GA and evaluated on simulated data. In tracking harmonic components and fundamental frequency, the suggested MOGA control system provides high convergence speed and accuracy. It's extremely adaptable, and it can predict changes in the phase angle, amplitude, and fundamental frequency of harmonic components. When compared to the Genetic Algorithm method, it performs better. Simulation results using the SIMULINK/MATLAB simulation tool are delivered to evaluate the efficacy of the suggested active filter system. The impact of harmonic currents on the magnetic flux density is investigated using the rated condition as a reference. It has been established that the time harmonic is a significant element influencing generator performance. At the same time, the impacts of harmonic currents on the generator's eddy current loss, average torque, and torque ripple are investigated, as well as the mechanism of eddy current loss fluctuation.

The goal of this article is to create an intelligent energy management system that will control the stand-alone microgrid and power flow of a grid associated that includes Battery Energy Storage System, Fuel Cell, Wind Turbine, Diesel Generator, Photovoltaic, and a Hydro Power Plant. Storage systems are required for high dependability, while control systems are required for the system's optimum and steady functioning. The control, operation, and planning of both energy demand and production are all part of energy management. By controlling unpredictable power and providing an appropriate control algorithm for the entire system, the suggested energy management strategy is designed to handle diverse variations in power demand and supply. Under the TOU Tariff, the problem is presented as a discrete time multi-objective optimization method to minimize grid imported energy costs. It also maximizes earnings from surplus RE sales to the grid at a pre-determined RE feed-in tariff. Simulations were run using SIMULINK/MATLAB to validate and evaluate the suggested energy management approach under various power demand and power supply scenarios. The simulations indicate that the proposed energy management can fulfill demand at all times utilizing unreliable renewables like wind, solar, and hydroelectric power plants, as well as hydrogen fuel cells and batteries, without affecting load supply or power quality.

Because of the growing nonlinear and complexity nature of microgrid systems for example battery energy storage systems, wind-turbine fuel cell, photovoltaic, and micro hydro power plants (BESSs/FC/WT/PV/ Micro Hydro), load-frequency management has been a difficulty. The development of a load-frequency controller based on Proportional–Integral–Derivative (PID) for an autonomous microgrid (MG) with hydro, wind, and PV RES is shown in this article. The suggested LFC goal is to retain the frequency of the micro hydro power plant under variable load situations by controlling the sharing of output power constant generator between the dummy loads and consumer. Using an adaptive fuzzy logic controller to govern nearly the generating unit`s whole operation, the suggested control technique optimally chooses PID settings for each load value. The suggested fuzzy logic-based controller regulates the plant's frequency output despite fluctuating user loads and manages energy distribution by separating the micro network into separate departures connected in priority order. The suggested frequency controller uses a centralised LFC approach centred on a combination of smart load and Battery Energy Storage System to manage the MG frequency (BESS). It regulates MG frequency by providing active power balancing for a variety of events that such systems face in real-world settings, such as energy surplus generation and energy shortage. In Simulink/MATLAB, the suggested structure is simulated. The simulation results clearly demonstrate the proposed frequency controller's ability to dump extra power when the customer load varies while maintaining a consistent supply frequency.

This article offers a clear and realistic design for an active power filter to increase reliability and power quality of the photovoltaic charging system and a high-penetration electric vehicle distribution system. The MOPSO algorithm is used as the basis for problems with optimization and filter tuning. A typical regular load curve is used to model the warped power grid over a 24-hour cycle to estimate the total harmonic distortion (THD). For structures with high penetration of electric cars, the probability of minimizing THD (for example to five percent) is explored via optimum capacity active shunt filters and shunt capacitors. To maximize general performance of the charging system, the switching systems are re-scheduled. Moreover, to increase the current control accuracy of shunt active filter, the fuzzy logic controller is utilized. The major drawback to new system is that it would have unrestricted billing for entire day to cope with voltage interruption. In MATLAB / SIMULINK, detailed machine setup and control algorithm experiments are simulated. The simulation findings confirm the efficiency and viability of projected shunt active filter to enhance voltage profile and track power performance of photovoltaic charging system.

the key goal of this article is on the design and optimum sliding mode control for Grid-Connected direct drive extraction method of ocean wave energy by Multi-Objective Particle Swarm Optimization (MOPSO). A Linear Permanent Magnet Generator simulates the ocean wave energy extraction system, driven by an Archimedes Wave Swing. Uncontrolled three-phase rectifiers, a three-level buck-boost converter and 3 level neutral point clamped inverter are planned grid integration of Wave Energy Conversion device. The technique monitors the three-level buck-boost converter service cycle linked to the PMLG output terminals and decides the optimum switching sequence of 3 level neutral point clamped inverter to enable the grid relation. Simulations using Matlab/Simulink were carried out to test working of the wave energy converter after the suggested optimal control method was applied under various operating settings. Various simulation test results indicate that the proposed optimum control system is tested in both normal and irregular ocean waves. And it has been shown that the control method of the MOPSO sliding mode is ideal for maximizing energy transfer efficiency. Better voltage management at the DC-link and for achieving greater controllability spectrum was accomplished by the proposed Duty-ratio optimal control system.