Feasibility study of a grid-connected PV/wind hybrid energy system for an urban dairy farm.

This study evaluates the energy efficiency of an urban dairy farm in Tlemcen, Algeria, by assessing the feasibility of a grid-connected photovoltaic (PV)/wind hybrid energy system. Using HOMER and MATLAB software, the study explores the potential for replacing the farm's existing energy systems with a hybrid system integrated into a low-voltage electrical grid. The HOMER software determined the configuration that resulted in the lowest net present cost, energy cost in kWh, greenhouse gas emission mitigation, and renewable fraction (RF).

A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems.

This research study presents the application of the FC-PCC (Fuzzy Logic Predictive Current Control) algorithm in the context of maximum power point tracking (MPPT) for a proton exchange membrane fuel cell system employing a three-level boost converter (TLBC). The proposed approach involves the integration of an intelligent fuzzy controller with a predictive current control strategy in order to improve the performance of MPP tracking. Initially, the utilization of fuzzy logic involves the utilization of data values obtained from the PEMFC.

Finite control set model predictive current control for three phase grid connected inverter with common mode voltage suppression.

This research introduces an advanced finite control set model predictive current control (FCS-MPCC) specifically tailored for three-phase grid-connected inverters, with a primary focus on the suppression of common mode voltage (CMV). CMV is known for causing a range of issues, including leakage currents, electromagnetic interference (EMI), and accelerated system degradation. The proposed control strategy employs a system model that predicts the inverter's future states, enabling the selection of optimal switching states from a finite set to achieve dual objectives: precise current control and effective CMV reduction, a meticulously designed cost function evaluates the potential switching states, balancing the accuracy of current tracking against the necessity to minimize CMV.

A reduced vector model predictive controller for a three-level neutral point clamped inverter with common-mode voltage suppression.

This paper presents a novel, state-of-the-art predictive control architecture that addresses the computational complexity and limitations of conventional predictive control methodologies while enhancing the performance efficacy of predictive control techniques applied to three-level voltage source converters (NPC inverters). This framework's main goal is to decrease the number of filtered voltage lifespan vectors in each sector, which will increase the overall efficiency of the control system and allow for common mode voltage reduction in three-level voltage source converters. Two particular tactics are described in order to accomplish this.

Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments.

This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in adapting to varying conditions, including fluctuations in pressure and temperature. Through meticulous simulations and analyses, the study explores the collaborative integration of these techniques with boost converters to enhance reliability and productivity.