To remove pollutants from industrial waste, magnetic separation by use of magnetic reduced graphene oxide (rGO) is a possible route, due to the high specific surface area of rGO. Reduced graphene oxide decorated with nickel, cobalt and cobalt ferrite nanoparticles was synthesized by means of modified coprecipitation methods. Nitrogen-doped reduced graphene was prepared by a thermal doping method. The resulting composites were characterized with scanning electron microscope, transmission electron microscope (TEM), powder X-ray diffraction (XRD), thermal analysis and Raman spectroscopy. Samples were magnetically characterized using vibrating sample magnetometer to determine the magnetic properties. All the prepared sampled were found to have weak ferromagnetic properties. The particle size distribution of the nanoparticles was determined using the TEM images and Image J software. The average particle size for the Co-rGO was 1.89 nm, 35.12 nm for Ni-rGO and 32.15 nm for CoFe-rGO. The Co-rGO was used as proof of principle to remove Cr(VI) ions from solution. The Co-rGO was recycled five times before it was deemed unusable.
Stand-alone DC microgrids have multiple distributed generation (DG) sources that meet the required demand (load) by using droop control to achieve load (current) sharing between the DGs. The use of droop control leads to a voltage drop at the DC bus. This paper presents a distributed secondary control scheme to simultaneously ensure current sharing between the DGs and regulate the DC bus voltage. The proposed control scheme eliminates the voltage deviation and ensures balanced current sharing by combining the voltage and current errors in the designed secondary control loop. A new flight-based artificial bee colony optimization algorithm is proposed. This selects the parameters of the distributed secondary control scheme to achieve the objectives of the proposed controller. A state–space model of the DC microgrid is developed by using eigenvalue observation to test the impacts of the proposed optimized distributed secondary controller on the stability of the DC microgrid system. A real-time test system is developed in MATLAB/Simulink and used in a Speedgoat real-time simulator to verify the performance of the proposed control scheme for real-world applications. The results show the robustness of the proposed distributed secondary control scheme in achieving balance current sharing and voltage regulation in the DC microgrid with minimal oscillations and fast response time.
There is a growing focus on exploring direct current (DC) microgrids in traditional power grids. A key challenge in operating these microgrids is ensuring proper current distribution among converters. While conventional droop control has been used to address this issue, it requires compensating for voltage deviations in the DC bus. This paper introduces an innovative distributed secondary control approach that effectively addresses both voltage restoration and current sharing challenges within a standalone DC microgrid. The distributed secondary control proposed in this study is integrated into the microgrid’s cyber layer, enabling information sharing between controllers. This distributed approach ensures reliability, even in the event of partial communication connection failures. The controller employs a fuzzy logic control approach to dynamically determine the parameters of the secondary control, resulting in an enhanced control response. Additionally, the proposed approach can handle constant power and resistive loads without specific requirements. Employing the Lyapunov method, we have derived adequate stability conditions for the proposed controller. The performance of the controller has been assessed using MATLAB/Simulink® models and validated with real-time experimental testing performed with a SpeedgoatTM real-time machine, considering five different test cases. The results indicated that the proposed control system is robust in achieving its control objectives within a DC microgrid, exhibiting fast response and minimal oscillations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.