A Solar Energy System Design for Green Hydrogen Production in South-Western Nigeria, Lagos State, Using HOMER & ASPEN

Solar system design for green hydrogen production has become the most prominent renewable energy research area, and this has also actively fueled the desire to achieve net-zero emissions. Hydrogen is a promising energy carrier because it possesses more energy capacity than fossil fuels and the abundant nature of renewable energy systems can be utilized for green hydrogen production. However, the design of an optimized electrical energy system required for hydrogen production is crucial. Solar energy is indeed beneficial for green hydrogen production and this research designed, discussed, and provided high-level research on HOMER design for green hydrogen production and deployed the energy requirement with ASPEN Plus to optimize the energy system, while also incorporating fuzzy logic and PID control approaches. In addition, a promising technology with a high potential for renewable hydrogen energy is the proton exchange membrane (PEM) electrolyzer. Since its cathode (hydrogen electrode) may be operated over a wide range of pressure, a control process must be added to the system in order for it to work dynamically efficiently. This system can be characterized as an analogous circuit that consists of a resistor, capacitor, and reversible voltage. As a result, this research work also explores the Fuzzy-PID control of the PEM electrolysis system. Both the PID and Fuzzy Logic control systems were simulated using the control simulation program Matlab R2018a, which makes use of Matlab script files and the Simulink environment. Based on the circuit diagram, a transfer function that represents the mathematical model of the plant was created, and the PEM electrolysis control system is determined to be highly significant and applicable to the two control systems. The PI controller, however, has a 30.8% overshoot deficit, but when the fuzzy control system is compared to the PID controller, it is found that the fuzzy control system achieves stability more quickly, demonstrating its benefit over PID.

Systematic Biological Upgrade of a Urea Fertilizer Effluent Treatment Plant Using GPS

The use of modeling and simulation has developed into a critical tool for the sustainable management of wastewater, especially when it comes to replicating the complex biochemical procedures required for fertilizer effluent treatment, which calls for a significant amount of wastewater-related data. The biological improvement of a urea fertilizer effluent via GPS* simulation was carried out in this work using a methodical process. Using established analytical techniques, temperature, total suspended solids (TSS), biochemical oxygen demand (BOD), total phosphorus (T/), chemical oxygen demand (COD), total nitrogen (TN), total nitrate (NO3), electric conductivity (EC), turbidity, residual chlorine, urea, NH3, and heavy metals (Cu, Cd, Cr, Pb, Ni, and Fe) were assessed. The research revealed that the measured values from the fertilizer factory outfall effluent had high concentrations of all the physicochemical water quality indicators, with the exception of TSS, PO4-, SO4-, and NO3-. These concentrations are higher compared to the authorized limits or suggested values by the Federal Environmental Protection Agency (FEPA). To improve the therapy biologically, however, a modeling and simulation program (GPS-X, version 8.0) was used with the physicochemical information gathered from the studied sample. The results of the treated water simulation showed that the concentrations of BOD5 and COD had been significantly reduced by 35% and 44%, respectively. Additionally, it was discovered that total phosphorus (TP), nitrate (N), and total nitrogen (TN) were all within the permitted FEPA limit. The results revealed good treatment performance of the wastewater with increasing concentration of acetic acid and sodium hydroxide. Hence, the results of this research work identify the need for proper treatment of fertilizer industry effluents prior to their release into the environment.