Erhan Kayabasi

Integration of renewable energy and waste heat resources could effectively reduce emissions and the production cost in methane production power plants. The objective of this study is to conduct a technoeconomic analysis of an Iraqi methanol production facility using a combination of energy resources of waste gas from Al-Fallujah white cement factory, solar and wind energy. It is hypothesized that the carbon dioxide present in the flue gas could be extracted using solar and wind turbine energy in a carbon capture unit in the hydrogen plant. Methanol fuel is then produced in the methanol plant from the combined sources. The amount of energy and the number of solar panels or wind turbines (WT) needed to supply this energy requirement were estimated using the Engineering Equation Solver (EES), and then the environmental impact of the methanol plant was assessed. The efficiencies of renewable energy PV, WT, methanol plants, and methanol fuel were predicted as 21%, 35%, 16.26%, and 58.72%, respectively. The electrolyzers' efficiency was 78.2% at their ideal density of 2.2 kA/m 2. With a production capacity of 34,530 million tons of methanol, the total cost to operate the plant for 30 years for each of the PV plants and WT was found to be $9.46 billion and $5.291 billion, respectively. This translates to 0.4131 $/kg methane for the PV plant and 0.2413 $/kg methane for the wind power plant. In terms of the environment, there is a daily 3,894 tons of collected CO 2 emissions and 3,306 tons of mitigation. The results show that the current facility can compete with facilities that produce clean synthetic fuel.

In this study, it is proposed to generate electrical energy by recovering the waste heat of an annealing furnace (AF) in an iron and steel plant using combined cycles such as steam Rankine cycle (SRC), organic Rankine cycle (ORC), Kalina cycle (KC) and transcritical CO₂ cycle (t-CO₂). Instead of releasing the waste heat into the atmosphere, the waste heat recovery system (WHRS) discharges the waste heat into the plant’s low-temperature oxygen line for the first time, achieving a lower temperature and pressure in the condenser than conventional systems. The waste heat of the flue gas (FG) with a temperature of 1093.15 K from the reheat furnace was evaluated using four different cycles. To maximize power generation, the SRC input temperature of the proposed system was studied parametrically. The cycles were analyzed based on thermal efficiency and net output power. The difference in SRC inlet temperature is 221.6 K for maximum power output. The proposed system currently has a thermal efficiency and total power output of 0.19 and 596.6 kW, respectively. As an environmental impact, an emission reduction potential of 23.16 tons/day was achieved. In addition, the minimum power generation cost of the proposed system is $0.1972 per kWh.

In this study, heat transfer and cost optimization of a gas-to-gas heat exchanger (recuperator) operating in the targeted temperature range has been made. Firstly, the thermophysical properties of the waste heat source and the volumetric flow rates of the flows were obtained, and the maximum heat that could be recovered was obtained. Afterward, a parametric study was carried out to size the recuperator. The parameters affecting the cost, such as hot flow and cold flow outlet temperatures, were determined by the overall heat transfer coefficient, effectiveness, and pressure drop. Finally, the thermal parameters obtained from the parametric study are used in the technoeconomic analysis. The recuperator geometry with the maximum saving coefficient was determined considering investment and operating costs. As a result, the 108th simulation resulted in maximum savings with 653 252 $/year using 321.19 m2 heat transfer surface area.

In this study, results of HTRI Xchanger software used in the analysis of shell and tube heat exchangers (STHE), and Kern and Bell-Delaware methods, which are the conventional methods used for calculation of shell side heat transfer coefficient (SSHTC) and pressure loss (PL), were compared with experimental data. An experimental study was considered for Heat exchanger (HE) dimensions and fluid properties from literature. Then SSHTC and PL values were calculated using Kern and Bell-Delaware methods and HTRI Xchanger software for the measured shell side flowrates. SSHTC and PL values calculated for lower shell side mass flowrates by Kern method deviated from experimental results at low ratios. In addition, deviations in high flowrates values increasingly moved away from experimental results. In the Bell-Delaware method, although low deviations were observed in the high shell-side mass flowrates, the deviations increased at low flow rates and diverged from the experimental results. The deviation of SSHTC values calculated by the HTRI Xchanger program was found to be massively independent from the shell side flowrate. In addition, as in Bell-Delaware method, it has been observed that deviations in the shell side pressure loss (SSPL) calculations increased with increasing shell-side mass flowrate. As a result, SSHTC was calculated with average deviations of + 17, −11, and + 18%, by Kern and Bell-Delaware methods and HTRI Xchanger software respectively. Similarly, shell side PL was found with + 64, −25, and −32% average deviation, respectively.

In this study, energy demand of a faculty was aimed to supply with a hybrid energy system (HES) consisting of photovoltaic (PV) panels, wind turbine (WT) and bomass (BM) system with optimum power usage distribution and sized to reach a lowest cost and a reliable system. In this optimization, total net present cost (TNPC) for economic analysis, loss of power supply probability (LPSP) for reliability, and localized cost of energy (LCOE) for determining the unit energy cost were considered and an effective control algorithm was developed to decide the power source for improving system reliability. We used genetic algorithm (GA) and simulated annealing (SA), which are commonly used in the literature. On the other hand, we utilized the Grey Wolf Optimizer (GWO), which was recently found out and inspired by the hierarchy and hunting instincts of grey wolves. The results of GWO algorithm were also compared with GA and SA and confirmed that GWO is satisfying. GWO achieved better results to solve problems by setting LPSP to both 0.02 and 0.01 upper limits. When LPSP set to 0.02 maximum point, GWO suggested PV system at 86.39 kW power and BG at 50 kW power. Consequently, the energy requirement of a faculty was supplied by an optimized and designed PV/WT/BM HES. In addition, by the installation of optimized system, 144.29 tons of CO₂ emissions per year will be reduced.