Modelling hydrogen production from biomass pyrolysis for energy systems using machine learning techniques

A Review of Automation and Sensors: Parameter Control of Thermal Treatments for Electrical Power Generation

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electrical power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters, such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electrical power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

Thermogravimetric and thermovolumetric study of municipal solid waste (MSW) and wood biomass for hydrogen-rich gas production: a case study of Tashkent region

Application of municipal solid and wood waste, as dominant sources of biomass, could be a promising alternative for producing energy from renewables via thermochemical gasification technology. In this paper, a study of thermogravimetric analysis (TGA) and excurrent gas composition produced by the municipal solid waste (MSW) and wood biomass gasification is presented. Thermogravimetric and heat flow curves for waste samples were performed at the temperature interval of 20-890 °C with a heating rate of 10 °C min-1 under a nitrogen atmosphere. According to thermal analysis data, differential scanning calorimetry (DSC) curves, the degradation stages of waste samples was determined, which correspond to the mono- or bimodal evolution of volatile compounds and the degradation of the resulting carbon residue. The gasification experiments were conducted in a high-pressure quartz reactor at temperatures of 850, 900, and 950 °C, using steam (0.3 g/min) and argon (2 dm3/min) as the gasifying agents. To ascertain the syngas composition, gas chromatography was employed in conjunction with a thermal conductivity detector. Both types of biomass showed remarkably similar syngas compositions. The highest concentration of hydrogen-rich gases was recorded at 950 °C for wood biomass, with 42.9 vol% and 25.2 vol% for hydrogen (H2) and carbon monoxide (CO), and for MSW, with an average 44.2 vol% and 18 vol% for H2 and CO. Higher temperatures improved the syngas composition by promoting endothermic gasification reactions, increasing hydrogen yield while decreasing tar and solid yields. This research helped to comprehend the evolution of the gasification process and the relationship between increased H2 and CO production as the gasification temperature increased.