In this work, biogas and biomethane production in a one-stage anaerobic digester (AD) are investigated. Four batch digesters were rotated at different speeds: 180 rpm for the first anaerobic digester (d1), 120 rpm for the second (d2), 60 rpm for the third (d3), and no speed at fourth digester (d4). Anaerobic digestion (AD) process of these digesters was thermophilic at 55℃ and 1 bar. The substrates were three liters of water, 1.5 kg of potatoes (PT), and 1.5 kg of moist cow dung (CD). Rotating speed, pressure, temperature, residence time (RT), and restarting time were investigated in theoretical and experimental energies of an anaerobic digester (AD). The simulation of one-stage anaerobic digestion (AD) is studied using Aspen Plus software. The simulations showed that increasing AD pressure by one to three bars in one stage increased biomethane production by 32%. Increasing the temperature from 35 to 70 degrees increased biomethane output by 38%. Increasing AD residence duration to 384 days increased biomethane concentration by 52.23%. The move increased AD's gross heating value by 1.73%. The experiment's findings were obtained by holding the system at 1 bar, 55℃, and varying the restarting time between 6 and 24 hours. The average biogas volume increase between the 1st-AD and the 4th-AD before rest, after restarting, and after/before restating AD operations is 118%, 124.5%, and 10.96%, respectively. The average biogas concentration increases between the 1st-AD and the 4th-AD before restating, after beginning, and after/before restating AD processes is 17.31%, 20.65%, and 6.4%, respectively. For the first and fourth digestors, the absolute average deviation (AAD) of biomethane content was 3.78% and 3.21%, respectively. Experimental and simulation data agreed. Finally, digestor performance was directly proportional to AD restarting time for one stage, with the optimal interval after 6 hours.

This study introduces two advanced artificial intelligence systems designed to model and predict various boiler trips, playing a pivotal role in maintaining boilers' normal and safe functioning. These AI systems have been meticulously developed using MATLAB, thus offering sophisticated tools for diagnosing boiler trip occurrences. Real-world operational data from a coal-fired power plant, encompassing a comprehensive range of thirty-two operational variables tied to seven distinct boiler trips, was harnessed for these innovative systems' training, validation, and analysis. The first intelligent system capitalizes on a pure Artificial Neural Network (ANN) approach, leveraging the insights drawn from plant operators' decision-making processes concerning the key variables influencing each specific boiler trip. On the other hand, the second system takes a hybrid approach, incorporating Genetic Algorithms (GAs) to emulate the decision-making role of plant operators in identifying the most influential variables for each trip. Moreover, different topology combinations were explored to pinpoint the optimal diagnostic structure. The outcomes of our investigation underline the impressive capabilities of the ANN system, successfully detecting all six considered boiler trips either before or concurrently with the detection by the plant's control system. Furthermore, the hybrid system exhibited a marginal improvement of 0.1% in Root Mean Square error compared to the pure ANN system. These findings collectively emphasize the potential of AI-driven methods in enhancing early detection and prevention of boiler trips, thereby contributing to improved operational safety and efficiency.

This article assesses various optimization algorithms used to find the sizing of standalone hybrid energy system (HES) providing energy to isolated residential area load. The HES comprises three elements: photovoltaic panels (PV), diesel generators (DG). Many optimization algorithms have been assessed in this research to determine the most effective sizing of the HES in order to reduce the PV arrays, DGs number and the overall system cost hence minimizing the cost of energy (COE). The algorithms convergence time and the resulting loss of power supply probability (LPSP) are examined in this comparison. In this article, MATLAB/Simulink is used for its robust capabilities in modeling, simulating, and analyzing dynamic systems. The optimization's constraint is maintaining a reliability of 100%, ensuring uninterrupted energy supply to meet the energy demand. The results of the optimizations demonstrate that some algorithms gave different results of sizing.

Wind energy is one of the most widely used renewable energy sources around the world. A considerable research amount was accomplished in the area of performance enhancement for H-type Darrieus VAWT using blade pitch angle regulation. This paper aims to provide a comprehensive information for future research related to performance enhancement of H-type Darrius VAWT using blade pitch angle regulation. By pointing out the current technological development, the main advantages and disadvantages of the blade pitch angle techniques used. This review discusses the main effect of fixed and variable blade pitch angle regulation, blade pitch control techniques, and mathematical modelling. The state-of-the-art on how to improve the H-type Darrieus VAWT performance by using variable pitch angle adjustment was addressed. The active variable blade pitching technique was suggested to enhance the performance of H-type Darrius VAWT as it can increase the lift force and reduce the drag force on the blade during the wind turbine operation. Additionally, DMST model was suggested to be utilized to calculate the power output as it provides relatively accurate results especially at low TSRs.

This research explores the direct and indirect impacts of PT Pertamina Geothermal (Tbk) Sibayak's geothermal exploration on the economic, social, and environmental aspects of Semangat Gunung Village in Merdeka District, Karo Regency. The study surveyed 120 residents, achieving a 100% response rate. Using the Lilliefors test, the data were found to be normally distributed. The socioeconomic and environmental impacts were assessed by comparing pre- and post-exploration conditions. Findings indicate significant effects on various aspects: employment opportunities increased, though business opportunities remained unaffected by the geothermal activities. Community income saw a decline, primarily due to environmental disruptions such as floods impacting agriculture. Despite these economic shifts, the majority of the population continued working in agriculture, with a significant minority engaged in informal businesses. The exploration activities also affected community comfort and cultural heritage, with a substantial number of residents expressing discomfort and concerns over environmental degradation. The study underscores the need for a strategic environmental management approach, identifying key internal and external factors influencing the community. Recommendations include leveraging strengths and opportunities while mitigating weaknesses and threats, using a Livelihood Approach matrix for strategic planning. These findings provide crucial insights for policymakers and stakeholders in managing the socioeconomic and environmental impacts of geothermal exploration.

The solar air heaters are generally used in food drying applications or air heating applications. The solar air heater encompasses the collector body, duct, absorber glass surface, air inlet, and air outlet tube. In the present research, the solar collector model is designed in Creo parametric design software and imported into ANSYS design modeler. The thermal analysis of the solar air dryer is conducted in the ANSYS CFX simulation package at different Reynolds numbers. To attain heat transfer enhancement, V-shaped artificial roughness is incorporated on the upper absorber plate. The V-shaped artificial roughness considered for the analysis are 60°, 90°, and 120° angles. From the thermal analysis, heat transfer coefficient (HTC) value, pressure drop, and thermos hydraulic performance parameter are determined for different V-shaped artificial roughness profiles. The CFD simulation results have shown that including ribs in the design of the solar collector enhances its heat transfer rate and THPF (thermos-hydraulic performance factor). The V-shaped ribs with a rib angle of 60° have shown superior thermal-hydraulic performance in comparison to rib angles of 90° and 120°, across all Reynolds numbers.

The investigation of the substantial impact of natural gas composition on the parameters for operation as well as the performance of centrifugal gas compressors in gas turbine power plants is presented in this paper. The efficiency and dependability of these compressors are greatly impacted by the composition of natural gas, which is defined by the different proportions of methane, ethane, propane, butane, nitrogen, carbon dioxide, and other trace elements. This paper attempts to outline the complex effects of different gas compositions on compressor efficiency, maintenance needs, and overall plant operations through a thorough examination. Important factors to consider include how compressor longevity and performance are affected by gas density, energy content, corrosive components, moisture content, inert gases, and combustion characteristics. In addition, the study examines mitigating tactics to deal with issues brought on by variations in gas composition, including material compatibility, adaptive technologies, monitoring systems, and maintenance plans. This study offers insightful information that is crucial for maximizing the dependability and efficiency of centrifugal gas compressors in gas turbine power plants under various natural gas compositions.

This document delineates the central supervision and control variables for photovoltaic parks that possess a net adequate capacity or power exceeding 5 MW, which are interconnected to the National Interconnected System (SIN) serving as a backup to Colombia's Regional Transmission System (STR). To establish a comprehensive understanding of the operating limits and control variables for photovoltaic solar plants with a net adequate capacity or maximum power of at least 5 MW, a research and analysis methodology was developed in accordance with the regulatory framework in Colombia. This methodology aims to underpin the regulatory parameters and operational guidelines for enhancing the efficiency and compliance of these energy systems.