ئەز   Ali Ibrahim Hameed

Increasing the reliability, stability, and safety of renewable energy systems depends on the integration of energy storage systems in order to balance energy production and demand. This research introduces an innovative system that combines a chemisorption unit, a phase change material (PCM)-based thermal energy storage (TES) mechanism, and a solar thermal unit with Linear Fresnel Reflectors (LFRs), tailored for residential usage. The system’s performance and dynamics are examined using TRNSYS and MATLAB software tools. Within this system, electricity is produced via a turbine propelled by the pressure differential created by chemical reactions within a chemisorption unit. Concurrently, cooling was facilitated through the ammonia evaporation process within an evaporator. At heat source temperatures between 100–200 °C, the system achieved a maximum electricity output of 2,718.9 W and a cooling rate of 14,601.5 W. The energy efficiency peaked at 46.32 %, and exergy efficiency at 40.78 %. The thermal energy storage component, with a volume of 1.5 m3, achieved a maximum storage capacity of 253.7 kWh. The study shows that higher heat source temperatures enhance production capacity but reduce the coefficient of performance (COP) for cooling by approximately 25 %. Overall, the system demonstrates significant potential for improving the efficiency and reliability of renewable energy systems.

This study aims to investigate the influence of building height and layout on energy consumption. It also analyzes methods for reducing energy consumption in these buildings. The EnergyPlus software performs simulations under local climatic conditions for all seasons. The city is divided into several sections based on cardinal directions, and energy consumption is calculated for each section, considering the city's distinct seasonal variations. Buildings in suburban areas with more sunlight exhibited higher overall energy consumption due to the reliance on heating and cooling systems, compared to the city center where denser urban areas moderated temperature extremes. Additionally, building design and insulation played significant roles. The analysis also revealed a west-to-east trend; higher consumption at the edges compared to the center. This is attributed to factors such as building density and shade from taller structures. The study further examined the impact of varying building heights. While most buildings were 20 meters tall, specific rows ranged from 21 to 25 meters. Changing these heights resulted in decreased cooling and increased heating demands in the north-south analysis, and reduced demands for both heating and cooling in the west-east analysis. This highlights the complex interplay between building layout, height, and energy consumption.

Systems are inherently tied to uncertainty, which necessitates the development of designs and schedules that accommodate this unpredictability. Particularly in modern power systems, the variable efficiency of numerous factors, including pricing, underscores the need for uncertainty modeling. In the meantime, the incorporation of EVs (electric vehicles) into the electrical grid is advancing, with these vehicles being recognized for their role in reducing dependency on fossil energies and enhancing the resilience, stability and efficiency of the grid. However, the rapid growth of the EV sector necessitates thoughtful strategies from decision-makers to manage its expansion effectively, particularly considering the environmental implications associated with the life cycle of EVs, including their charging and discharging processes. This research introduces the conceptual design and optimization approach utilizing a hybrid bat algorithm and differential evolution algorithm (BA-DEA) to improve the efficiency and resilience of EV-smart parking lots under the unpredictable conditions caused by grid pricing fluctuations within the DRP (demand response program). The technique effectively modulates daily costs by adjusting loads among peak and off-peak periods. Key features of the proposed approach include a non-dominated sorting model, innovative variable identification, a memory-based selection process, and the application of fuzzy theory to identify optimal Pareto outcomes. This methodology is not only swift in converging to a solution but also demonstrates a high likelihood of reaching the global optimum. Modeling considerations for smart hydrogen storage systems (SHSSs) incorporate significant constraints, notably those associated with electrolyzers, fuel cells, and storage capacities. The algorithm's effectiveness is validated in scenarios involving parking facilities and multiple uncertain resources, demonstrating a robust reduction in specific cost indicators and adjustments in cost dynamics when DRP is considered. Specifically, the algorithm achieves a substantial 42% decrease in cost variability when DRP is excluded, and a 46.9% reduction in cost variability when DRP is included, despite a minor 5% increase in average cost. These outcomes underscore the proposed system's capability to improve resilience and thermal performance under fluctuating conditions, making it a promising solution for future smart energy systems. Further, the results exhibited the complex interplay between cost optimization and operational adjustments in response to demand-side management.

Two-phase flow behavior and its flow patterns have a significant effect in many applications in industry. Oil-gas is one of the two-phase flow types that have many applications in petroleum and power stations. An oil-gas two-phase flow behaviour and flow patterns have been investigated in an inclined pipe using two different tomography sensors: Wire Mesh sensor (WMS) and Electrical Capacitance Tomography (ECT). A special experimental facility was designed and built to operate the tow-phase flow application in the inclined pipe with the various angle of inclination. A set of experimental data were collected using operating conditions which covered a two-phase flow range of superficial velocity of gas (Usl) from 0.05 to 0.52 m/s and superficial velocity of liquid (Usg) from 0.05 to 4.7 m/s at atmospheric pressure and room temperature. Three inclined angles to change the pipe’s inclination 45, 60, and 80-degree were applied in the experiments. The Comparison between the Wire Mesh Sensor (WMS) and Electrical Capacitance Tomography (ECT) was completed experimentally. The results revealed that there is a good agreement between the two sensors, however; the WMS had a higher frequency which was calculated 1000 frames per second compared with the ECT which worked at 200 frames per second.