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Due to the pressures caused by the energy crisis, environmental pollution, and international regulations, the largest ship-producing nations are exploring renewable resources, such as wind power, solar energy, and fuel cells to save energy and develop more environmentally-friendly ships. Solar energy has recently attracted a great deal of attention from both academics and practitioners; furthermore, the optimization of energy management has become a research topic of great interest. This paper takes a solar-diesel hybrid ship with 5000 car spaces as its research object. Then, following testing on this ship, experimental data were obtained, a multi-objective optimization model related to the ship’s fuel economy and diesel generator’s efficiency was established, and a partial swarm optimization algorithm was used to solve a multi-objective problem. The results show that the optimized energy management strategy for a hybrid energy system should be tested under different electrical loads. Moreover, the hybrid system’s economy should be taken into account when the ship’s power load is high, and the output power from the new energy generation system should be increased as much as possible. Finally, the diesel generators’ efficiency should be taken into consideration when the ship’s electrical load is low, and the injection power of the new energy system should be reduced appropriately.

Sibuyan Island is experiencing a significant increase in electricity demand due to population growth, urbanization, and industrial development. The island plans to use solar energy, recognizing its abundance and renewable nature; thus, this study was conducted to visualize the spatial distribution of solar exploration suitability using a geographic information system (GIS). Various criteria, including climatology, location, geography, meteorology, and disaster susceptibility, were considered in the assessment. Parameters affected by government policies, such as protected areas, proximity to rivers, roads and faults, ancestral domains, and proclaimed watersheds, were also considered. Parameters were weighted, and suitability levels were highlighted using AHP. The study revealed that about 5.88% (2674.06 km2) of the island was categorized as highly suitable for a solar farm, 34.99% (15,908.21 km2) as suitable, 2.49% (1129.95 km2) as moderately suitable, and the majority, 56.64% (25,754.47 km2), was considered not suitable for solar projects. A solar power suitability map was developed as a reference for local governments and residents in establishing solar PV systems in their respective sites, thus maximizing the full potential of their land. The study also directs future solar power exploration studies in Sibuyan Island, supporting ongoing efforts to maximize solar energy utilization.

This paper presents an exergy analysis of an actual two-pass (RO) desalination system with the seawater solution treated as a real mixture and not an ideal mixture. The actual 127 ton/h two pass RO desalination plant was modeled using IPSEpro software and validated against operating data. The results show that using the (ERT) and (PX) reduced the total power consumption of the SWRO desalination by about 30% and 50% respectively, whereas, the specific power consumption for the SWRO per m3 water decreased from 7.2 kW/m3 to 5.0 kW/m3 with (ERT) and 3.6 kW/m3 with (PX). In addition, the exergy efficiency of the RO desalination improved by 49% with ERT and 77% with PX and exergy destruction was reduced by 40% for (ERT) and 53% for (PX). The results also showed that, when the (ERT) and (PX) were not in use, accounted for 42% of the total exergy destruction. Whereas, when (ERT) and (PX) are in use, the rejected seawater account maximum is 0.64%. Moreover, the (PX) involved the smallest area and highest minimum separation work.

A pneumatic radial piston motor is studied in this paper in order to establish a dynamic modelling and simulation method. As a result of using geometric parameters, the piston cylinder volume change was calculated, and the heat transfer equation, thermodynamic energy balance equation, and motion equation were combined in order to create a complete model of the piston cylinder. With the aid of compressed air, several experimental tests were conducted, and the results of rotational speed with varying inlet pressure were fed into the simulation to determine one of the critical unknown parameters, such as the overall friction coefficient of the system. For the studied piston motor, this coefficient was 0.0625 Nm. Computer simulations can be used to adjust design parameters in order to reach a higher rotation speed by using an accurate model. As a result, better efficiency and performance present several opportunities that would not be possible when running experimental tests in a lab. The mathematical model yielded higher rotational speeds of 50 RPM on average, with an increased piston diameter of 1.775 mm; by increasing the diameter of the cylinder to 25.8 mm, it was possible to achieve faster rotational speeds. The performed precise simulation could be used for further motor design and optimisation, and performance estimates under a broader range of operational conditions. Simulations should be conducted on multiple sets of experimental test results to determine the correct foverall value for each motor. In addition to guiding the design and optimisation of the motor, simulations could also predict its performance under a broader range of operating conditions by utilising effective parameters such as geometrical characteristics, flow conditions, and motion equations.

The outbreak of SARS-COV-2 disease 2019 (COVID-19) abruptly changed the patterns in electricity consumption, challenging the system operations of forecasting and balancing supply and demand. This is due to the mitigation measures that include lockdown and Work from Home (WFH), which decreased the aggregated demand and remarkably altered its profile. Here, we characterise these changes with various quantitative markers and compare it with pre-COVID-19 business-as-usual data using Great Britain (GB) as a case study. The ripple effects on the generation portfolio, system frequency, forecasting accuracy and imbalance pricing are also analysed. An energy data extraction and pre-processing pipeline that can be used in a variety of similar studies is also presented. Analysis of the GB demand data during the March 2020 lockdown indicates that a shift to WFH will result to a net benefit for flexible stakeholders, such as consumer on variable tariffs. Furthermore, the analysis illustrates a need for faster and more frequent balancing actions, as a result of the increased share of renewable energy in the generation mix. This new equilibrium of energy demand and supply will require a redesign of the existing balancing mechanisms as well as the longer-term power system planning strategies.

The accurate prediction of the performance output of photovoltaic (PV) installations is becoming ever more prominent. Its success can provide a considerable economic benefit, which can be adopted in maintenance, installation, and when calculating levelized cost. However, modelling the long-term performance output of PV modules is quite complex, particularly because multiple factors are involved. This article investigates the available literature relevant to the modelling of PV module performance drop and failure. A particular focus is placed on cracks and hotspots, as these are deemed to be the most influential. Thus, the key aspects affecting the accuracy of performance simulations were identified and the perceived relevant gaps in the literature were outlined. One of the findings demonstrates that microcrack position, orientation, and the severity of a microcrack determines its impact on the PV cell’s performance. Therefore, this aspect needs to be categorized and considered accordingly, for achieving accurate predictions. Additionally, it has been identified that physical modelling of microcracks is currently a considerable challenge that can provide beneficial results if executed appropriately. As a result, suggestions have been made towards achieving this, through the use of methods and software such as XFEM and Griddler.

To date, only a few studies have examined the execution of the actuator disc approximation for a full-size turbine. Small-scale models have fewer constraints than large-scale models because the range of time-scale and length-scale is narrower. Hence, this article presents the methodology in implementing the actuator disc approach via the Reynolds-Averaged Navier-Stokes (RANS) momentum source term for a 20-m diameter turbine in an idealised channel. A structured grid, which varied from 0.5 m to 4 m across rotor diameter and width was used at the turbine location to allow for better representation of the disc. The model was tuned to match known coefficient of thrust and operational profiles for a set of validation cases based on published experimental data. Predictions of velocity deficit and turbulent intensity became almost independent of the grid density beyond 11 diameters downstream of the disc. However, in several instances the finer meshes showed larger errors than coarser meshes when compared to the measurements data. This observation was attributed to the way nodes were distributed across the disc swept area. The results demonstrate that the accuracy of the actuator disc was highly influenced by the vertical resolutions, as well as the grid density of the disc enclosure.