Since renewable energy sources have an intermittent nature, forecasting strategies are increasingly important. In parallel, ports are characterized by large energy demands, especially from berthed ships. Cold ironing systems have already been proven to reduce their environmental impact by connecting ships to the electricity grid and allowing them to switch off their auxiliary engines in port. In this work, a local energy production, consisting of photovoltaic, wind turbines, and an energy storage system, is proposed to cover the energy demand of ships. In addition, an energy forecasting strategy is presented, where the solar and wind energy potential is provided by the Weather and Research Forecasting (WRF) mesoscale model. By forecasting the energy production for the following day, the storage system can be charged from the grid at night, namely in off-peak periods, reducing the pressure on the grid in on-peak periods. The methodology is tested on the port of Ancona (Italy). Results show that energy production can directly cover 54% of energy demand, and up to 70% by adding the storage system. The forecasting strategy reduces the energy withdrawn during the daytime by 24.9% and increases that during the nighttime by 18.9%, proving the effectiveness of the proposed strategy.

Delay-Tolerant Networks (DTN) are intermittent wireless mobile networks designed to handle communications in environments where network connectivity is often disrupted due to node mobility or the absence of fixed infrastructures. These frequent disconnections lead to repeated communication attempts between nodes, thereby increasing energy consumption. DTN is often deployed in isolated and hard-to-reach environments with limited energy sources, imposing significant constraints on the performance and operational lifetime of individual DTN nodes, as well as the DTN network as a whole. Despite the significant efforts invested by researchers to develop energy-efficient algorithms and models, the problem of energy consumption persists, especially with non-renewable sources. The motivation for this research is based on the major challenges related to powering mobile nodes in DTN networks, notably due to the absence of reliable and constant energy sources. The energy constraints of the nodes, combined with their mobility, raise problems of energy consumption and durability, leading to communication interruptions, delays, data losses, and a decrease in the overall efficiency of the network. To overcome these challenges, the article proposes a long-term energy management strategy by integrating renewable energy sources, notably solar energy, into the architecture of DTN nodes. The contributions include the modeling of an energy-autonomous and sustainable solar-powered DTN node, the evaluation of the energy generated and stored by these nodes, and the validation of the effectiveness of this approach through simulations in the ONE simulator, considering realistic mobility scenarios and communication conditions. The results show that solar DTN nodes have significantly higher residual energy than those with limited power sources. Additionally, social mobility models (MBM, SPMBM) consume more energy than individual models (RW, RWP, RD), while the Spray-and-Wait and PROPHET protocols are more energy-efficient compared to Epidemic and MaxProp. These analyses reveal optimal combinations of DTN protocols and mobility models to reduce energy consumption: the Spray-and-Wait protocol aligns well with social mobility models, while PROPHET is more suited to individual mobility models.

Globalization has made the business environment more complex, with many corporations facing increasingly difficult challenges. Furthermore, some corporations place a higher focus on risk management than profit. However, risk management has continued to evolve over the years. Therefore, this study delves into the determinants influencing risk management disclosure (RMD) in energy insurance companies, addressing the complex requirements of risk and transparency. The research presents a new model and examines parameters such as profitability, leverage, liquidity, company size, and ownership structure—including public, institutional, and managerial ownership—within the framework of ISO 31000, moderated by the risk management committee. This study used a quantitative research approach to gather data from 2014 to 2023 for 133 observations through purposive sampling. The findings indicate that company profitability, leverage, liquidity, company size, and ownership structure—including public ownership and managerial ownership—have no positive effect on risk management disclosure (RMD), whereas institutional ownership has a positive impact on RMD. On the other hand, the risk management committee moderates the significant impact of public ownership, institutional ownership, and managerial ownership on RMD. This study underscores the importance of shaping risk management disclosures in the Indonesian insurance sector. This research contributes to a nuanced understanding of the factors driving RMD, offering valuable insights for stakeholders in the energy insurance industry.

The research proposes a Hybrid Renewable Energy System (HRES) that integrates wind and solar energy to address the high initial investment challenges associated with renewable energy systems. The primary objective is to develop a cost-effective energy solution for Electric Vehicle Charging Stations (EVCS) located at rest areas along the Trans Java toll road, supporting Indonesia's transition to environmentally friendly land transportation. Utilizing HOMER-Grid software, the study analyzes the potential of wind and solar energy and associated investment costs. Key outcomes include energy production, consumption, surplus energy, energy cost ratios, Net Present Cost (NPC), and Cost of Energy (COE). The findings indicate that the hybrid system can achieve a 17.66% contribution of renewable energy when connected to the primary grid, highlighting its potential to enhance efficiency and sustainability in Indonesia’s transportation sector.

It can be described that high solar radiation intensity is the basis for the performance of solar photovoltaic modules. Therefore, it causes a decrease in the efficiency of the panel due to the increase in its surface temperature and thus affects its lifespan due to periodic thermal effects. This paper presents an analysis of the PV panel performance and thermal problems and attempts to solve them by cooling it during the day using water circulation in a heat exchanger embedded in the ground. The present work aims to analyze the thermal exchange process of geothermal heat exchangers by computational simulation approach. The research parameters included changing the depth of the copper pipe loop in the soil at 0.5, 1.0, and 1.5 m, and water flow rate of 0.0278 kg/s, copper pipe length, and thermal conductivity of soil in steady conditions employing the yearly weather data of southern desert in Iraq. The computational simulation results manifested that during the solar day, the fluctuations of outlet water temperature are diminished when the burial depth of the heat exchanger is around 2.0 m due to the soil's elevated thermal inertia. In addition, the temperature of the ground is comparatively stable and these values are higher than the inlet water temperature in winter with low values in summer.

The study of non-Newtonian fluid dynamics within cardiovascular systems is critical for understanding the complex interactions between blood flow and arterial health. This research focuses on the application of the Finite Volume Method (FVM) to simulate non-Newtonian fluid behavior under pulsatile flow conditions, mimicking the heartbeat. The objective is to analyze the effects of varying viscosity properties and flow patterns on the development and progression of atherosclerosis. By employing computational simulations, we investigate the rheological properties of blood, characterized as a non-Newtonian fluid, and its impact on shear stress distribution and arterial wall interaction. The simulation framework incorporates advanced non-Newtonian models, including Power-law and Carreau-Yasuda models, to accurately represent blood viscosity variations. Pulsatile flow dynamics are modeled to replicate physiological conditions, providing insights into the mechanical forces exerted on arterial walls and their role in atherosclerotic plaque formation. The results highlight critical areas of high shear stress and low shear rate, which correlate with regions prone to atherosclerosis. This study's findings contribute to a deeper understanding of cardiovascular fluid mechanics and offer potential implications for medical diagnostics and treatment strategies for atherosclerosis. The application of the FVM in this context demonstrates its robustness in handling complex fluid behaviors and geometries, paving the way for more sophisticated simulations in biomedical engineering.

One of the main problems with a solar photovoltaic (PV) system is the partial shading condition (PSC). This results in a significant reduction of the output power of a solar PV system. This paper mainly aims at proposing and validating a novel optimization technique namely the Genetic Algorithm (GA) for Maximum Power Point Tracking (MPPT) in case of PSC. In this study, an experimental examination utilizing a PV emulator highlights the effect of PSC on PV system performance. PSC was found to result in a 37% decrease in maximum power, a 38% decrease in fill factor, and a 60% decrease in efficiency. Meta-heuristic techniques for P-V curves with several peaks can be used to track the maximum power point (MPP). GA is based on a metaheuristic methodology that has been applied to solve optimization problems in a variety of systems, such as PV systems with MPPT. With a convergence time of less than 2 ms, the suggested system can track the global MPP with 99% tracking efficiency. This demonstrates the improvement in tracking time and accuracy over traditional MPPT techniques. Additionally, the suggested system can also accomplish steady operation in dynamically changing environmental conditions and reduce the oscillations around MPP.