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In recent years, advanced methods and smart solutions have been investigated for the safe, secure, and environmentally friendly operation of ships. Since data acquisition capabilities have improved, data processing has become of great importance for ship operators. In this study, we introduce a novel approach to ship machinery monitoring, employing generative adversarial networks (GANs) augmented with failure mode and effect analysis (FMEA), to address a spectrum of failure modes in diesel generators. GANs are emerging unsupervised deep learning models known for their ability to generate realistic samples that are used to amplify a number of failures within training datasets. Our model specifically targets critical failure modes, such as mechanical wear and tear on turbochargers and fuel injection system failures, which can have environmental effects, providing a comprehensive framework for anomaly detection. By integrating FMEA into our GAN model, we do not stop at detecting these failures; we also enable timely interventions and improvements in operational efficiency in the maritime industry. This methodology not only boosts the reliability of diesel generators, but also sets a precedent for prescriptive maintenance approaches in the maritime industry. The model was demonstrated with real-time data, including 33 features, gathered from a diesel generator installed on a 310,000 DWT oil tanker. The developed algorithm provides high-accuracy results, achieving 83.13% accuracy. The final model demonstrates a precision score of 36.91%, a recall score of 83.47%, and an F1 score of 51.18%. The model strikes a balance between precision and recall in order to eliminate operational drift and enables potential early action in identified positive cases. This study contributes to managing operational excellence in tanker ship fleets. Furthermore, this study could be expanded to enhance the current functionalities of engine health management software products.

The paper presents a technical and economic analysis for two energy systems (conventional and renewable) with grid connection. The investigation was carried out using an experimental measurement for the desired load and weather data (solar irradiance and ambient temperature), were 5.1 kWh the daily energy consumption as measured and 4.6 kWh/m /day the annual average of the solar irradiance. The simulation process was done by using MATLAB and HOMER software at a 1 min time step resolution. The economic optimization objective presented for two energy system scenarios (i) photovoltaic/grid and (ii) diesel/grid, takes into account the economic aspects and component prices based on the Iraqi market and regulations. The diesel generator, very popular in rural areas, is designed to work during the same period as the photovoltaic system (only during day hours). The yearly operating hours were recorded at 4380 h/year, and energy generation was approx. 2349 kWh/year while fuel consumption was 1826 L/year. The results showed that the photovoltaic system in scenario (i) can generate about 7895 kWh, and for the diesel generator in scenario (ii), it can generate approximately 2346 kWh. Furthermore, for scenario (i) the levelized net present cost is $1079 and the cost of energy is about $0.035/kWh, while for scenario (ii) the levelized net present cost is $12,287 and the cost of energy is $0.598/kWh. The use of solar energy is highly recommended compared to diesel generators due to the lowest cost and delivery of energy to the grid. Furthermore, it can capture carbon dioxide by about 5295 kg/year.

Currently, the high consumption of fossil fuels is causing problems, perhaps, irreversible to the planet, investing in green energy is an essential point for the sustainable development of any country. Concomitant to this, biomass fuels, in particular natural vegetable oils, appear as an option for the total or partial replacement of these fuels in the production of energy in the current world energy matrix. Corroborating this pretext, the objective of this work is to analyze the effects of using different mixtures of Brazilian commercial diesel oil (92% diesel, 8% biodiesel) with refined soybean oil from the effective cylinder pressure of a stationary diesel generator set. To achieve this purpose, the generator set of the Branco brand, model BD-6500, was used, with the aid of the pressure acquisition system of the Austrian company AVL. Analyzes of the requested fuels were carried out in addition to the experimental tests. The results presented show that the use of mixtures with volumetric ratios of soybean oil may show a drop in the cylinder pressure.

This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore minimizes the use of the genset, and it ensures that the batteries bank operates into the prefixed values of state of charge to ensure their safe operation. The EMS provides the switching control of the switches that link the plant components and decides on the loads’ operation. The simulation of the system using measured climatic data of Mostoles (Madrid, Spain) shows that the proposed EMS fulfills the designed objectives.

This paper demonstrates the optimum design and analysis of hybrid renewable energy system (HRES) for village electrification in Korkadu, Puducherry, India. Renewable energy sources (RES) comprises of photovoltaic, wind turbine and bio-diesel generators. The main target of this work is to design an optimal HRES system that can generate and provide cost-effective electricity to satisfy the electricity need. In the pre-hybrid optimization model for the electric renewable (HOMER), the paper evaluates the load forecasting for the selected district. For reliable electrification, the desired HRES needs to meet the forecasted load demand. HOMER software is used to estimate the different feasible hybrid configurations. The configurations are hybrid conventional (bio-gasifiers) and renewable energy system, standalone renewable energy system with high renewable fractions and standalone conventional (bio-gasifiers) system. From the investigations, it indicates that the Korkadu zone is highly potential area for implementing standalone hybrid electrification system. Furthermore, the proposed work result demonstrates that the HRES-based power generation at off-grid location can be a cost-effective. Additionally, our proposed strategy can conquer the uncertainty found in RES and the over-sizing issues in installed capacity.

This study aims to experimentally investigate the effects of using different percentages of ethanol-biodiesel-diesel blends in diesel internal combustion engines and to analyze energy and combustion parameters. The experiments were conducted on a single-cylinder, four-stroke, air-cooled, and constant-speed diesel generator set with a rated electrical power of 4.5 kW and 79% of full engine load (3.54kW). Temperature, fuel flow, AVL pressure, and rotation sensors were installed on the crankshaft and inside the cylinder. The fuels used were commercial diesel (S-10) and blends with 1%, 2%, and 3% of anhydrous ethanol added to diesel, changing the injection pressure in only one blend. The results show a decrease in thermal efficiency and an increase in fuel consumption, in addition to an increase in ignition delay, an increase in combustion duration, a decrease in in-cylinder pressure, and a decrease in the heat release rate as the percentage of ethanol increased.

Islanded microgrids with low-inertia distributed energy resources (DERs) are prone to frequency fluctuations. With the increasing integration of DERs in microgrids, the complexity of control and stability has also increased. Moreover, the integration of DERs into microgrids may result in a power imbalance between energy supply and demand during sudden changes in load or energy generation. This can cause frequency variations in the microgrid, which could have disastrous consequences such as equipment damage or even blackouts. This paper proposes a control strategy to ensure the efficient operation of an islanded hybrid microgrid consisting of a PV generator, battery energy storage system (BESS), and emergency diesel generator. According to Energy Exchange Model proposed in this paper, the hybrid system presented operates independently without being connected to the electrical grid, where the PV system and BESS act as the main energy sources, while the emergency diesel generator provides active power backup with voltage and frequency regulation. The novel in this paper is also that DER aids in frequency regulation during active power transients by delivering and absorbing active power in accordance with the inverter's suggested P droop control strategy. In this way inverter droop control decreases system frequency nadir emulating so called “synthetic inertia”. To design both the islanded hybrid system and the proposed control strategy, the MATLAB/Simulink environment is utilized. Based on the results, it can be concluded that the analyzed microgrid system is capable of maintaining stability and operating efficiently in a range of operating conditions.

In the quest for sustainable energy solutions, this study analyses the hybrid solar photovoltaic (PV)-diesel generator system's feasibility for reliable electricity supply to a mini-mart in Ajase-Ipo, Nigeria. Utilizing HOMER software, the system was modelled and optimized with a focus on both technical and economic factors. The optimal configuration comprises a 10.2 kW solar PV system, 8 batteries, a 6-kW converter, and a 10-kW diesel generator, meeting the annual energy demand of 29,200 kWh. The system's technical performance is highlighted by a capacity utilization factor of 17.9% and a performance ratio of 82.16%, demonstrating the efficiency of the solar PV system. However, heavy reliance on diesel fuel, with an annual consumption of 5,632 litres, leads to a high levelized cost of energy (LCOE) of 306.16 per kWh. This underscores the need for strategies to reduce diesel dependency and improve long-term economic viability through improved solar capture and optimized battery storage. The system also demonstrates significant environmental benefits, with CO2 emissions reduced by 8,614 kg annually, alongside reductions in other harmful pollutants such as CO, SO2, and NOx. These findings reinforce the potential of renewable energy to provide a more sustainable, cost-effective, and environmentally friendly solution for electricity generation in similar contexts.

Diesel generator sets are commonly used as power sources in transportation due to their versatility and cost-effectiveness. During the shutdown process, the diesel engine’s cylinder compression pressure would cause forced vibration in the driveline system through the crank linkage mechanism, resulting in unsteady loads that pose a threat to the bearing life. To address this issue, a coupling forward design method is proposed that takes into account the impact of unsteady loads on bearing life. An experiment was conducted on a 16V280 diesel generator set shutdown process, and a driveline dynamic model was established. The cumulative damage value that connects unsteady loads and bearing life was introduced to quantify the effect of unsteady loads on the bearing life during the shutdown process. The unsteady loads included torque fluctuation and collision forces. The results showed that reducing the driveline key gap and increasing the coupling stiffness can decrease the combined load on bearings and improve bearing life. A large stiffness coupling was designed to achieve shutdown smoothness and a 43.19% reduction in bearing life damage, confirming the design method’s feasibility concerning bearing life.

The purpose of the article is to assess the possibility of using a hydrogen–air gas turbine energy storage system for a wind farm in a selected area of the Magadan oblast, calculate the gas storage capacities, select the main power equipment, and also determine diesel fuel savings relative to the use of backup diesel generator sets under the same conditions.