Global Growth in Offshore Wind Turbine Technology

Due to the commissioning of floating wind units, the latest technological developments, significant growth, and improvements in turbines, developments in offshore wind power capacity are estimated to increase faster than in the last two decades. The total installed offshore wind power capacity, which is currently 35 GW, is predicted to be approximately 382 GW by 2030 and approximately 2,002 GW by 2050. For this reason, attempts are proposed to lower levelised cost of electricity (LCOE) for offshore wind power generation more than for other energy sources. In this study firstly, the global growth in the nominal capacity and size of offshore wind turbines over the last twenty years is examined. Then, the effects of this increase in nominal capacity and size on the LOCE, total installation cost (TIC), and turbine capacity factor are investigated. In parallel with this development, the changes in distance to shore and water depth for installation offshore wind power plants are reviewed according to the years. In addition, the effects of this global growth on wind farm capacity, turbine-specific power capacity, number of turbines per GW, and area needed per GW are investigated and discussed in detail.

Boilers slagging when burning wood pellets

A promising trend for upgrading wastes from timber cutting, processing and treatment is their granulation. It allows to increase their specific heats of combustion by 2.5– 3.5 times and their portability characteristics by 3–4 times, to reduce transportation costs by 6– 10 times and to improve all the operations stages. The construction and commissioning of boiler facilities operating on refined biofuel made it possible to form a stable domestic market for wood pellets. However, 0.5 – 1.5 MW nominal capacity hot water boilers equipped with furnaces and profiled burners at the bottom, in cold seasons had fast accumulation of focal residues deposits in the burners and on the furnace chambers lining. The process was complicated by these deposits hardening due to their melting and sintering. These circumstances cause a decrease in the energy and environmental performance of heat-generating installations and their reliability, and also leads to the unplanned shutdowns to clean the boiler furnaces. To find out the reasons for these negative phenomena and to develop recommendations for their elimination, a set of research operations was carried out with wood pellets shipped by the manufacturer and supplied to the burners of the boilers under the analyses; with focal residues accumulated in the burners and on the lining of the furnace chambers; as well as an analysis of the heat generating facilities operation modes. The studies carried out made it possible to identify the main factors that caused these negative phenomena and to develop the recommendations for their elimination.

Failure Mode Determination of API 12F Shop-Welded Tanks with a New Roof-to-Shell Junction Detail

The API 12F is the specification for vertical, aboveground shop-welded storage tanks published by the American Petroleum Institute (API). The nominal capacity for the twelve tank designs given in the current 13th edition of API 12F ranges from 90 bbl. (14.3 m3) to 1000 bbl. (159 m3). The minimum required component thickness and design pressure levels are also provided in the latest edition. This study is a part of a series research project sponsored by API that dedicates to ensure the safe operation of API 12 series storage tanks. In this study, the twelve API 12F tank designs presented in the latest edition are studied. The elastic stress analysis was conducted following the procedures presented in the ASME Boiler and Pressure Vessel Code 2019, Section VIII, Division 2 (ASME VIII-2). The stress levels at the top, bottom, and cleanout junctions subject to the design pressures are determined through finite element analysis (FEA). The bottom uplift subjected to design pressures are obtained, and the yielding pressure at the roof-shell and shell-bottom junctions are also determined. The specific gravity of the stored liquid is raised from 1.0 to 1.2 in this study. A new roof-shell attachment detail is proposed, and a 0.01 in. (0.254 mm) gap between the bottom shell course and the bottom plate is modeled to simulate the actual construction details. In addition, the flat-top rectangular cleanout presented in the current edition of API 12F is modeled.

Applying the Heaviside step function to simulate the changes of temperature in automotive batteries

Discharged batteries do not provide the specified voltage in the car’s power supply system during parking, which can cause malfunctions of electrical equipment and an increase in the quiescent current in the on-board network, due to incorrect operation of electronic control units responsible for the operation of self-diagnosis systems, anti-theft alarm, multi-media, maintaining a thermal state, etc. Therefore, to ensure a reliable start of the ICE and the proper operation of the electrical equipment of a car at low temperatures, it is required to maintain the battery in a charged state. Vehicle generator is selected taking into account the nominal capacity of the battery, power and operating modes of electrical consumers, which excludes the battery operation with a low level of charge. However, when operating cars in large cities in winter, the battery charge level decreases. Deterioration of the battery charging characteristics, increased power consumption of additional equipment and low speed of movement of cars in the city with frequent stops at intersections are the reasons for the decrease in the efficiency of the battery charge. In such conditions, the battery can be discharged not only by starting the ICE and turning on consumers in the parking lot, but also when the ICE is idling and at low crankshaft speeds while driving on city routes and during rush hours. Considering that the operational characteristics of the battery change significantly with decreasing temperature, studies aimed at establishing and predicting the battery temperature during operation are relevant.

Influence of the hydrodynamic efforts on the efficiency of the regeneration of the granular filtering material in a water treatment plant

This article aims to study the hydrodynamic conditions of the parameters that influence the removal of dirt particles and aggregates by the drainage of wash water into filter materials for better regeneration efficiency. The water treatment plant with a nominal capacity of 600 m3·h−1 is located in the city of Parakou in Benin. It appears that one of the causes of the poor performance of the methods used for water treatment is the insufficient value of the shear stresses of the movement created by the flow of washing water in the filter bed. The use of hydro-elevators and hydrocyclones for the removal of particles from the surface of the grains of the filtering material under hydraulic load makes it possible to reduce the quantity of remaining pollution respectively by 1.5 to 2.5 times compared with the combined washing of water and air. To this end, the performance of grain washing in the hydrocyclone is explained by the presence of centrifugal field, self-separation and the friction of the particles between them and on the wall of the apparatus. The regeneration of the filter material under the action of ultrasonic waves reduces the remainder of particles compared to washing with water and air about 6 times.

VxG Pattern-Based Analysis and Battery Deterioration Diagnosis

This paper presents the results of an analysis using the direct current internal resistance (DCIR) method on a nickel-cobalt-manganese oxide (NCM)-based battery with a nominal capacity of 55.6 Ah. The accelerated degradation test was performed on V0G, V1G, and V2G patterns, representing existing simple power supply, smart charging control, and bi-directional charge/discharge control, respectively. We assumed V0G, V1G, and V2G patterns and conducted charging and discharging experiments according to the set conditions. According to the pattern repetition, changes in the internal resistance of DCIR and AC-impedance were analyzed and battery deterioration was diagnosed. By comparing DCIR and AC-impedance, we confirmed that the changes in internal resistance has a similar trend. In particular, we propose a new DCIR analysis method in the “stop-operation” part rather than the traditional DCIR method. In the case of traditional DCIR method, time is required for the battery to stabilize. However, the newly proposed DCIR analysis method has the advantage of diagnosing the deterioration of the battery during system operation by analyzing the internal resistance without the stabilization time of the battery.

Data-driven lithium-ion battery capacity estimation from voltage relaxation

Accurate capacity estimation is critical for reliable and safe operation of lithium-ion batteries. A proposed approach exploiting features from the relaxation voltage curve enables battery capacity estimation without requiring previous cycling information. Machine learning methods are used in the approach. A dataset including 27,330 data units are collected from batteries with LiNi0.86Co0.11Al0.03O2 cathode (NCA battery) cycled at different temperatures and currents until reaching about 71% of their nominal capacity. One data unit comprises three statistical features (variance, skewness, and maxima) derived from the relaxation voltage curve after fully charging and the following discharge capacity for verification. Models adopting machine learning methods, i.e., ElasticNet, XGBoost, Support Vector Regression (SVR), and Deep Neural Network (DNN), are compared to estimate the battery capacity. Both XGBoost and SVR methods show good predictive ability with 1.1 % root-mean-square error (RMSE). The DNN method presents a 1.5% RMSE higher than that obtained using ElasticNet and SVR. 30,312 data units are extracted from batteries with LiNi0.83Co0.11Mn0.07O2 cathode (NCM battery). The model trained by the NCA battery dataset is verified on the NCM battery dataset without changing model weights. The test RMSE is 3.1% for the XGBoost method and 1.8% RMSE for the DNN method, indicating the generalizability of the capacity estimation approach utilizing battery voltage relaxation.

An Assessment of the Efficiency and Emissions of a Pellet Boiler Combusting Multiple Pellet Types

With sustainable energy being the key to reaching climate neutrality, the utilization of non-wooden biomass is a necessity. This article compares the emissions and efficiency of combusting a number of types of agrobiomass and wood pellets. A comparison was made on a moving grate pellet burner mounted in a boiler, where flue gas had a vertical flow via two pass heat exchangers with turbulization elements. Tests were conducted on wood pellets (ENPlus), miscanthus straw pellets, sunflower husk pellets, and corn stover pellets. During combustion, both wood and miscanthus pellets met the PN-EN 303-5:2012 emission and efficiency requirements. Corn stover pellets met the requirement on the nominal capacity. Sunflower husk pellets are characterized by excessive CO and particulate matter emissions. Sunflower husk pellets were the most problematic fuel from the point of view of the results of this research. During combustion of the miscanthus straw pellets there was a need to decrease the nominal heating capacity due to ash sintering.

Modelling and Performance Analysis of Stationary Gas Turbines Operating Under Rotational Speed Transients

In order to increase the flexibility and performance of gas turbines, generally their manufacturers and research centers involved in their development are constantly seeking the expansion of their operational envelope as well as their efficiency, making the engine more dynamic, less polluting and able to respond promptly to variations in load demands. An important aspect that should be considered when analyzing these prime movers is the assessment of its behavior under transients due to load changes, which can be accomplished through the development of a detailed, accurate and effective computational model. Considering this scenario, the present work aims to develop a model for the simulation and analysis of the dynamic behavior of stationary gas turbines. The engine considered in this analysis has a nominal capacity of 30.7 MW (ISO conditions) and is composed by a two-spool gas generator and a free power turbine. The model was developed using T-MATS, an integrated Simulink/Matlab toolbox, develop by NASA. The gas turbine was evaluated under both permanent and transient regimes and each one of its component was analyzed individually. The assessment made it possible to determine the engine performance parameters such as efficiency, heat rate and specific fuel consumption and its operational limits (surge limits, stall, turbine inlet temperatures, etc.) under different load conditions and regimes. The results obtained were compared with available field data, and the relative deviations for the considered parameters were all lower than 1%.