LIU Donglin, ZHOU Xia, DAI Jianfeng, XIE Xiangpeng, TANG Yi, LI Juanshi
Integrated energy systems in buildings are an effective means to achieve low-carbon buildings. To further tap into their demand-side flexibility adjustable potential and carbon reduction potential, and reasonably allocate the interests of various entities in the building integrated energy system, a bi-level optimization scheduling strategy for building integrated energy system considering virtual energy storage in buildings under Stackelberg game framework is proposed. First, the thermal inertia of the cooling and heating system inside the building and the flexibility of the cooling and heating load are considered to leverage the virtual energy storage function of the building and improve system flexibility in the game model. Then, the genetic algorithm is used to solve the upper-level pricing model of energy operators, updating the purchase and sale electricity prices set by upper-level leaders, while the CPLEX solver is used to solve the lower-level problem, optimizing equipment output, demand response, and electricity trading plans. Finally, the proposed model is verified by case studies that it can effectively improve the economic performance and low-carbon characteristics of building integrated energy systems.
Engineering (General). Civil engineering (General), Chemical engineering
XIA Jinlei, TANG Yijie, WANG Lingling, JIANG Chuanwen, GU Jiu
In the context of “carbon peaking and carbon neutrality”, the large-scale integration and consumption of wind and solar resources is an inevitable trend in future energy development. However, as the capacity of wind and solar power integration increases, the power system also requires more flexible resources to ensure secure operation. To investigate the flexible regulation of hydropower in the system, this study focuses on the downstream stations of the hydro-wind-solar-pumped storage clean energy base in the Yalong River Basin. Considering its flexible regulation capabilities, the study conducts day-ahead optimized operational strategy research for the complementary system. First, to address the challenges of site selection and high costs associated with independent pumped storage, steady-state models for hybrid pumped storage stations in a cascade hydro-wind-solar-pumped storage system are established. To overcome the limitations of traditional models such as low predictive accuracy and the subjective selection of long short-term memory (LSTM) hyperparameters, the particle swarm optimization (PSO) algorithm is used to optimize the parameters of LSTM and the optimized LSTM model is then used to forecast the output of wind and solar power. Next, in order to fully harness the flexible regulation potential of the complementary system, a multi-objective optimal dispatching model is developed considering the economic benefits and flexible regulation margin of the complementary system in the day-ahead time. The normal boundary intersection (NBI) method is employed to solve the multi-objective problem, which can obtain the Pareto optimal solutions with an even distribution. Finally, case studies are conducted based on the actual conditions of the Yalong River Basin. By analyzing different scenarios, the effectiveness of the proposed model and the supportive role of pumped storage in enhancing system flexibility are validated. The results demonstrate that the proposed approach not only balances system profits but also fully exploits the flexible regulation potential of the system, ensuring stable operation of the system.
Engineering (General). Civil engineering (General), Chemical engineering
With the rapid development and accelerated utilization of marine resources, multi-body floating systems have become extensively used in practical applications. This study examines the coupled motions of a side-by-side anchoring system for five fishing vessels in a harbor using ANSYS-AQWA. The system is connected by hawsers and equipped with fenders to reduce collisions between the vessels. It is designed to operate in the sheltered wind-wave combined environment within Ningbo Zhoushan Port, China. Considering the diverse types and quantities of fishing vessels in the anchorage area, this paper proposes a mixed arrangement of three large-scale fishing vessels in the middle and two small-scale vessels on both sides. The time-domain analysis is performed on this system under the combined effects of wind and waves, calculating the motion responses of the five fishing vessels along with the mechanical loads at the hawsers, fenders, and moorings. The results indicate that the maximum loads on these mechanical components remain well within the safe working limits, ensuring reliable operation. In addition, the impact of varying wind-wave angles on the coupled motions of the fishing vessel system are studied. As the wind-wave angle increases, the surge motion of the fishing vessels gradually decreases, while the sway motion intensifies. The forces on the hawsers, fenders, and mooring system exhibit distinct characteristics at different angles.
To respond to the endurance bottleneck faced by unmanned undersea vehicles(UUVs) in missions such as ocean observation and resource exploration, this paper studied the hydrodynamic performance optimization of a novel foldable solar wing. To balance computational efficiency and optimization accuracy, a parametric model of the wing was established in CAESES software with variables including wing point coordinates, rounding factors of wing edges, wing gaps, and gaps between the wing and the hull. Innovatively, a hybrid optimization framework combining Sobol global sampling and the non-dominatedsorting genetic algorithm II(NSGA-II) optimization algorithm was constructed. Firstly, the Sobol algorithm was used to generate 80 sample points within the threshold space of each variable to fully explore the design space, followed by multi-generation optimization through NSGA-II. To avoid the accuracy degradation of traditional surrogate models, a coupled computational process integrating high-precision hydrodynamic solutions and optimization algorithms was established, enabling automatic co-simulation between CAESES and STAR-CCM + software. Hydrodynamic analyses were conducted on UUVs equipped with wings of different shapes to explore the impact of different parameter combinations on total drag. The optimization results indicate that a certain height difference between the two wing sections protruding from the hull is beneficial for reducing total drag. Flow field analysis shows that the optimized shape effectively suppresses energy dissipation caused by turbulence. The proposed technical route of parametric modeling, intelligent optimization, and high-precision verification not only reduces the straight-line drag of the UUV with a new configuration but also provides a methodological reference for the optimization of complex appendages, possessing significant engineering value for improving the energy utilization efficiency of underwater equipment.
The assessment for the resistance of a new ship under design can be performed through the Experimental Fluid Dynamics (EFD) or the Computational Fluid Dynamics (CFD) approach; both have their own Uncertainty Assessment (UA). In CFD field, the Verification and Validation (V&V) procedures take into account the approximations for numerical issues and the assumptions adopted to describe the physical phenomena to assess UA. Different theoretical approaches have become available over time; nevertheless, a single comprehensive solution to achieve the UA remains still unknown because as the theoretical methodology varies, the outcome changes. In current work, four different literature approaches will be augmented to perform a V&V analysis for two kinds of model hulls, tested at different speeds and compared with the experimental data. The investigations performed among results lead to the division of all the approaches into the three and four solutions families and to define a robust procedure to identify a reasonable value for the numerical uncertainty assessment. Regarding the robustness and the UA of the approaches, the first family proved successful in only 55% of cases with a UA mean value below 2.01%, while the second one always provides a quantification but with a mean value of 6.65%.
In this manuscript, we will apply the regularized meshless method, coupled with an error estimation technique, to tackle the challenge of modeling oblique incident waves interacting with multiple cylinders. Given the impracticality of obtaining an exact solution in many real engineering problems, we introduce an error estimation technique designed to achieve reliable solutions. This technique excels in providing dependable solutions that closely approximate analytical solutions. An additional advantage is its capacity to identify the optimal number of points for both source and collocating points, thereby enhancing computational efficiency. The validity of the proposed method will be demonstrated through three numerical cases, presenting results that exhibit substantial agreement.
The Bohai Sea is a semi-enclosed shallow water that is influenced by both natural and anthropogenic stressors. However, the microeukaryotic communities and environmental factors that affect them in different regions remain largely unclear. We investigated microeukaryotic communities in surface sediments from five geographic regions using high-throughput sequencing of the 18S rDNA gene. The Miaodao Archipelago, Yellow River Estuary, and Central Bohai Sea had the highest Shannon and Simpson indices of the eukaryotic communities, while the Yellow River Estuary exhibited the highest Chao1 index. The microeukaryotic communities in surface sediments were mainly composed of Dinoflagellata, Bacillariophyta, Ciliophora, Cercozoa, and Protalveolata. <i>Thalassiosira</i> has a relatively high abundance at the Liaodong Bay and Central Bohai Sea, possessing the proportion of 41.70% and 38.10%, respectively, while <i>Gonyaulax</i> was the most abundant taxa in the Bohai Bay, occupying a proportion of 57.77%. Moreover, a negative correlation between diatoms and dinoflagellates was observed. Phosphorus, nitrogen, salinity, temperature, and silicate were major environmental determinants of microeukaryotic composition. Microeukaryotic communities in the surface sediments, especially for the composition and ratio of diatoms to dinoflagellates, reflected the environmental quality of marine ecosystems. Overall, these microeukaryotic community compositions provide a reliable indicator for monitoring the level of marine eutrophication in the Bohai Sea.
The seasonal dynamics of phytoplankton communities in Korean coastal waters (KCWs) are influenced by complex interactions between ocean currents and nearshore human activities. Despite these influences, the understanding of seasonal phytoplankton changes and their environmental relationships in KCWs remains limited. We investigate the influence of the distinct characteristics of the three seas surrounding the KCWs (the Yellow Sea, the South Sea, and the East Sea) on seasonal phytoplankton communities based on field surveys conducted at 23 stations between 2020 and 2021. The East Sea exhibited higher winter temperatures due to the Jeju and Tsushima warm currents, while summer temperatures were lower compared to the other regions, highlighting the role of currents and deeper oceanic waters. The Yellow Sea showed significant freshwater influence with low salinity levels from major rivers, contrasting with the higher salinity in the East Sea. These differences led to a disparity in the productivity of the two regions: the highest value of Chl. <i>a</i> was observed to be 6.05 µg L<sup>−1</sup> in the Yellow Sea in summer. Diatoms dominated in nutrient-rich conditions, particularly in the Yellow Sea, where they comprised up to 80–100% of the phytoplankton community in summer, winter, and spring. PCA analysis revealed positive correlations between diatoms and Chl. <i>a</i>, while cryptophytes, which thrive in the absence of diatom proliferation, showed no such correlation, indicating their opportunistic growth in nutrient-limited conditions. This study highlights the significant impact of region-specific hydrographic factors on phytoplankton communities in KCWs, with diatoms dominating in summer and cryptophytes and dinoflagellates showing seasonal and regional variations. Understanding these dynamics is crucial for predicting phytoplankton bloom dynamics and their ecological implications in coastal ecosystems.
ZHANG Haigang, XIE Jinhuai, LIU Jiaqi, GONG Lijia, LI Zhi
The depth distribution characteristics of particle velocity field intensity have had a significant impact on underwater acoustic detection and estimation. In this paper, based on the approximate conditions of the incoherent normal modes sum transformation to angular integration, the angular integration form of incoherent normal modes of particle velocity was derived, which avoided the complex calculations of eigenvalues and eigenfunctions while revealing the physical mechanism behind the significant variations in particle velocity intensity with source depth and symmetrical depth. The numerical results demonstrate that the analytical expression of the angular integration of incoherent particle velocity can facilitate fast computation and effectively characterize the depth distribution characteristics of particle velocity intensity. Additionally, due to the superposition effect of the amplitude function of normal modes, there are notable differences in the depth distribution of vertical and horizontal particle velocity. Subsequently, focusing on the intensity difference of particle velocity, the study analyzed the effects of parameters such as horizontal distance, source frequency, sound speed profile, and water depth on the depth distribution characteristics of particle velocity field intensity. The findings provide a theoretical basis for passive target depth estimation based on vector fields.
Engineering (General). Civil engineering (General), Chemical engineering
ObjectiveAs the traditional ship trajectory prediction method is prone to gradient explosion and long calculation time, this paper seeks to improve its accuracy and calculation efficiency by proposing a ship trajectory prediction model based on an improved Bayesian optimization algorithm (IBOA) and temporal convolution network (TCN). MethodA temporal pattern attention (TPA) mechanism is introduced to extract the weights of each input feature and ensure the timing of the historical flight track data. At the same time, a reversible residual network （RevNet） is introduced to reduce the memory occupied by TCN model training. The IBOA is then used to find the optimality of the hyperparameters in the TCN (size of kernel K, expansion coefficient d). The model is finally validated using a five-fold cross-validation method, and trajectory prediction is carried out after obtaining the optimal model. ResultThe trajectory data is collected by automatic identification system (AIS) and verified. The root mean square error (RMSE) is found to be increased by 5.5×10−5, 3.5×10−4 and 6×10−4 in weak coupling, medium coupling and strong coupling track prediction respectively.ConclusionThe proposed network has good adaptability to complex trajectories and higher accuracy than the traditional model and long short-term memory (LSTM) model, while maintaining high prediction accuracy for trajectories with strong coupling.
The establishment of ship trajectory prediction is critical in analyzing trajectory data. It serves as a critical reference point for identifying abnormal behavior and potential collision risks for ships. Accurate and real-time ship trajectory prediction is essential during navigation. Since the timing of automatic identification system (AIS) data is irregular, traditional methods usually use time calibration to simulate the data of uniform sequencing before analysis. Inevitably, this increases the chances of error and time delays. To address this issue, we propose a time-aware LSTM (T-LSTM) single-ship trajectory model combined with the generative adversarial network (GAN) to predict multiple ship trajectories. These analysis methods are capable of directly analyzing AIS data and have demonstrated better performance in both single-ship and multi-ship trajectories. Our experimental results show that the proposed method achieves high accuracy and can meet the practical navigation requirements of ships.
The port waterway network plays an important role in the organization and management of port ship traffic. Due to limited ship operations, conflicts, congestion, and safety issues often arise in port waters. Conflicts between ships can be predicted by collision detection between ships. A novel collision detection algorithm for trajectory pairs is proposed by introducing variable time interval variables. In addition, to improve the overall accuracy of trajectory compression and reduce redundant calculation in collision detection, a multi-factor Douglas-Peucker algorithm adapted to ship trajectory compression is proposed with the consideration of speed and turn constraints. The maximum speed difference of the algorithm is increased by 1.5–2.5%, and the average speed difference increased by 2.0–4.5%. Based on the method mentioned above, the risk assessment framework of maritime collision is established and the risk situation of the waters near Ningbo Zhoushan Port is evaluated and analyzed by using ship historical track data.