This study constructs a distributed generation (DG) multi-objective hierarchical optimal planning model. A solution method is proposed based on an improved beluga whale optimization algorithm (IBWO). Reasonable planni...
详细信息
This study constructs a distributed generation (DG) multi-objective hierarchical optimal planning model. A solution method is proposed based on an improved beluga whale optimization algorithm (IBWO). Reasonable planning of the location and capacity of DG access to the distribution network plays an important role in minimizing actual power losses, reducing grid operating costs, and improving voltage distribution. The output power of DG has uncertainties and the demand response on the load side can also affect the DG planning;however, previous studies have ignored these two critical factors. This study aims to determine the optimal location and capacity of DG access to distribution network considering the demand response and the uncertainty of DG output power to improve the economic benefit, power quality and energy utilization efficiency. This study proposes an IBWO algorithm with better performance, aiming at the multi-objective, multi-constrained and nonlinear DG planning problem and a DG multi-objective hierarchical optimal planning model is established. The results show that proposed method can reduce the annual comprehensive cost, total voltage deviation and power loss of system by 11.66%, 40.55% and 38.61%.
Accurately structural damage identification remains a significant challenge due to dynamic response fluctuations caused by temperature variations. To address this problem, a novel two-stage damage identification metho...
详细信息
Accurately structural damage identification remains a significant challenge due to dynamic response fluctuations caused by temperature variations. To address this problem, a novel two-stage damage identification method based on Multi-head Convolutional Neural Network (MCNN) and improved beluga whale optimization algorithm (IBWO) is proposed to precisely predict temperatures, localize the damage, and quantify damage severity. First, the MCNN is exploited to forecast the ambient temperature and detect the number of damaged locations. The predicted values are then fed into an iterative optimization process of the IBWO to identify the damage location and severity. Finally, numerical models of simply supported beams and a 3-storey bookshelf structure are employed to verify the effectiveness and robustness of this method under measurement noises. Results demonstrate that the two-stage diagnosis method can accurately identify both single and multiple damages under varying ambient temperatures. The comparison study with two other state-of-the-art methods also demonstrates the superior performance of the two-stage method in damage localization and quantification.
With the swift evolution of renewable energy technologies, the design and optimization of microgrids have emerged as vital components for fostering energy transition and promoting sustainable development. This study p...
详细信息
With the swift evolution of renewable energy technologies, the design and optimization of microgrids have emerged as vital components for fostering energy transition and promoting sustainable development. This study presents a bi-level capacity optimization model for microgrids, integrating wind-solar generation with hybrid electric-hydrogen energy storage systems to simultaneously enhance economic efficiency and system stability. The outer layer minimizes the annual total cost through the application of an improvedbelugawhaleoptimization (IBWO) algorithm, which is enhanced by strategies including the reverse elitism strategy, horizontal and vertical crossover operations, and a whirlwind scavenging strategy to improve performance. The inner layer builds on the optimized results from the outer layer, employing a Multivariable Variational Mode Decomposition (MVMD) algorithm to regulate the power output of the energy storage system. By integrating electric-hydrogen hybrid storage technology, the inner layer effectively mitigates power fluctuations. Furthermore, this study designs a modal decomposition-based charging and discharging scheduling strategy to ensures the system's continuous and stable operation. Simulations performed on MATLAB 2018b and CPLEX 12.8 platforms indicate that the proposed dual-layer model decreases annual total expenses by 27.5% compared to a single-layer model while keeping grid-connected power variations within 10% of the installed capacity. This research provides innovative perspectives on microgrid optimization design and offers substantial technical support for ensuring stability and economic efficiency in intricate operational settings.
With the acceleration of urbanization, the number of urban rail transit trains has increased dramatically, and the economy and safety of subway trains have become important standards. As an essential subsystem of the ...
详细信息
With the acceleration of urbanization, the number of urban rail transit trains has increased dramatically, and the economy and safety of subway trains have become important standards. As an essential subsystem of the subway train, the bogie has a long maintenance process and serious failure consequences. So, it is essential to formulate a reasonable maintenance strategy to ensure its operation. To solve the above problems, a preventive maintenance (PM) strategy for key components of train bogie is established with consideration of failure risk in this paper. Firstly, the failure risk factors of the bogie components are scored and weighted, and the failure risk cost model and PM cost model are established. Next, a Weibull distribution parameter estimation method for bogie components based on the improved beluga whale optimization algorithm (IBWO) is proposed, providing a theoretical basis for PM decision-making optimization. Then, the Le ' vy flight is introduced into particle swarm optimization to enhance the optimization performance of the model and obtain the optimal solution. Finally, the bogie key components of Nanning Metro line 1 are selected as a case study. The results show that the IBWO algorithm has strong applicability and feasibility, and can accurately calculate the Weibull parameter values of the bogie key components. Compared with the PM plan without considering the failure risk, the proposed method is more economical and safer, which can provide necessary theoretical support for the maintenance decision optimization of urban rail transit train components.
暂无评论