Chen Pan, ChangGyoon Lim^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3747-3781, 2025, DOI:10.32604/cmes.2025.073389 - 23 December 2025

Abstract Solar forecasting using ground-based sky image offers a promising approach to reduce uncertainty in photovoltaic (PV) power generation. However, existing methods often rely on deterministic predictions that lack diversity, making it difficult to capture the inherently stochastic nature of cloud movement. To address this limitation, we propose a new two-stage probabilistic forecasting framework. In the first stage, we introduce I-GPT, a multiscale physics-constrained generative model for stochastic sky image prediction. Given a sequence of past sky images, I-GPT uses a Transformer-based VQ-VAE. It also incorporates multi-scale physics-informed recurrent units (Multi-scale PhyCell) and dynamically weighted fuses… More >

Michał Guminiak¹, Marcin Kamiński^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3133-3163, 2025, DOI:10.32604/cmes.2025.071887 - 23 December 2025

Abstract The analysis of the dynamics of surface girders is of great importance in the design of engineering structures such as steel welded bridge plane girders or concrete plate-column structures. This work is an extension of the classical deterministic problem of free vibrations of thin (Kirchhoff) plates. The main aim of this work is the study of stochastic eigenvibrations of thin (Kirchhoff) elastic plates resting on internal continuous and column supports by the Boundary Element Method (BEM). This work is a continuation of previous research related to the random approach in plate analysis using the BEM.… More >

Qiuyu Lu¹, Yunqi Yan², Yang Liu¹, Ying Chen^2,*, Yinguo Yang¹, Tannan Xiao³, Guobing Wu¹

Energy Engineering, Vol.122, No.12, pp. 4799-4814, 2025, DOI:10.32604/ee.2025.069131 - 27 November 2025

Abstract The rapid expansion of offshore wind energy necessitates robust and cost-effective electrical collector system (ECS) designs that prioritize lifetime operational reliability. Traditional optimization approaches often simplify reliability considerations or fail to holistically integrate them with economic and technical constraints. This paper introduces a novel, two-stage optimization framework for offshore wind farm (OWF) ECS planning that systematically incorporates reliability. The first stage employs Mixed-Integer Linear Programming (MILP) to determine an optimal radial network topology, considering linearized reliability approximations and geographical constraints. The second stage enhances this design by strategically placing tie-lines using a Mixed-Integer Quadratically Constrained More >

Miguel A. Millán^1,*, Rubén A. Galindo², Fausto Molina-Gómez¹

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2923-2941, 2025, DOI:10.32604/cmes.2025.069356 - 30 September 2025

Abstract Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes, resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns. This complexity poses significant challenges for slope stability analysis, requiring the development of specialized techniques to address these issues. This research presents a numerical methodology that incorporates spatial variability, nonlinear material characterization, and probabilistic analysis using a Monte Carlo framework to address this issue. The heterogeneous structure is represented by randomly assigning different lithotypes across the slope, while maintaining predefined global proportions. This contrasts with the more common approach… More >

Yoshihiro Kanno^1,*, Izuru Takewaki²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 115-152, 2025, DOI:10.32604/cmes.2025.061551 - 11 April 2025

Abstract Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review on optimization-based methods for uncertainty analysis, with focusing attention on specific properties of adopted numerical optimization approaches. We collect and discuss the methods based on nonlinear programming, semidefinite programming, mixed-integer programming, mathematical programming with complementarity constraints, difference-of-convex programming, optimization methods using surrogate models and machine learning techniques, and metaheuristics. As a closely related topic, we also overview the methods for assessing structural robustness using non-probabilistic uncertainty modeling. We conclude the paper by drawing several remarks through More >

Yongfeng Fang^1,3, Kong Fah Tee^2,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 771-771, 2025, DOI:10.32604/sdhm.2024.061036 - 03 April 2025

Abstract This article has no abstract. More >

Yukai Li^1,*, Ruixue Zhang¹, Yongfeng Ni¹, Hongkai Qiu¹, Yuning Zhang², Chunming Liu²

Energy Engineering, Vol.122, No.2, pp. 681-707, 2025, DOI:10.32604/ee.2024.058981 - 31 January 2025

Abstract Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network (ADN) and the difficulty of security assessment of distribution network, this paper proposes a two-phase scheduling model for flexible resources in ADN based on probabilistic risk perception. First, a full-cycle probabilistic trend sequence is constructed based on the source-load historical data, and in the day-ahead scheduling phase, the response interval of the flexibility resources on the load and storage side is optimized based on the probabilistic trend, with the probability of the security boundary as the security constraint, and with… More >

Xueqian Wang^*, Hongsheng Su

Energy Engineering, Vol.122, No.2, pp. 667-680, 2025, DOI:10.32604/ee.2024.058102 - 31 January 2025

Abstract As the proportion of new energy increases, the traditional cumulant method (CM) produces significant errors when performing probabilistic load flow (PLF) calculations with large-scale wind power integrated. Considering the wind speed correlation, a multi-scenario PLF calculation method that combines random sampling and segmented discrete wind farm power was proposed. Firstly, based on constructing discrete scenes of wind farms, the Nataf transform is used to handle the correlation between wind speeds. Then, the random sampling method determines the output probability of discrete wind power scenarios when wind speed exhibits correlation. Finally, the PLF calculation results of More >

Jeng-Shyang Pan^1,2, Wenda Li¹, Shu-Chuan Chu^1,*, Xiao Sui¹, Junzo Watada³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3033-3062, 2024, DOI:10.32604/cmc.2024.056310 - 18 November 2024

Abstract The growth optimizer (GO) is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environment. However, the original GO algorithm is constrained by two significant limitations: slow convergence and high memory requirements. This restricts its application to large-scale and complex problems. To address these problems, this paper proposes an innovative enhanced growth optimizer (eGO). In contrast to conventional population-based optimization algorithms, the eGO algorithm utilizes a probabilistic model, designated as the virtual population, which is capable of accurately replicating the… More >

Hongsheng Su, Shilin Song^*, Xingsheng Wang

Energy Engineering, Vol.121, No.11, pp. 3289-3303, 2024, DOI:10.32604/ee.2024.054643 - 21 October 2024

Abstract This paper introduces the Particle Swarm Optimization (PSO) algorithm to enhance the Latin Hypercube Sampling (LHS) process. The key objective is to mitigate the issues of lengthy computation times and low computational accuracy typically encountered when applying Monte Carlo Simulation (MCS) to LHS for probabilistic trend calculations. The PSO method optimizes sample distribution, enhances global search capabilities, and significantly boosts computational efficiency. To validate its effectiveness, the proposed method was applied to IEEE34 and IEEE-118 node systems containing wind power. The performance was then compared with Latin Hypercubic Important Sampling (LHIS), which integrates significant sampling More >