Pub Date : 2026-05-01Epub Date: 2025-11-26DOI: 10.1016/j.matcom.2025.11.025
Weishi Peng , Runze Wu , Yu Wang , Jingyi Wang
To address the inherent limitations of the conventional Egret Swarm Optimization Algorithm (ESOA), this study proposes an enhanced variant, namely the improved egret swarm optimization algorithm (IESOA), which integrates a hybrid multi-strategy framework. Initially, the piecewise chaotic mapping is employed for population initialization. This approach enables a more flexible distribution of egret individuals within the initial solution space, thereby enhancing population diversity and mitigating the risk of the algorithm converging to local optima. Subsequently, an adaptive T-distribution method is introduced to update the hunting positions of egret squads. This modification strengthens the algorithms capability to escape local optima and improves its global search performance. Furthermore, a sine–cosine strategy is incorporated to dynamically adjust the search direction and control step size variations during the optimization process, which significantly accelerates the convergence speed. Experimental results demonstrate that IESOA exhibits robust performance in escaping local optima, achieves rapid convergence, and maintains relatively high optimization accuracy.
{"title":"Improved Egret Swarm Optimization Algorithm with mixed multi-strategy for system evaluation","authors":"Weishi Peng , Runze Wu , Yu Wang , Jingyi Wang","doi":"10.1016/j.matcom.2025.11.025","DOIUrl":"10.1016/j.matcom.2025.11.025","url":null,"abstract":"<div><div>To address the inherent limitations of the conventional Egret Swarm Optimization Algorithm (ESOA), this study proposes an enhanced variant, namely the improved egret swarm optimization algorithm (IESOA), which integrates a hybrid multi-strategy framework. Initially, the piecewise chaotic mapping is employed for population initialization. This approach enables a more flexible distribution of egret individuals within the initial solution space, thereby enhancing population diversity and mitigating the risk of the algorithm converging to local optima. Subsequently, an adaptive T-distribution method is introduced to update the hunting positions of egret squads. This modification strengthens the algorithms capability to escape local optima and improves its global search performance. Furthermore, a sine–cosine strategy is incorporated to dynamically adjust the search direction and control step size variations during the optimization process, which significantly accelerates the convergence speed. Experimental results demonstrate that IESOA exhibits robust performance in escaping local optima, achieves rapid convergence, and maintains relatively high optimization accuracy.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 362-381"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-11-30DOI: 10.1016/j.matcom.2025.11.030
Yuxuan Zhang, Zhiming Li
Uncertain regression analysis explores functional relationships in uncertain environments. While existing uncertain statistical models have been widely applied, they often struggle with some complex uncertain phenomena. This paper introduces an uncertain semi-varying coefficient model and derives the parameter vector using the profile least squares method. We provide residual analysis and hypothesis testing to validate the model’s fit, and introduce a significance test for constant coefficients. A case study on house prices demonstrates the model’s effectiveness, highlighting its potential for real-world applications, such as economic forecasting. Statistical tests indicate that the disturbance term should be characterized as an uncertain variable rather than a random one.
{"title":"Uncertain semi-varying coefficient model with application to housing prices","authors":"Yuxuan Zhang, Zhiming Li","doi":"10.1016/j.matcom.2025.11.030","DOIUrl":"10.1016/j.matcom.2025.11.030","url":null,"abstract":"<div><div>Uncertain regression analysis explores functional relationships in uncertain environments. While existing uncertain statistical models have been widely applied, they often struggle with some complex uncertain phenomena. This paper introduces an uncertain semi-varying coefficient model and derives the parameter vector using the profile least squares method. We provide residual analysis and hypothesis testing to validate the model’s fit, and introduce a significance test for constant coefficients. A case study on house prices demonstrates the model’s effectiveness, highlighting its potential for real-world applications, such as economic forecasting. Statistical tests indicate that the disturbance term should be characterized as an uncertain variable rather than a random one.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 270-282"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-11-25DOI: 10.1016/j.matcom.2025.11.031
Seok Young Lee , Nam Kyu Kwon , JunMin Park
This paper proposes a novel looped-functional approach that provides tractable conditions for the stability analysis and stabilization synthesis of linear systems under asynchronously sampled inputs. To reduce the conservatism of these conditions, a general looped-functional framework is introduced that includes existing approaches as special cases, and thereby yields more relaxed conditions expressed as linear matrix inequalities. Compared to several existing works, the proposed approach offers not only a general but also a specific functional structure composed of bivariate functions. One of these variables is associated with differentiation, and the other is associated with integration. The proposed framework provides relaxed conditions for both the Lyapunov functional and its time derivative, which play essential roles in the conservatism reduction of the conditions for stability analysis and stabilization synthesis. Seven numerical examples demonstrate the effectiveness of the proposed approach through maximum admissible sampling intervals, with only a small additional number of decision variables.
{"title":"Stability analysis and stabilization synthesis of asynchronously sampled-data systems via integral looped functionals composed of bivariate functions","authors":"Seok Young Lee , Nam Kyu Kwon , JunMin Park","doi":"10.1016/j.matcom.2025.11.031","DOIUrl":"10.1016/j.matcom.2025.11.031","url":null,"abstract":"<div><div>This paper proposes a novel looped-functional approach that provides tractable conditions for the stability analysis and stabilization synthesis of linear systems under asynchronously sampled inputs. To reduce the conservatism of these conditions, a general looped-functional framework is introduced that includes existing approaches as special cases, and thereby yields more relaxed conditions expressed as linear matrix inequalities. Compared to several existing works, the proposed approach offers not only a general but also a specific functional structure composed of bivariate functions. One of these variables is associated with differentiation, and the other is associated with integration. The proposed framework provides relaxed conditions for both the Lyapunov functional and its time derivative, which play essential roles in the conservatism reduction of the conditions for stability analysis and stabilization synthesis. Seven numerical examples demonstrate the effectiveness of the proposed approach through maximum admissible sampling intervals, with only a small additional number of decision variables.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 221-236"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-12-03DOI: 10.1016/j.matcom.2025.12.003
Benjamin Ducharne , Abderraouf Ouazib , Mathieu Domenjoud , Patrick Fagan , Laurent Daniel
This study extends an analytical fractional approach for describing magnetic losses to thick, low-carbon steel specimens, focusing on the influence of uniaxial mechanical stress on magnetic loss variations. The main objective is to develop a simple, yet accurate analytical model for describing magnetic losses in a low-carbon steel under static mechanical stress. The model is based on a fractional-order approach that captures the material’s dissipative behavior across a wide range of frequencies and stress levels.
The high conductivity and thickness of the tested specimens amplify the classical loss contribution, making the methods using a fixed fractional derivative order inadequate.
To address this, the order is made dependent on the maximal value of the average flux density (), reducing the relative Euclidean distance (RED(%)) between simulation predictions and experimental results to 5.4 % under stress-free conditions.
Under applied stress, a fitting procedure linking to both maximum flux density () and stress achieves a RED(%) of 3.16 % across 225 data points, albeit with excessive degrees of freedom. Simplifying the definition of to a three-parameter polynomial maintains reasonable accuracy (RED(%) = 6.7 %) while improving efficiency. Deviations are observed at = 0.5 T and 1.7 T. They are attributed to specific low-field material behaviors or experimental inconsistencies.
Finally, using a sigmoid-type function with the same number of parameters achieves an improved RED(%) of 6.4 % while ensuring physical coherence.
{"title":"Fractional approach to dynamic magnetic power losses in low-carbon steel under static mechanical stress and alternating magnetic field","authors":"Benjamin Ducharne , Abderraouf Ouazib , Mathieu Domenjoud , Patrick Fagan , Laurent Daniel","doi":"10.1016/j.matcom.2025.12.003","DOIUrl":"10.1016/j.matcom.2025.12.003","url":null,"abstract":"<div><div>This study extends an analytical fractional approach for describing magnetic losses to thick, low-carbon steel specimens, focusing on the influence of uniaxial mechanical stress on magnetic loss variations. The main objective is to develop a simple, yet accurate analytical model for describing magnetic losses in a low-carbon steel under static mechanical stress. The model is based on a fractional-order approach that captures the material’s dissipative behavior across a wide range of frequencies and stress levels.</div><div>The high conductivity and thickness of the tested specimens amplify the classical loss contribution, making the methods using a fixed fractional derivative order <span><math><mi>n</mi></math></span> inadequate.</div><div>To address this, the order <span><math><mi>n</mi></math></span> is made dependent on the maximal value of the average flux density (<span><math><msub><mrow><mi>B</mi></mrow><mrow><mi>a</mi><mi>max</mi></mrow></msub></math></span>), reducing the relative Euclidean distance (RED(%)) between simulation predictions and experimental results to 5.4 % under stress-free conditions.</div><div>Under applied stress, a fitting procedure linking <span><math><mi>n</mi></math></span> to both maximum flux density (<span><math><msub><mrow><mi>B</mi></mrow><mrow><mi>a</mi><mi>max</mi></mrow></msub></math></span>) and stress <span><math><mi>σ</mi></math></span> achieves a RED(%) of 3.16 % across 225 data points, albeit with excessive degrees of freedom. Simplifying the definition of <span><math><mi>n</mi></math></span> to a three-parameter polynomial maintains reasonable accuracy (RED(%) = 6.7 %) while improving efficiency. Deviations are observed at <span><math><msub><mrow><mi>B</mi></mrow><mrow><mi>a</mi><mi>max</mi></mrow></msub></math></span> = 0.5 T and 1.7 T. They are attributed to specific low-field material behaviors or experimental inconsistencies.</div><div>Finally, using a sigmoid-type function with the same number of parameters achieves an improved RED(%) of 6.4 % while ensuring physical coherence.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 468-482"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-11-24DOI: 10.1016/j.matcom.2025.11.026
Sayan Mandal, Pankaj Kumar Tiwari
In this study, we develop and analyze a deterministic prey–predator model where predators are generalist and follows modified Beverton–Holt-type growth dynamics due to additional foods, incorporating prey refuge. We also analyze system’s dynamics in the presence of seasonal and environmental fluctuations. Our key attention is on emphasizing the effects of density-dependent prey refuge and additional food availability on species coexistence and stability. Through theoretical analysis, we establish the feasibility of solutions under both autonomous and seasonal settings, identifying local stability criteria and the existence of positive periodic solutions. Our numerical results reveal that when there are no refuge and additional food, the system undergoes transcritical and supercritical Hopf bifurcations, leading to stable coexistence or population oscillations. However, the provision of prey refuge increases the number of coexistence equilibria, inducing bistability and, at higher levels, potential predator extinction. On variations of the levels of refuge and additional food, the system transitions from bistability to tristability, displaying complex dynamical shifts. However, the time variation of parameters significantly alter population stability, triggering periodic oscillations, chaotic regimes, and potential predator extinction under high-intensity of seasonal strengths. Sensitivity analysis confirms chaotic behavior under specific seasonal conditions, reinforcing the unpredictability of ecological dynamics. Notably, environmental noise can drive transitions between multiple equilibria, with moderate noise promoting coexistence and high noise leading to species extinction.
{"title":"Predator–prey interactions: How prey refuge, additional food, seasonality, and stochasticity shape ecological stability?","authors":"Sayan Mandal, Pankaj Kumar Tiwari","doi":"10.1016/j.matcom.2025.11.026","DOIUrl":"10.1016/j.matcom.2025.11.026","url":null,"abstract":"<div><div>In this study, we develop and analyze a deterministic prey–predator model where predators are generalist and follows modified Beverton–Holt-type growth dynamics due to additional foods, incorporating prey refuge. We also analyze system’s dynamics in the presence of seasonal and environmental fluctuations. Our key attention is on emphasizing the effects of density-dependent prey refuge and additional food availability on species coexistence and stability. Through theoretical analysis, we establish the feasibility of solutions under both autonomous and seasonal settings, identifying local stability criteria and the existence of positive periodic solutions. Our numerical results reveal that when there are no refuge and additional food, the system undergoes transcritical and supercritical Hopf bifurcations, leading to stable coexistence or population oscillations. However, the provision of prey refuge increases the number of coexistence equilibria, inducing bistability and, at higher levels, potential predator extinction. On variations of the levels of refuge and additional food, the system transitions from bistability to tristability, displaying complex dynamical shifts. However, the time variation of parameters significantly alter population stability, triggering periodic oscillations, chaotic regimes, and potential predator extinction under high-intensity of seasonal strengths. Sensitivity analysis confirms chaotic behavior under specific seasonal conditions, reinforcing the unpredictability of ecological dynamics. Notably, environmental noise can drive transitions between multiple equilibria, with moderate noise promoting coexistence and high noise leading to species extinction.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 121-148"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-11-24DOI: 10.1016/j.matcom.2025.11.029
Xing Guo , Lianghao Ji , Shasha Yang , Rongjian Liu
This paper investigates the impulsive consensus control for nonlinear multiagent systems (MASs) with semi-Markov switching topologies (semi-MSTs) under deception attacks. A novel switching-triggered impulsive control scheme is proposed, which creatively uses topology switching as an event to drive impulsive control. This method decouples the execution of impulsive control from conventional time-triggered or even-triggered approaches by introducing topology switching as the primary determinant of control updates, thereby enabling full utilization of topological information. The network topology condition for achieving impulsive consensus of MASs with semi-MSTs under this scheme can be relaxed to only require that the union of all switching subtopologies contains a spanning tree. Furthermore, deception attacks occurring in communication channels are considered, which can cause incorrect state information transmission. The random variables describing whether deception attacks occur obey Bernoulli distribution. Sufficient conditions for realizing secure impulsive consensus control of MASs with semi-MSTs under deception attacks and the upper bound on the mean square error between the leader and the followers are given. Finally, an example is presented to validate the effectiveness of the main results.
{"title":"Switching-triggered control for multiagent systems with semi-MSTs under deception attacks","authors":"Xing Guo , Lianghao Ji , Shasha Yang , Rongjian Liu","doi":"10.1016/j.matcom.2025.11.029","DOIUrl":"10.1016/j.matcom.2025.11.029","url":null,"abstract":"<div><div>This paper investigates the impulsive consensus control for nonlinear multiagent systems (MASs) with semi-Markov switching topologies (semi-MSTs) under deception attacks. A novel switching-triggered impulsive control scheme is proposed, which creatively uses topology switching as an event to drive impulsive control. This method decouples the execution of impulsive control from conventional time-triggered or even-triggered approaches by introducing topology switching as the primary determinant of control updates, thereby enabling full utilization of topological information. The network topology condition for achieving impulsive consensus of MASs with semi-MSTs under this scheme can be relaxed to only require that the union of all switching subtopologies contains a spanning tree. Furthermore, deception attacks occurring in communication channels are considered, which can cause incorrect state information transmission. The random variables describing whether deception attacks occur obey Bernoulli distribution. Sufficient conditions for realizing secure impulsive consensus control of MASs with semi-MSTs under deception attacks and the upper bound on the mean square error between the leader and the followers are given. Finally, an example is presented to validate the effectiveness of the main results.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 69-81"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-11-19DOI: 10.1016/j.matcom.2025.11.021
Huiyan Zhang , Yu Huang , Ning Zhao , Kalidass Mathiyalagan , Peng Shi
This paper investigates the issue of adaptive neural non-fragile proportional and derivative (PD) feedback control for the singular systems with unknown nonlinear dynamics. First, considering the inaccuracy of controller implementation, the problem of non-fragile controller design is considered and solved by using a robust control strategy. Second, PD feedback control is established to transform the singular system into a normal system, which facilitates stability analysis of the system. Third, the adaptive proportional–derivative radial basis function neural network technique is used to approximate the unknown nonlinear function and resist its influence. Under this designed framework, the stability conditions of the closed-loop system are given by using the Lyapunov method. The designed methods of state feedback gains and observer-based gain matrices are presented, respectively. Last, three examples are employed to elucidate the feasibility of the developed control strategy.
{"title":"RBFNN-based adaptive control of singular systems via non-fragile proportional and derivative feedback method","authors":"Huiyan Zhang , Yu Huang , Ning Zhao , Kalidass Mathiyalagan , Peng Shi","doi":"10.1016/j.matcom.2025.11.021","DOIUrl":"10.1016/j.matcom.2025.11.021","url":null,"abstract":"<div><div>This paper investigates the issue of adaptive neural non-fragile proportional and derivative (PD) feedback control for the singular systems with unknown nonlinear dynamics. First, considering the inaccuracy of controller implementation, the problem of non-fragile controller design is considered and solved by using a robust control strategy. Second, PD feedback control is established to transform the singular system into a normal system, which facilitates stability analysis of the system. Third, the adaptive proportional–derivative radial basis function neural network technique is used to approximate the unknown nonlinear function and resist its influence. Under this designed framework, the stability conditions of the closed-loop system are given by using the Lyapunov method. The designed methods of state feedback gains and observer-based gain matrices are presented, respectively. Last, three examples are employed to elucidate the feasibility of the developed control strategy.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 51-68"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-11-15DOI: 10.1016/j.matcom.2025.11.014
Zichen Yao , Zhanwen Yang , Mingying Sun
In this paper, we investigate the numerical analysis of fractional Fisher–KPP equation with Neumann boundary conditions. We rigorously establish key analytical properties of the exact solution, including positivity, boundedness, asymptotic stability, and regularity. A finite element method combined with an -implicit–explicit scheme is proposed to solve the equation. Building upon the diagonally positive-definite structure of the mass matrix, it is shown that both the semi-discrete and fully discrete schemes preserve the qualitative properties of the solution, i.e., the numerical solution remains positive for positive initial data, bounded for bounded initial data, and stable for when the exact solution is stable. We further derive the spatial error estimates by exploiting the boundedness and regularity of the exact solution. Our scheme extends effectively to irregular domains while maintaining these properties. Numerical experiments illustrate and complement the theoretical results.
{"title":"Numerical analysis of a positivity-preserving finite element method for fractional Fisher–KPP equation","authors":"Zichen Yao , Zhanwen Yang , Mingying Sun","doi":"10.1016/j.matcom.2025.11.014","DOIUrl":"10.1016/j.matcom.2025.11.014","url":null,"abstract":"<div><div>In this paper, we investigate the numerical analysis of fractional Fisher–KPP equation with Neumann boundary conditions. We rigorously establish key analytical properties of the exact solution, including positivity, boundedness, asymptotic stability, and regularity. A finite element method combined with an <span><math><mrow><mi>L</mi><mn>1</mn></mrow></math></span>-implicit–explicit scheme is proposed to solve the equation. Building upon the diagonally positive-definite structure of the mass matrix, it is shown that both the semi-discrete and fully discrete schemes preserve the qualitative properties of the solution, i.e., the numerical solution remains positive for positive initial data, bounded for bounded initial data, and stable for when the exact solution is stable. We further derive the spatial error estimates by exploiting the boundedness and regularity of the exact solution. Our scheme extends effectively to irregular domains while maintaining these properties. Numerical experiments illustrate and complement the theoretical results.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 35-50"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-05-01Epub Date: 2025-12-13DOI: 10.1016/j.matcom.2025.12.008
Fábio Castro , Bruno Canizes , João Soares , Sérgio Ramos , Zita Vale
Electric power systems are undergoing rapid evolution driven by increasing loads, widespread renewable energy integration, distributed generation, sector liberalization, and the rise of emerging technologies like electric vehicles. These transformations necessitate intelligent and efficient management of distribution networks, marking the transition to Smart Grids. This study introduces a novel optimization framework utilizing Benders’ Decomposition to tackle network reconfiguration and self-healing challenges in medium-voltage distribution networks during contingency scenarios. The proposed methodology supports decision-making by optimizing network topology and balancing supply-demand dynamics, minimizing operational costs while ensuring system resilience and reliability. Key contributions include the development of a robust tool capable of delivering optimal reconfiguration solutions with low computational latency, adaptable to networks of various sizes and topologies. Simulations on both 13-bus and 180-bus networks demonstrated the model’s scalability and effectiveness, ensuring operational continuity even under severe contingencies. Additionally, this approach accommodates modern network elements such as energy storage systems, electric vehicle charging infrastructure, and distributed renewable generation, enabling a comprehensive Smart Grid framework. The study highlights the potential for integrating this tool into real-time operational systems, ensuring proactive network management and enhanced resilience.
{"title":"Optimal power flow in distribution networks: Reconfiguration and self-healing via Benders’ decomposition","authors":"Fábio Castro , Bruno Canizes , João Soares , Sérgio Ramos , Zita Vale","doi":"10.1016/j.matcom.2025.12.008","DOIUrl":"10.1016/j.matcom.2025.12.008","url":null,"abstract":"<div><div>Electric power systems are undergoing rapid evolution driven by increasing loads, widespread renewable energy integration, distributed generation, sector liberalization, and the rise of emerging technologies like electric vehicles. These transformations necessitate intelligent and efficient management of distribution networks, marking the transition to Smart Grids. This study introduces a novel optimization framework utilizing Benders’ Decomposition to tackle network reconfiguration and self-healing challenges in medium-voltage distribution networks during contingency scenarios. The proposed methodology supports decision-making by optimizing network topology and balancing supply-demand dynamics, minimizing operational costs while ensuring system resilience and reliability. Key contributions include the development of a robust tool capable of delivering optimal reconfiguration solutions with low computational latency, adaptable to networks of various sizes and topologies. Simulations on both 13-bus and 180-bus networks demonstrated the model’s scalability and effectiveness, ensuring operational continuity even under severe contingencies. Additionally, this approach accommodates modern network elements such as energy storage systems, electric vehicle charging infrastructure, and distributed renewable generation, enabling a comprehensive Smart Grid framework. The study highlights the potential for integrating this tool into real-time operational systems, ensuring proactive network management and enhanced resilience.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 499-523"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The limitations of traditional methods for identifying resonance frequencies have driven the development of Resonance Mode Analysis (RMA) as a more effective alternative. Despite its potential, RMA faces challenges in computational efficiency, particularly in multi-terminal transmission grids. To address this, Rapid RMA, a power iteration (PI)-based approach for determining the dominant eigenvalue of the nodal impedance matrix, was introduced. However, the PI-based approach can exhibit slow convergence or fail under certain conditions. To overcome these limitations, recent advancements have proposed two new methodologies: Faster RMA, a modified shifted-inverse PI-based method, and Lanczos-based RMA, a non-Hermitian Lanczos method. This paper evaluates the computational performance of RMA-based methods using various software tools (including normal computation, parallel computation and sparse techniques) across three distinct hardware-computing systems. The study highlights practical differences in computational speed and efficiency for RMA applications under diverse scenarios. By emphasising the critical role of optimising computational tools, the paper examines how hardware and software configurations influence RMA performance, particularly in transmission grids and microgrid clusters, using MATLAB/Simulink simulations. Finally, the paper proposes an efficient RMA-based methodology that is adaptable to a wide range of grid configurations and computational environments. This approach is applied to stability studies using the positive-mode-damping stability criterion, thereby offering a robust framework for advancing harmonic resonance analysis in power systems.
{"title":"Computational time efficiency analysis for resonance studies in transmission grids and microgrid clusters","authors":"Oriol Cartiel , Juan-José Mesas , Lluís Monjo , Luis Sainz","doi":"10.1016/j.matcom.2025.12.009","DOIUrl":"10.1016/j.matcom.2025.12.009","url":null,"abstract":"<div><div>The limitations of traditional methods for identifying resonance frequencies have driven the development of Resonance Mode Analysis (RMA) as a more effective alternative. Despite its potential, RMA faces challenges in computational efficiency, particularly in multi-terminal transmission grids. To address this, Rapid RMA, a power iteration (PI)-based approach for determining the dominant eigenvalue of the nodal impedance matrix, was introduced. However, the PI-based approach can exhibit slow convergence or fail under certain conditions. To overcome these limitations, recent advancements have proposed two new methodologies: Faster RMA, a modified shifted-inverse PI-based method, and Lanczos-based RMA, a non-Hermitian Lanczos method. This paper evaluates the computational performance of RMA-based methods using various software tools (including normal computation, parallel computation and sparse techniques) across three distinct hardware-computing systems. The study highlights practical differences in computational speed and efficiency for RMA applications under diverse scenarios. By emphasising the critical role of optimising computational tools, the paper examines how hardware and software configurations influence RMA performance, particularly in transmission grids and microgrid clusters, using MATLAB/Simulink simulations. Finally, the paper proposes an efficient RMA-based methodology that is adaptable to a wide range of grid configurations and computational environments. This approach is applied to stability studies using the positive-mode-damping stability criterion, thereby offering a robust framework for advancing harmonic resonance analysis in power systems.</div></div>","PeriodicalId":49856,"journal":{"name":"Mathematics and Computers in Simulation","volume":"243 ","pages":"Pages 486-498"},"PeriodicalIF":4.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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