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Soft Open Point-Based Service Restoration Coordinated With Distributed Generation in Distribution Networks

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2024年第2期60卷 2554-2566页

作者： Saaklayen, Md Abu Liang, Xiaodong Faried, Sherif O. Martirano, Luigi Sutherland, Peter E. Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK S7N 5A2 Canada Sapienza Univ Rome Dept Elect Engn I-00185 Rome Italy GE & ABB Voorheesville NY USA

The soft open point (SOP) is an emerging power electronics device in place of normally open points/tie switches in distribution systems. During a fault, service restoration can be effectively achieved by coordinating SOPs and distributed generation (DG) units. In this article, a novel two-stage SOP-based service restoration method in distribution networks is proposed: In Stage 1, a dynamic load-shedding scheme is prepared/applied during a fault occurred at the upstream grid, and the power supply to priority loads is maintained through DGs;in Stage 2, DGs, SOPs and switches are coordinated and operated to realize restoration in the outage area with controllable/dispatchable distributed generation (CDG) units dispatched to their maximum capacity limits. In both stages, real and reactive power of SOPs is regulated to maximize load restoration. A mixed-integer nonlinear programming (MINLP) model through AC power flow is developed to formulate the restoration problem mathematically. The modified IEEE 33-node test system is used to validate the proposed restoration method combined with centralized or decentralized optimization. The proposed method is also compared with an existing method, showing much improved restoration performance.

关键词： Reactive power Distribution networks Microgrids Load modeling programming Distributed power generation Power system reliability Centralized optimization decentralized optimization distributed generation distribution network mixed-integer nonlinear programming restoration soft open point

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Efficient iterative optimization to real-time train regulation in urban rail transit networks combined with Benders decomposition method

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COMPUTERS & OPERATIONS RESEARCH 2024年 162卷

作者： Yuan, Yin Li, Shukai Yang, Lixing Gao, Ziyou Beijing Jiaotong Univ Sch Syst Sci Beijing 100044 Peoples R China

Considering the rapid expansion of urban rail transit networks and increasing transfer demands, this paper investigates the design of real-time train regulation strategies for urban rail networks under disturbances. Specifically, a mixed-integer nonlinear programming (MINLP) model is constructed in a rolling horizon (RH) framework to reduce train deviations and passenger waiting times, which involves complex coupling relationships among network-wide non-transfer passengers, transfer passengers and train traffics of different lines. To effectively address the model complexity and adapt to the real-time nature of this issue, we proposed an efficient iterative optimization (IO) approach to split the original problem into a smaller-scale regulation issue and a computationally cheap passenger loading procedure, which can efficiently treat the introduced nonconvexity of the exact modelling scheme. Besides, tailored to the mixed-integer property of the model, the generalized Benders decomposition (GBD) technique is incorporated into our algorithm. Furthermore, to verify the effectiveness of our method, we describe the detailed implementation of a series of numerical experiments on a small-scale and a real-world case. Computational results show that our regulation method can effectively contribute to the reliability of train systems, improving operational efficiency and service level. Besides, it performs promising computational efficiency in dealing with large-scale real-world cases, applicable for real-time applications.

关键词： Timetabling Urban rail transit networks Train regulation Benders decomposition mixed-integer nonlinear programming

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Sequential Competitive Facility Location: Exact and Approximate Algorithms

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OPERATIONS RESEARCH 2024年第1期72卷 300页

作者： Qi, Mingyao Jiang, Ruiwei Shen, Siqian Tsinghua Univ Shenzhen Int Grad Sch Logist & Transportat Div Shenzhen 518071 Peoples R China Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

We study a competitive facility location problem (CFLP), where two firms sequentially open new facilities within their budgets, in order to maximize their market shares of demand that follows a probabilistic choice model. This process is a Stackelberg game and admits a bilevel mixed-integer nonlinear program (MINLP) formulation. We derive an equivalent, single-level MINLP reformulation and exploit the problem structures to derive two valid inequalities based on submodularity and concave overestimation, respectively. We use the two valid inequalities in a branch-and-cut algorithm to find globally optimal solutions. Then, we propose an approximation algorithm to find good-quality solutions with a constant approximation guarantee. We develop several extensions by considering general facility-opening costs and outside competitors as well as diverse facility-planning decisions, and we discuss solution approaches for each extension. We conduct numerical studies to demonstrate that the exact algorithm significantly accelerates the computation of CFLP on large-sized instances that have not been solved optimally or even heuristically by existing methods, and the approximation algorithm can quickly find high-quality solutions. We derive managerial insights based on sensitivity analysis of different settings that affect customers' probabilistic choices and the ensuing demand.

关键词： competitive facility location mixed-integer nonlinear programming branch-and-cut submodularity concave overestimation approximation algorithm

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Ecological Robustness-Oriented Grid Network Design for Resilience Against Multiple Hazards

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IEEE TRANSACTIONS ON POWER SYSTEMS 2024年第1期39卷 416-428页

作者： Huang, Hao Mao, Zeyu Panyam, Varuneswara Layton, Astrid Davis, Katherine R. Princeton Univ Dept Elect & Comp Engn Princeton NJ 08544 USA DRW Holdings LLC Houston TX 77056 USA Rani Therapeut San Jose CA 95131 USA Texas A&M Univ J Mike Walker Dept Mech Engn 66 College Stn TX 77843 USA Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA

Power systems are critical infrastructure for reliable and secure electric energy delivery. Incidents are increasing, as unexpected multiple hazards ranging fromnatural disasters to cyberattacks threaten the security and functionality of society. Inspired by resilient ecosystems, this article presents a resilient network design approach with an ecological robustness (R-ECO)-oriented optimization to improve power systems' ability to maintain a secure operating state throughout unknown hazards. The approach uses R-ECO, a surprisal-based metric that captures key features of an ecosystem's resilient structure, as an objective to strategically design the electrical network. The approach enables solvability and practicality by introducing a stochastic-based candidate branch creation algorithm and a Taylor series expansion for relaxation of the R ECO formulation. Finally, studies are conducted on the R-ECO-oriented approach using the IEEE 24 Bus RTS and the ACTIVSg200 systems. Results demonstrate improvement of the system's reliability under multiple hazards, network properties of robust structure and equally distributed power flows, and survivability against cascading failures. From the analysis, we observe that a more redundant network structure with equally distributed power flows benefits its resilience.

关键词： Ecological robustness mixed-integer nonlinear programming power networks design power system reliability power system resilience

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Packing spheres with quasi-containment conditions

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JOURNAL OF GLOBAL OPTIMIZATION 2024年第3期90卷 671-689页

作者： Fischer, Andreas Litvinchev, Igor Romanova, Tetyana Stetsyuk, Petro Yaskov, Georgiy Tech Univ Dresden Inst Numer Math Dresden Germany Autonomous Univ Nuevo Leon Fac Mech & Elect Engn San Nicolas De Los Garza Mexico Natl Acad Sci Ukraine A Pidhornyi Inst Mech Engn Problems Dept Math Modeling & Optimal Design Kharkiv Ukraine Kharkiv Natl Univ Radio Elect Dept Appl Math Kharkiv Ukraine Kharkiv Natl Univ Radio Elect Dept Syst Engn Kharkiv Ukraine Natl Acad Sci Ukraine V M Glushkov Inst Cybernet Dept Nonsmooth Optimizat Methods Kiev Ukraine

A novel sphere packing problem is introduced. A maximum number of spheres of different radii should be placed such that the spheres do not overlap and their centers fulfill a quasi-containment condition. The latter allows the spheres to lie partially outside the given cuboidal container. Moreover, specified ratios between the placed spheres of different radii must be satisfied. A corresponding mixed-integer nonlinear programming model is formulated. It enables the exact solution of small instances. For larger instances, a heuristic strategy is proposed, which relies on techniques for the generation of feasible points and the decomposition of open dimension problems. Numerical results are presented to demonstrate the viability of the approach.

关键词： Packing spheres Nonstandard packing Quasi-containment Ratio condition mixed-integer nonlinear programming Heuristic Open dimension problem Decomposition technique nonlinear programming

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Cooperative Ground-Satellite Scheduling and Power Allocation for Urban Air Mobility Networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第1期43卷 218-233页

作者： Moon, Hyung-Joo Chae, Chan-Byoung Yonsei Univ Sch Integrated Technol Seoul 03722 South Korea BK21 Grad Program Intelligent Semicond Technol Seoul 03722 South Korea

In this paper, we investigate a multi-user downlink scheduling and power allocation strategy for urban air mobility (UAM) within a 6G non-terrestrial network (NTN) framework that integrates satellite and ground networks. We consider a system model involving multiple ground stations (GSs) and a single satellite, addressing the sum rate maximization problem with link-association, power, elevation angle, and minimum quality-of-service constraints. The proposed method initially segregates satellite-serviced users to reduce interference among the remaining GS-serviced users, taking into account the locations and movements of those UAMs. Subsequently, using a graph-theoretical approach, we convert the GS link association problem into a minimum-cost maximum-flow problem. In this process, we employ an analytical method involving polynomial approximations or a numerical method using integral approximation through the sum of time-sampled parameters. We then address the non-convex power allocation problem for scheduled links through iterative algorithms. The proposed scheduling and power allocation algorithms effectively manage interference in multi-UAM and multi-GS environments, and their performance is validated through extensive simulation results. Our study provides a comprehensive framework and strategy for efficient downlink transmission in future UAM operations, paving the way for novel applications in 6G NTN.

关键词： Satellites Resource management Interference Downlink Quality of service Antenna arrays Autonomous aerial vehicles Urban air mobility non-terrestrial network resource allocation mixed-integer nonlinear programming

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Optimal scheduling of power-to-ammonia systems considering multi-load operations

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ENERGY CONVERSION AND MANAGEMENT 2025年 327卷

作者： Yang, Shuting Yang, Liuyi Zhang, Wei Bi, Kexin Ji, Xu Zhou, Li Dai, Yiyang Chai, Shiyang Dang, Yagu Sichuan Univ Sch Chem Engn Chengdu 610065 Sichuan Peoples R China

Power-to-ammonia (PtA) systems offer several benefits in terms of energy storage and may aid in the transition to net-zero carbon emissions, but the fluctuations and intermittency of renewable energy often induce a temporal and spatial mismatch between the electricity supply and chemical production. This study proposes an optimal scheduling framework by integrating the response surface methodology with mixed-integer nonlinear programming. Explicit formulas describing the Habor-Bosch process are provided in response surface models, which are simple, exhibit high fidelity, and help ensure optimal performance. In the optimization process, capacity is allocated based on the supply and utilization of renewable power, electricity, and hydrogen. This framework departs from traditional single-load production models, effectively minimizing curtailment and addressing the intermittency of renewable energy sources. The results show that multi-load operations achieve a favorable balance between economic benefits (profit of 33.8 million CNY.y(-1)) and renewable energy utilization efficiency (0.4 % curtailment). The industrial case studies considered herein validate the feasibility of PtA systems and support the development of other power-to-X systems.

关键词： Power-to-ammonia Optimal scheduling Response surface methodology mixed-integer nonlinear programming Multi-load working conditions

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Handling Multiple-Fuel Options in Economic Dispatch of Thermal Power Plants Through a Tight Model Applying Indicator Variables

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2025年第1期2025卷

作者： Sharifzadeh, Hossein Hakim Sabzevari Univ Dept Elect & Comp Engn Sabzevar Iran

Thermal power plants play a central role in present power systems because of their high efficiency, fast startup capability, and flexibility to integrate the variability of renewable generations. These thermal units can utilize various fuels, including coal, natural gas, and oil, which enhances both the economic performance and security of the overall energy system. Representing the fuel cost functions of these units with multiple fuels (MFs) as binary decisions involves adding binary variables to the economic dispatch (ED) problem. The inclusion of these binary variables and nonlinear cost functions results in a complex NP-hard mixed-integer nonlinear programming (MINLP). This paper provides another perspective on the ED, where indicator variables represent the MF options and determine which cost functions should be set to zero. Based on this perspective, the paper builds a tight model to handle the indicator variables and solve the MINLP ED. Moreover, the paper introduces an iterative solution method with a bound-tightening technique to speed up the solution process. We conducted experimental studies using eight ED case studies with MF options involving up to 1280 generating units. The optimal costs obtained from these case studies demonstrate the effectiveness of the tight model and the iterative solution method for solving the MINLP ED problem. Furthermore, the proposed approach generally outperforms earlier algorithms in terms of solution quality and robustness. Finally, the tight model can speed up the solution process by 18%-45% compared with the standard formulation in the adopted case studies.

关键词： bound tightening economic dispatch indicator variables mixed-integer nonlinear programming multiple-fuel option tight formulation valve point effect

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Generalized optimization framework for synthesis of thermally coupled distillation columns

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AICHE JOURNAL 2025年第6期71卷

作者： Liu, Chao Ma, Yingjie Li, Jie Univ Manchester Ctr Proc Integrat Sch Engn Dept Chem Engn Manchester M13 9PL England MIT Dept Chem Engn Cambridge MA USA

In this article, a generalized optimization framework is proposed for the synthesis of thermally coupled distillation systems within an equation-oriented environment. The proposed framework consists of three components: an efficient superstructure representation, a novel mathematical formulation, and the associated solution algorithm, encompassing a broad range of alternatives. The mathematical model is developed using conditional statements to activate specific sets of equations, effectively addressing existing zero-flow issues. The synthesis problem is formulated as a mixed integer nonlinear programming problem, which is optimized using our previously developed Feasible Path-Based Branch and Bound method, coupled with an improved Sequential Quadratic programming algorithm. The computational studies demonstrate that the proposed optimization framework successfully solves complex benchmark problems for separating zeotropic multicomponent mixtures within reasonable computational time with good convergence performance from easily selected starting points. The optimal configuration generated leads to a reduction in total annualized cost ranging from 3.5% to 45%.

关键词： branch and bound complex distillation system mixed-integer nonlinear programming process synthesis thermally coupled distillation

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Global optimization of mixed-integer nonlinear programs with SCIP 8

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JOURNAL OF GLOBAL OPTIMIZATION 2025年第2期91卷 287-310页

作者： Bestuzheva, Ksenia Chmiela, Antonia Mueller, Benjamin Serrano, Felipe Vigerske, Stefan Wegscheider, Fabian Zuse Inst Berlin Dept AIS2T Berlin Germany GAMS Software GmbH Zuse Inst Berlin Berlin Germany

For over 10 years, the constraint integer programming framework SCIP has been extended by capabilities for the solution of convex and nonconvex mixed-integer nonlinear programs (MINLPs). With the recently published version 8.0, these capabilities have been largely reworked and extended. This paper discusses the motivations for recent changes and provides an overview of features that are particular to MINLP solving in SCIP. Further, difficulties in benchmarking global MINLP solvers are discussed and a comparison with several state-of-the-art global MINLP solvers is provided.

关键词： Global optimization mixed-integer nonlinear programming SCIP Branch-and-cut Optimization software Benchmark

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