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Distributionally robust planning for power-to- gas integrated large wind farm systems incorporating hydrogen production switch control model

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ENERGY 2025年 314卷

作者： Son, Yeong Geon Kim, Sung Yul Hanyang Univ Dept Elect Engn Seoul South Korea

To address the challenges associated with the variability of wind power and to optimize the use of renewable energy, this study investigates the integration of large wind farms with a power-to-gas system. This integration is designed to convert surplus wind energy into hydrogen, thereby enhancing grid stability and reducing energy curtailment. In this paper, an optimal planning and operation strategy is proposed for a large wind farm coupled with a power-to-gas system. The key contributions include: (1) a mixed integer linear programming-based switch control model that accurately captures the realistic operation of the electrolyzer within the power-to-gas system, and (2) a novel distributionally robust optimization method that considers variability in wind speed distributions. The electrolyzer requires a continuous and stable output to preserve its lifespan, and the switch control model ensures realistic operational conditions. The proposed distributionally robust optimization addresses regional variations in wind speeds, balancing robustness with flexibility. A case study demonstrates that the proposed approach outperforms conventional methods. Furthermore, incorporating mixed integer linear programming-based constraints for the electrolyzer switch control led to a 20 % improvement in economic performance over systems without power-to-gas integration and reduced curtailed energy from the wind farm by up to 94.5 %.

关键词： Wind farm Power to gas Distributionally robust optimization Ambiguity set mixed-integer linear programming

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Long term turnaround planning for an oil refinery using a MILP model

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COMPUTERS & CHEMICAL ENGINEERING 2025年 194卷

作者： Lima, Ricardo A. de O. Guirardello, Reginaldo Univ Campinas UNICAMP Sch Chem Engn Ave Albert Einstein 500 BR-13083852 Campinas Brazil

This study presents a discrete-time mixed-integer linear programming (MILP) model to optimize long-term maintenance turnaround scheduling in an oil refinery focused on fuel production. Refineries are complex networks of integrated process units, and maintenance turnarounds, involving temporary shutdowns for inspection and repair, can significantly disrupt production and reduce revenues. The MILP model aims to minimize these disruptions by optimizing turnaround schedules while maintaining product supply and maximizing economic performance. The model incorporates flow, labor, resource, and planning constraints, allowing for different unit groupings and scenario simulations. Key outputs include the maintenance schedule, unit utilization rates, intermediate stock levels, production, manpower, and maintenance costs. The model serves as a decision-support tool for refining managers, enabling them to plan maintenance interventions that maximize operating profit while adhering to operational constraints.

关键词： Oil refinery Long-term maintenance Turnaround scheduling mixed-integer linear programming Operating profit

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Integrated optimisation of operations and financing for large-scale multi-period multi-product capital-constrained supply chains

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年

作者： Cheng, Junheng Lin, Yanhong Cheng, Jingya Liao, Lingtong Chu, Feng Fujian Normal Univ Sch Econ Fuzhou Peoples R China Univ Paris Saclay Univ Evry IBISC F-91020 Evry France

In a typical supply chain, the operations of procurement, production, inventory, distribution, transportation, and financing decisions are interdependent, collectively impacting the overall performance of the system. However, traditional supply chain management often prioritises minimising operating costs, rarely considering financial strategies simultaneously to achieve enhanced operational benefits. This study addresses a novel operations and financing integrated optimisation problem in multi-period, multi-product, capital-constrained supply chain systems, with the objective of maximising profit. The studied NP-hard problem is formulated as a mixed-integer linear programming (MILP) model. To efficiently and effectively tackle large-sized problems, two decomposition-based effective heuristics are developed. The first decomposes the original problem into two sub-problems: an integrated optimisation problem involving inventory, production, transportation, distribution, and financing (sub-problem 1) and a procurement problem (sub-problem 2), both of which are solved using MILP models. The second method further develops a polynomial-time heuristic for sub-problem 1. To evaluate the performance of the developed methods, 180 instances involving up to 600 products and 1200 raw materials are conducted. Experimental results show that the proposed algorithms can achieve high quality solutions with an average gap of less than 2.24% within 50 seconds. Based on the numerical analysis, managerial insights are discussed.

关键词： Multi-period supply chain management operations and financing integrated optimisation production-inventory-distribution mixed-integer linear programming matheuristic

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Smarter facility layout design: leveraging worker localisation data to minimise travel time and alleviate congestion

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第4期63卷 1326-1353页

作者： Aslan, Ayse Vasantha, Gokula El-Raoui, Hanane Quigley, John Hanson, Jack Corney, Jonathan Sherlock, Andrew Edinburgh Napier Univ Sch Comp Engn & Built Environm Merchiston CampusRoom C6710 Colinton Rd Edinburgh EH10 5DT Scotland Univ Strathclyde Dept Management Sci Glasgow City Scotland Univ Edinburgh Sch Engn Edinburgh Scotland Univ Strathclyde Natl Mfg Inst Scotland Glasgow City Scotland

This paper introduces a novel methodology leveraging worker localisation data from ultrawide-band sensors to formulate alternative facility layouts aimed at minimising travel time and congestion in labour-intensive manufacturing systems. The system preprocesses sensor data to discern flow patterns between existing stations within the production facility, such as machine tools, workbenches, and stores. This information about the movement of people and materials informs the generation of optimised layouts through scenario-based optimisation. We explored two methods to devise these new layouts: a mixed-integer linear programming method and a simulated annealing metaheuristic, the latter being specifically developed to find high-quality solutions to the quadratic layout design formulation. Both methods employ biobjective formulations, focussing on the minimisation of travel time and the reduction of congestion risk on the manufacturing floor, an aspect often neglected in prior studies. Our methodology, applied to a real-world manual assembly line case study, demonstrated the potential to reduce travel time by a minimum of 32% and alleviate congestion while maintaining significant safety distances between facilities. This was achieved by automatically identifying design features that position high-traffic facilities closely and align them to eliminate movement overlaps.

关键词： SDG 9: industry facility layout optimisation smart manufacturing mixed-integer linear programming process mining indoor localisation sensors

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Multi-objective optimization of integrated energy systems in natural gas industrial zones: Enhancing performance through variable hydrogen blending ratios

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APPLIED THERMAL ENGINEERING 2025年 268卷

作者： Mao, Yudong Li, Xinwei Liu, Jiying Yu, Mingzhi Kim, Moon Keun Yang, Kaimin Shandong Jianzhu Univ Sch Thermal Engn Jinan 250101 Peoples R China Oslo Metropolitan Univ Dept Built Environm N-0130 Oslo Norway

In order to solve the problem of new energy consumption and reduce the use of fossil fuels, a multi-objective optimization and evaluation system is constructed for Integrated energy system (IES). The system takes into account factors including economy, environmental conservation, and hydrogen blending ratio. It establishes a mixed-integer linear programming model for multi-objective optimal scheduling. The conversion of renewable energy sources into electricity, followed by its conversion into hydrogen. By changing the hydrogen blending ratio of natural gas pipeline network, each objective function can reach the best. The optimal operation of each equipment of the heat and cold networks is obtained by changing the proportion of hydrogen blending into the natural gas pipeline network. Based on the multi-objective comprehensive analysis under conditions of constant heat consumption, the optimal solution is a hydrogen blending ratio of 10.67 %. This solution results in a cost of $305,426.29, carbon emissions of 19,709,221.40 kg, and a total natural gas consumption of 19,128,759.35 m3. Compared with the conventional energy system, this scheme not only offers better economy but also has characteristics of energy saving and emission reduction, making it superior in comprehensive evaluation compared to other schemes. In conclusion, this system enhances energy utilization efficiency, maximizes the integration of renewable energy sources, and reduces carbon emissions.

关键词： Integrated energy system Multi-objective optimization algorithm mixed-integer linear programming Hydrogen blending of natural gas Renewable energy

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An improved compact formulation for the assortment optimization problem with small consideration sets

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2025年

作者： Roberti, Roberto Salvagnin, Domenico Fischetti, Matteo Univ Padua Dept Informat Engn Padua Italy

We investigate the assortment optimization problem with small consideration sets, where customers belong to classes and choose according to the k-product non-parametric ranking-based choice model - i.e., each customer's preference list contains at most k products, and customers purchase the most preferred product among the ones offered in the assortment. This problem is known to be NP-hard even when k is equal to 2. The best approximation method from the literature has a performance guarantee of 2(1-1k)k-1(1k) and can find, empirically, assortments that are 0.3-0.5% within optimality when k equals 4 and there are 100 products and 10 000 customer classes. By building upon a compact mixed-integer linear programming model proposed, in the literature, for the full non-parametric ranking-based choice model, we propose an improved compact model that features a very tight continuous relaxation and can be easily solved with a general-purpose solver. An extensive set of computational experiments shows that our improved formulation can find provably optimal assortments of instances with up to 200 products, 100 000 customers classes, and k equal to 5, in a few minutes of runtime.

关键词： Assortment optimization choice models mixed-integer linear programming exact methods

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Short-Term Optimal Scheduling of a Cascade Hydro-Photovoltaic System for Maximizing the Expectation of Consumable Electricity

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PROCESSES 2025年第2期13卷 328-328页

作者： Hu, Shuzhe Miao, Jinniu Wu, Jingyang Zhao, Liqian Wang, Yue Meng, Fanyan Wei, Chao Zhang, Xiaoqin Zhu, Benrui China Oil & Gas Piping Network Corp Beijing 102206 Peoples R China China Petr Pipeline Engn Corp Langfang 065000 Peoples R China China Petr Pipeline Res Inst Co Ltd Langfang 065000 Peoples R China Tianjin Univ Natl Key Lab Intelligent Construct & Operat & Main Tianjin 300350 Peoples R China

Fully leveraging the regulatory role of cascade hydropower in river basins and realizing complementary joint power generation between cascade hydropower and photovoltaic (PV) systems is a crucial approach to promoting the consumption of clean energy. Given the uncertainty of PV outputs, this paper introduces a short-term scheduling model for cascade hydropower-PV systems. The model aims to maximize electricity consumption by considering individual units, hydropower plant constraints, unit constraints, and grid constraints. By allocating loads among hydropower plants and periods, it optimizes hydropower's dual roles, supporting grid power supplies and coordinating with PVs, thus boosting the overall system consumption. In terms of model solution, linearization methods and modeling techniques such as piecewise linear approximation, the introduction of 0-1 integer variables, and the discretization of generation headwater are employed to handle the nonlinear constraints in the original model, transforming it into a mixed-integer linear programming problem. Finally, taking a complementary system constructed by 15 units of 4 hydropower stations and 2 photovoltaic groups in a cascade in a river basin in Southwest China as an example, the results show that through the complementary coordination of cascade hydropower and photovoltaic power, under the same grid constraints, the expected value of the power consumption of the complementary system in the model of this paper increased by 863.2 MWh, among which the power consumption of photovoltaic group 1 increased by 1035.7 MWh, and the power consumption of photovoltaic group 2 decreased by 172.5 MWh.

关键词： cascade hydropower complementary system consumable electricity mixed-integer linear programming hydropower plant

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A hybrid local search algorithm for the continuous energy-constrained scheduling problem

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JOURNAL OF SCHEDULING 2025年第1期28卷 65-84页

作者： Brouwer, Roel van den Akker, Marjan Hoogeveen, Han Univ Utrecht Dept Informat & Comp Sci Utrecht Netherlands

We consider the continuous energy-constrained scheduling problem (CECSP). A set of jobs has to be processed on a continuous, shared resource. A schedule for a job consists of a start time, completion time, and a resource consumption profile. The goal is to find a schedule such that each job does not start before its release time, is completed before its deadline, satisfies its full resource requirement, and respects its lower and upper bounds on resource consumption during processing. The objective is to minimize the total weighted completion time. We present a hybrid local search approach, using simulated annealing and linear programming, and compare it to a mixed-integer linear programming (MILP) formulation. We show that the hybrid local search approach matches the MILP formulation in solution quality for small instances and is able to find a feasible solution for larger instances in reasonable time.

关键词： Continuous scheduling Resource-constrained scheduling mixed-integer linear programming Simulated annealing

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Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment

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IEEE TRANSACTIONS ON POWER SYSTEMS 2024年第2期39卷 4735-4746页

作者： Ramesh, Arun Venkatesh Li, Xingpeng Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA

Security-constrained unit commitment (SCUC) is a computationally complex process utilized in power system day-ahead scheduling and market clearing. SCUC is run daily and requires state-of-the-art algorithms to speed up the process. The constraints and data associated with SCU Care both geographically and temporally correlated to ensure reliability of the solution, which further increases the complexity. In this article, an advanced machine learning (ML) model is used to study the patterns in power system historical data, which inherently considers both spatial and temporal (ST) correlations in constraints. The ST-correlated ML model is trained to understand spatial correlation by considering graph neural networks (GNN) whereas temporal sequences are studied using long short-term memory (LSTM) networks. The proposed approach is validated on several test systems namely, IEEE 24-Bus system, IEEE-73 Bus system, IEEE 118-Bus system, and synthetic South-Carolina (SC) 500-Bus system. Moreover, B-theta and power transfer distribution factor (PTDF) based SCUC formulations were considered in this research. Simulation results demonstrate that the ST approach can effectively predict generator commitment schedule and classify critical and non-critical lines in the system which are utilized for model reduction of SCUC to obtain computational enhancement without loss in solution quality.

关键词： Constraint reduction deep neural network graph neural networks machine learning mixed-integer linear programming model reduction security-constrained unit commitment spatio-temporal variable reduction

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A capacitated multi-vehicle covering tour problem on a road network and its application to waste collection

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第1期315卷 338-353页

作者： Fischer, Vera Paneque, Meritxell Pacheco Legrain, Antoine Burgy, Reinhard Univ Fribourg Blvd Perolles 90 CH-1700 Fribourg Switzerland Stn Ctr Ville POB 6079Stn Ctr Ville Montreal PQ Canada CIRRELT Interuniv Res Ctr Enterprise Networks Logi 2920 Chemin Tour Montreal PQ Canada GERAD Grp Res Decis Anal 2920 Chemin Tour Montreal PQ Canada Lucerne Univ Appl Sci & Arts Suurstoffi 1 CH-6343 Rotkreuz Switzerland

In most Swiss municipalities, a curbside system consisting of heavy trucks stopping at almost each household is used for non -recoverable waste collection. Due to the many stops of the trucks, this strategy causes high fuel consumption, emissions and noise. These effects can be alleviated by reducing the number of stops performed by the collection vehicles. One possibility consists of selecting a subset of candidate locations that are scattered throughout the municipality to place collection points which are used by residents to bring their waste. Provided that the underlying road network is available and that the collection vehicle has a known capacity, we refer to this problem as the capacitated multi -vehicle covering tour problem on a road network (Cm-CTP-R). We propose a road -network -based mixed -integer linear programming (MILP) formulation that exploits the sparsity of the network. We compare it against the MILP formulation that results from assuming a customer -based graph, which is typically used in vehicle routing problems (VRP). To solve large instances, we develop a two -phased heuristic approach that addresses the two subproblems the Cm-CTP-R is built on: a set covering problem to select the locations and a split -delivery VRP to determine the tours. Computational experiments on instances derived from real -life data show that the road -network -based formulation is better suited. Furthermore, the proposed heuristic provides good solutions with optimality gaps below 1.7% and finds better solutions for most of the instances that the exact method is not able to solve within a given time limit.

关键词： Combinatorial optimization Waste collection Multi-vehicle covering tour problem mixed-integer linear programming Road network

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