Article
Engineering, Electrical & Electronic
Dominik Putz, Daniel Schwabeneder, Hans Auer, Bernadette Fina
Summary: This paper addresses the Unit Commitment problem in power supply systems by using mixed-integer linear programming and backward dynamic programming. By enhancing the dynamic programming algorithm with state prediction, the proposed formulation significantly reduces computation time and delivers satisfactory solutions in a shorter time compared to other approaches. Additionally, the linear dependence of computation time on the number of steps is a key advantage of the dynamic programming strategy, especially for longer planning horizons.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Xinyu Wu, Yiyang Wu, Xilong Cheng, Chuntian Cheng, Zehong Li, Yongqi Wu
Summary: Optimizing hydro unit commitment has the potential to improve water use efficiency, but it is necessary to consider complex constraints from power grid, hydropower station, and unit operation. To overcome the problem of conflicting constraints leading to no feasible solution, a constraint grading principle is proposed to convert hard constraints into soft constraints and rank them in priority levels. The proposed method effectively solves the problem of no feasible solution due to conflicting constraints in HUC.
Article
Management
Meziane Aider, Oussama Gacem, Mhand Hifi
Summary: This paper investigates the application of branch and solve strategies in solving large-scale quadratic multiple knapsack problems. By developing an enhanced fix and solve solution procedure embedded in the local branching-based method, the proposed method is analyzed on multiple benchmark instances and newly generated large-scale instances.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2022)
Article
Mechanics
G. Ntourmas, F. Glock, F. Daoud, G. Schuhmacher, D. Chronopoulos, E. Oezcan
Summary: This manuscript presents two novel formulations for manufacturable stacking sequence retrieval, achieving solutions that meet both design and manufacturing requirements through a two-stage optimization approach. Using mathematical programming algorithms, high-quality solutions can be consistently obtained, with increased design freedom concerning blending formulation.
COMPOSITE STRUCTURES
(2021)
Article
Management
Federico Alonso-Pecina, David Romero, Marco Antonio Cruz-Chavez
Summary: In the label printing problem, the objective is to print a set of labels in specified quantities using predefined templates. Each template can hold a fixed number of printing plates. The problem involves determining the partition of labels, the number of identical printing plates for each label, and the number of imprints for each template. The proposed Iterated Local Search heuristic has shown improvements over existing results and has been able to find optimal solutions for known instances.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Computer Science, Artificial Intelligence
Jiayi Zhang, Chang Liu, Xijun Li, Hui-Ling Zhen, Mingxuan Yuan, Yawen Li, Junchi Yan
Summary: This paper surveys the trend of using machine learning to solve mixed-integer programming problems. Machine learning methods can provide solutions based on patterns from training data. The integration of machine learning and mixed-integer programming is discussed, including both exact and heuristic algorithms. The outlook for learning-based solvers, the expansion to other combinatorial optimization problems, and the embrace of traditional solvers and machine learning components are proposed. A list of papers utilizing machine learning technologies for combinatorial optimization problems is maintained.
Article
Operations Research & Management Science
Arne Schulz
Summary: This paper presents a new mathematical approach to solve the maximally diverse grouping problem and compares it with other methods, demonstrating better performance and efficiency.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Bruno Colonetti, Erlon Finardi, Samuel Brito, Victor Zavala
Summary: Unit commitment is a complex problem in power system operations that has yet to be fully solved. Operators currently use optimization solvers and simplifications to address the problem, but solving it in a timely manner remains a challenge. This study proposes a parallel dynamic integer programming approach for solving the unit commitment problem, which has been successfully applied to different power systems with impressive speed-ups compared to sequential strategies.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Deniz Tuncer, Burak Kocuk
Summary: This paper proposes a method to solve the UC and OPF problems in short-term power system planning simultaneously using AC power flow equations. Two different algorithms are developed for smaller instances to obtain high-quality feasible solutions. For larger instances, a Lagrangian decomposition based approach is developed to achieve promising results.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Cormac O'Malley, Patrick de Mars, Luis Badesa, Goran Strbac
Summary: Decarbonisation is driving the growth of renewable power generation and increasing uncertainty in power plant scheduling. This paper compares traditional mathematical programming methods with emerging reinforcement learning methods, finding that the former is more reliable and scalable with lower costs. However, the strength of reinforcement learning lies in its ability to produce instant solutions.
Article
Engineering, Electrical & Electronic
Yonghong Chen, Feng Pan, Jesse Holzer, Edward Rothberg, Yaming Ma, Arun Veeramany
Summary: This paper introduces a market economics based neighborhood search and polishing algorithm to solve security constrained unit commitment (SCUC) problem. The algorithm shows significant performance improvements compared to a MIP solver alone when tested on a large set of cases from Midcontinent Independent System Operator (MISO) on a high performance computing cluster with the concurrent neighborhood search and the polishing algorithm.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Industrial
Tiago Tiburcio da Silva, Antonio Augusto Chaves, Horacio Hideki Yanasse
Summary: A new multicommodity flow mathematical model for the Job Sequencing and Tool Switching Problem (SSP) is proposed, with computational tests showing better performance in execution time and solving optimization problems compared to existing literature models.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Operations Research & Management Science
Andre R. S. Amaral
Summary: This paper introduces a new mixed-integer programming model based on a linear extension of a partial order for the double row layout problem. By reformulating this model, stronger results are obtained. Computational experiments show that the proposed models achieve optimal solutions faster than previously published models.
OPTIMIZATION LETTERS
(2021)
Article
Energy & Fuels
Menghan Zhang, Zhifang Yang, Wei Lin, Juan Yu, Wei Dai, Ershun Du
Summary: This paper proposes a new approach to address the unit commitment problem with high time resolution by identifying representative scheduling points and reducing the optimization size, improving computational speed and providing feasible solutions.
Article
Computer Science, Artificial Intelligence
Baosu Guo, Jinrui Li, Yu Zhang, Fenghe Wu, Qingjin Peng
Summary: This paper proposes a vector superposition NFP method to improve the solution efficiency of 2D irregular layout problems with complex contours. An improved mixed integer programming model based on the NFP is built, and a hybrid algorithm based on the NFP and MIP is proposed to solve the problem. Comparing with existing methods, the proposed method shortens the search time and improves the material utilization.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Alberto Santini, Ana Viana, Xenia Klimentova, Joao Pedro Pedroso
Summary: We studied a variant of the Probabilistic Travelling Salesman Problem where retailers outsource last-mile deliveries to customers and proposed Machine Learning and Monte Carlo simulation methods to approximate the objective function. The results show that these approaches work well on small size instances and provide managerial insights on the economic and environmental benefits of crowdsourcing to customers.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Management
Margarida Carvalho, Andrea Lodi, Joao P. Pedroso
Summary: In this paper, the concept of integer programming games (IPG) and its application in real-world problems are introduced. A general algorithmic approach is developed to determine the equilibrium solution of the game by computing Nash equilibria and utilizing sufficient conditions. The performance of the method is validated through computational experiments on various games.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Christophe Rapine, Joao Pedro Pedroso, Ayse Akbalik
Summary: The article focuses on a variant of the two-dimensional knapsack problem that considers the possibility of splitting items and requires stable stacking. By proving the NP-hardness of the problem and establishing dominance properties of canonical packings, polynomial time algorithms and pseudo-polynomial time algorithms are proposed to address this problem.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Economics
Andre Gustavo Dos Santos, Ana Viana, Joao Pedro Pedroso
Summary: This article proposes a new approach for the last-mile delivery problem by using parcel lockers as collecting points and transshipment nodes, and incorporating occasional couriers for delivery. The use of shared locker facilities and occasional couriers enhances the usage of storage capacity and potentially reduces carbon footprint. The study presents a mixed-integer linear programming formulation to optimize delivery options and evaluates the impact of occasional couriers' availability and locker capacities through computational experiments.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Computer Science, Interdisciplinary Applications
Miguel Barbosa, Joao Pedro Pedroso, Ana Viana
Summary: A recent innovation in last-mile delivery is considering the possibility of using crowdsourced couriers for delivering goods. This paper focuses on in-store customers delivering goods ordered by online customers on their way home. Logistic regression is used to model the willingness of crowd agents to undertake a delivery, and a compensation scheme is developed based on the current plan for the professional fleet's routes and the couriers' probabilities of acceptance, using a direct search algorithm to minimize expected cost.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Management
Xenia Klimentova, Peter Biro, Ana Viana, Virginia Costa, Joao Pedro Pedroso
Summary: Kidney exchange programs provide an alternative option for end-stage kidney disease patients who have incompatible living donors. This study proposes four novel integer programming models to find maximum cardinality stable exchanges in scenarios where recipients have preference orders over potential donors. Computational experiments show that cycle-edge and position-indexed formulations outperform the other formulations, and targeting strongly stable solutions negatively impacts the number of transplants.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Marco Silva, Joao Pedro Pedroso, Ana Viana
Summary: This study investigates a logistics delivery problem in a business model where a company has a fleet of vehicles and drivers as well as occasional drivers (ODs). The study proposes a novel deep reinforcement learning approach and compares it with other optimization methods under uncertainty.
EURO JOURNAL ON TRANSPORTATION AND LOGISTICS
(2023)
Article
Management
Marco Silva, Jodo Pedro Pedroso, Ana Viana
Summary: In this study, we examine the use of occasional drivers in last-mile delivery for small companies. The problem is modeled as a variant of the stochastic capacitated vehicle routing problem. Our approach is data-driven and takes into account the uncertainty in both customer orders and the availability of occasional drivers. We optimize the problem considering a worst-case joint distribution and use a strategic planning perspective. We propose an extended formulation and implement a branch-price-and-cut algorithm to solve it. We also develop a heuristic approximation for larger instances of the problem. Computational experiments are conducted to analyze the solution and performance of the algorithms implemented.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Peter Biro, Flip Klijn, Xenia Klimentova, Ana Viana
Summary: In the housing market model of Shapley and Scarf, the unique strong core allocation respects improvement for both strict and weak preferences. This result is extended to various scenarios, and examples are provided to show exceptions.
MATHEMATICS OF OPERATIONS RESEARCH
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Joao Dionisio, Davi dos Santos, Joao Pedro Pedroso
Summary: Sea exploration is crucial for countries with ocean control, as it enables the potential exploitation of seafloor resources. The sea exploration problem involves scheduling ship expeditions to collect information on seafloor resources. This problem shares similarities with orienteering and navigation problems, but differs in terms of correlated resource scores and freely chosen vertex locations.
MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I
(2022)
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
