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检索条件"主题词=Mixed-integer linear programming"

共 2279 条记录，以下是651-660 订阅

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Including Dynamic Security Constraints in Isolated Power Systems Unit Commitment/Economic Dispatch: a Machine Learning-based Approach

Including Dynamic Security Constraints in Isolated Power Sys...

引用

IEEE Belgrade PowerTech Conference

作者： de Sousa, Rui Pinto Moreira, Carlos Carvalho, Leonel Matos, Manuel INESC TEC Porto Portugal Univ Porto Fac Engn Porto Portugal

ISBN: (纸本)9781665487788

Isolated power systems with high shares of renewables can require additional inertia as a complementary resource to assure the system operation in a dynamic safe region. This paper presents a methodology for the day-ahead Unit Commitment/ Economic Dispatch (UC/ED) for low-inertia power systems including dynamic security constraints for key frequency indicators computed by an Artificial Neural-Network (ANN)-supported Dynamic Security Assessment (DSA) tool. The ANN-supported DSA tool infers the system dynamic performance with respect to key frequency indicators following critical disturbances and computes the additional synchronous inertia that brings the system back to its dynamic security region, by dispatching Synchronous Condensers (SC) if required. The results demonstrate the effectiveness of the methodology proposed by enabling the system operation within safe frequency margins for a set of high relevance fault type contingencies while minimizing the additional costs associated with the SC operation.

关键词： Dynamic stability unit commitment mixed-integer linear programming synchronous inertia

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Optimal Energy Scheduling of Flexible Industrial Prosumers via Reinforcement Learning

Optimal Energy Scheduling of Flexible Industrial Prosumers v...

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IEEE Belgrade PowerTech Conference

作者： van den Bovenkamp, Nick Giraldo, Juan S. Duque, Edgar Mauricio Salazar Vergara, Pedro P. Konstantinou, Charalambos Palensky, Peter Delft Univ Technol Intelligent Elect Power Grids EEMCS Delft Netherlands Netherlands Org Appl Sci Res TNO Energy Transit Studies Grp Delft Netherlands Eindhoven Univ Technol Elect Energy Syst EES Eindhoven Netherlands Sunrock Investments BV Innovat Dept Amsterdam Netherlands King Abdullah Univ Sci & Technol KAUST CEMSE Div Thuwal Saudi Arabia

ISBN: (纸本)9781665487788

This paper introduces an energy management system (EMS) aiming to minimize electricity operating costs using reinforcement learning (RL) with a linear function approximation. The proposed EMS uses a Q-learning with tile coding (QLTC) algorithm and is compared to a deterministic mixed-integer linear programming (MILP) with perfect forecast information. The comparison is performed using a case study on an industrial manufacturing company in the Netherlands, considering measured electricity consumption, PV generation, and wholesale electricity prices during one week of operation. The results show that the proposed EMS can adjust the prosumer's power consumption considering favorable prices. The electricity costs obtained using the QLTC algorithm are 99% close to those obtained with the MILP model. Furthermore, the results demonstrate that the QLTC model can generalize on previously learned control policies even in the case of missing data and can deploy actions 80% near to the MILP's optimal solution.

关键词： Q-learning tile coding energy management system mixed-integer linear programming

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Constraint programming for the Robust Two-Machine Flow-Shop Scheduling Problem with Budgeted Uncertainty 20th

Constraint Programming for the Robust Two-Machine Flow-Shop ...

引用

20th International Conference on the Integration of Constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Juvin, Carla Houssin, Laurent Lopez, Pierre Univ Toulouse CNRS LAAS CNRS Toulouse France ISAE SUPAERO Toulouse France

ISBN: (纸本)9783031332708;9783031332715

This paper addresses the robust two-machine permutation flow-shop scheduling problem considering non-deterministic operation processing times associated with an uncertainty budget. The objective is to minimize the makespan of the schedule. Exact solution methods incorporated within the framework of a two-stage robust optimization are proposed to solve the problem. We first prove that under particular conditions the robust two-machine permutation flow-shop scheduling problem can be solved in polynomial time by the well-known Johnson's algorithm usually dedicated to the deterministic version. Then we tackle the general problem, for which we propose a column and constraint generation algorithm. We compare two versions of the algorithm. In the first version, a mixed-integer linear programming formulation is used for the master problem. In the second version, we use a constraint programming model for the master problem. To the best of our knowledge, the use of constraint programming for a master problem in a two-stage robust optimization problem is innovative. The experimental results show the very good performance of the method based on the constraint programming formulation. We also notice that Johnson's algorithm is surprisingly efficient for the robust version of the general problem.

关键词： Flow-Shop Scheduling Robust Optimization Uncertainty Budget mixed-integer linear programming Constraint programming

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Strategic Offering of a Wind Power Producer in Energy and Green Certificate Markets: A Stochastic Bilevel Approach 7

Strategic Offering of a Wind Power Producer in Energy and Gr...

引用

7th International Conference on Power and Energy Applications, ICPEA 2024

作者： Li, Jie Wang, Xiuli Zhou, Xiaoxin School of Electrical Engineering Xi'an Jiaotong University Xi'an China China Electric Power Research Institute National Key Laboratory of Power Grid Safety Beijing China

ISBN: (纸本)9798350356113

With the high penetration of renewable energy and the execution of renewable portfolio standards, it becomes urgent to analyze the behavior of a wind power producer (WPP) in energy and green certificate markets. To this end, we propose a strategic offering model for a WPP, aiming to analyze the impact of exercising market power on market clearing results and social welfare. Afterwards, the model is transformed into stochastic mathematical programming with equilibrium constraints (MPEC) and eventually mixed integer linear programming (MILP), which can be solved by off-the-shelf solvers. Finally, case studies are carried out on a small test system, illustrating that the market clearing price might increase compared with the perfect competition situation, and the expected profit of WPP increases at the expense of market efficiency. Besides, we analyse the impact of line congestion on the revenue of WPP. © 2024 IEEE.

关键词： mixed-integer linear programming

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Computing Inefficiency of Service Networks under Random Failures

Computing Inefficiency of Service Networks under Random Fail...

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IISE Annual Conference and Expo 2024

作者： Chandra, Ashish Department of Management College of Business Illinois State University NormalIL61761 United States

ISBN: (纸本)9781713877851

In this work, our focus is directed towards the examination of service networks in the context of random failures. Specifically, when presented with a service network graph and a parameter value denoted as f ∈ N, we presuppose the existence of an underlying probability distribution across the entirety of f-simultaneous links failure scenarios. Our primary objective lies in the computation of the probability associated with scenarios wherein the network utilization exceeds unity. The derived probability serves as a metric for assessing the inefficiency inherent in the service network. It is crucial to note that this computational task is classified as NP-Hard, given that determining even a single failure scenario resulting in network inefficiency falls within the NP-Hard complexity class. To quantify the network inefficiency, we propose an approach that leverages recently developed techniques from the field of optimization under uncertainty, and integer programming. Furthermore, we harness advancements in optimization solvers, in particular the Gurobi solver. Another outcome of our methodology is the ability to identify failure scenarios that render service networks inefficient, thereby causing network utilization to exceed one. This foreknowledge serves as a valuable tool in proactively designing more resilient networks. We also provide computational results to substantiate our findings. © IISE Annual Conference and Expo *** rights reserved.

关键词： mixed-integer linear programming

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A Combination of CMA-ES with Probability Distributions of integer Variables for mixed-integer Black-Box Optimization

A Combination of CMA-ES with Probability Distributions of In...

引用

2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Nguyen, Duc Manh Department of Mathematics and Informatics Hanoi National University of Education Hanoi Viet Nam

ISBN: (纸本)9798400704956

In this paper, we propose a method for efficiently solving the mixed-integer black-box optimization problem by utilizing the probability distribution models of integer variables in the CMA-ES algorithm. Firstly, some elite points among the generated ones during the evolution process of the CMA-ES algorithm are collected after some consecutive iterations to successively build the probability distribution model of integer variables. Then, the model is partially used to generate the values for the integer variables of candidate solutions in some next iterations. The numerical experiments on the MI-BBO benchmark problems will show that the probability distribution models of integer variables can guide the CMA-ES better to the optimal solution of the problem, as well as demonstrate the efficiency of the proposed method. © 2024 held by the owner/author(s).

关键词： mixed-integer linear programming

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Consideration of round-trip electric car-sharing in residential energy system modeling

Consideration of round-trip electric car-sharing in resident...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Achatz, Julian Mohapatra, Anurag Hamacher, Thomas Germany

ISBN: (纸本)9789531842976

This paper presents a residential, round-trip, mixed ownership, electric car-sharing scheme with an optimized charging schedule, expressed as a mixed integer linear programming model. Representing the given travel demand as a graph, a mixed (shared and owned cars) ownership fleet configuration, with different trip fulfillment possibilities, is determined using maximal cliques. Next, a car-to-trip allocation model for feasible trip plans, with considerations for equal car utilization and charging price, is used to generate charging profiles for the fleet. The model and the outputs can be variously integrated into existing energy system modeling frameworks. A case study, using data from a test building with a residential car-sharing fleet in Munich, demonstrates the potential of the proposed models to derive meaningful operational insights for fleet and energy system planners. 92% of the recorded trips at the test building could have been feasibly accomplished with only 60% of the available cars. © 2024 IEEE.

关键词： mixed-integer linear programming

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Optimal Location and Size of Inverter-Based Distributed Generation Considering Power Loss Reduction, Voltage Profile Improvement and Power Quality Preservation 11

Optimal Location and Size of Inverter-Based Distributed Gene...

引用

11th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2024

作者： Rakočević, Stevan Ćalasan, Martin Vujošević, Snežana University of Montenegro Faculty of Electrical Engineering Podgorica Montenegro

ISBN: (纸本)9798350386998

This paper addresses optimal allocation and sizing of inverter-based Distributed Generation (DG) with the aim of reducing power loss, enhancing voltage profile and preserving power quality of radial distribution network. Problem is formulated as mixed-integer Non-linear programming (MINLP), and is solved using BONMIN solver in General Algebraic Modeling Systems (GAMS) environment. The proposed approach is evaluated on IEEE 69-bus test system, considering non-sinusoidal operating condition. Both single-objective and multi-objective optimization of loss and voltage deviation is considered, while analyzing impact of inverter-based DGs on Total Harmonic Distortion (THD) © 2024 IEEE.

关键词： mixed-integer linear programming

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Mathematical Models for Finding the Shortest Cycle to Visit a Given Number of Vertices from the Graph Clusters 3

Mathematical Models for Finding the Shortest Cycle to Visit ...

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3rd International Conference on Problems of Logistics, Management and Operation in the East-West Transport Corridor, PLMO 2024

作者： Stetsyuk, Petro Korablov, Mykola Stoian, Oleksandr Hubernator, Oleh V.M. Glushkov Institute of Cybernetics of the Nas of Ukraine Department of Nonsmooth Optimization Methods Kyiv Ukraine Taras Shevchenko National University of Kyiv Faculty of Radiophysics Electronics and Computer Systems Kyiv Ukraine

ISBN: (纸本)9798350353099

Travelling Salesman Problem (TSP) is known for its numerous modifications and applications in different areas. Introduced in this paper are the problem of finding the shortest cycle through a given number of vertices from the graph clusters and two mixed integer linear programming (MILP) models for solving the problem. The first MILP model is based on the generalized version of Miller, Tucker and Zemlin constraints for standard TSP. The second model is based on the generalized version of Gavish and Graves constraints for standard TSP. Necessity and sufficiency of models constraints are proved. Results of a computational experiment are presented. © 2024 IEEE.

关键词： mixed-integer linear programming

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Improved Spectral Clustering for Distributed Resources 11

Improved Spectral Clustering for Distributed Resources

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11th China International Conference on Electricity Distribution, CICED 2024

作者： Wang, Liwen Lv, Leiyan Ma, Xiang Ling, Kaiyuan Xu, Peng Liu, Jiantao China Electric Power Research Institute Co. Ltd Nanjing China Jinhua Power Supply Company State Grid Corporation of China Jinhua China

ISBN: (纸本)9798350368345

In addressing the issue of exponential increase in solution time with the growing number of simulations when using mixed-integer linear programming methods to solve stochastic models based on Monte Carlo simulation, this paper proposes employing spectral clustering to determine the best-quality classification scheme. By using the spectral clustering method on random samples generated by Monte Carlo simulation, the optimal classification scheme is identified to group similar stochastic scenarios together. Finally, by selecting the center of each class as a representative, the number of scenarios to be considered is reduced, facilitating the solution of problems such as whole-scenario modeling and lowering the difficulty of solving. Experimental results demonstrate that the spectral clustering method proposed in this paper exhibits the best performance among some commonly used methods. © 2024 IEEE.

关键词： mixed-integer linear programming

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