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

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Multi-time Scale Probabilistic Aggregation Technology of Large-scale Electric Vehicle Energy Storage Batteries Participating in Grid Demand Response

Multi-time Scale Probabilistic Aggregation Technology of Lar...

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IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Liming Liu Liping Gao Yanjie She Chunqi He Jinglei Ren Jiang Li School of Metallurgy Northeastern University Shenyang China Luoyang Power Supply Company Henan Provincial Power Company Luoyang China School of Electric Power Engineering Shanghai University of Electric Power Shanghai China

ISBN: (数字)9798331529277

ISBN: (纸本)9798331529307

With the rapid development of electric vehicles (EVs), aggregators can use reliable technology to aggregate widely distributed lithium batteries, enabling deterministic centralized output and effectively participating in multi-time scale grid demand response, thereby achieving significant economic benefits. This paper analyzes demand response across different time scales, such as minutes and hours, and studies the multi-time matching technology of probabilistic profiling techniques. The SOM neural network clustering method is used to aggregate EV loads, and aggregators control the unified charging and discharging behavior of EV batteries. A mixed-integer linear programming optimization algorithm is employed to allocate the aggregated battery resources, ensuring optimal energy distribution. Finally, simulations based on typical daily EV random operation scenarios show an improvement in the revenue and operational satisfaction of EV aggregators, validating the effectiveness of the aggregation technology.

关键词： Economics Aggregates Neural networks Transportation Probabilistic logic Electric vehicles Lithium batteries Demand response mixed integer linear programming Optimization

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Stochastic Optimization of Energy Resources in Smart Homes

Stochastic Optimization of Energy Resources in Smart Homes

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IEEE ANDESCON

作者： Jéssica Alice A. Silva Derian C. Tairo Guilherme Souto Chagas Marcos J. Rider School of Electrical and Computer Engineering (FEEC) Universidade Estadual de Campinas (UNICAMP) Brazil

ISBN: (数字)9798350355284

ISBN: (纸本)9798350355291

Managing energy resources effectively in smart homes presents a multifaceted challenge due to the dynamic nature of renewable energy sources, unpredictable load profiles, and the integration of electric vehicles. This paper addresses this challenge by proposing a mixed-integer linear programming (MILP) model for efficient energy management. The model integrates battery energy storage systems (BESS), photovoltaic (PV) generation, and electric vehicle (EV) charging, aiming to address the complexities of energy resource coordination. We introduce a stochastic approach to account for uncertainties associated with PV generation, load profiles, and EV charging while also considering the probability of network outages. The proposed MILP model offers a systematic solution to the challenges posed by energy management in smart homes; by optimizing energy utilization and cost reduction, our approach enables efficient coordination of multiple energy resources. The application of the model in a smart home test scenario demonstrated that the BESS is employed to minimize operational expenses by charging it with excess PV generation and discharging it during peak periods. Finally, our approach offers a practical and scalable solution for sustainable energy usage, contributing to the advancement of smart home technology.

关键词： Photovoltaic systems Costs Uncertainty Energy resources Stochastic processes Smart homes Electric vehicle charging mixed integer linear programming Optimization Load modeling

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Computation of competitive market equilibrium in hydrothermal power systems with cascaded reservoirs

Computation of competitive market equilibrium in hydrotherma...

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Power Tech Conference

作者： A.R.M. Guerra J.L.M. Ramos Department of Electrical Engineering University of Seville Seville Spain

In a competitive electricity market, generation companies have to maximize their benefits selecting the best strategy; therefore it is convenient to previously know the resulting spot prices. This paper presents a model to determine market clearing prices and hourly generation levels of each participant over a 24-hour period, including hydrothermal constraints. The optimal competitive market equilibrium problem is formulated as a large-scale mixed integer linear programming algorithm and is solved by using an optimization package. The model incorporates the following elements: thermal plants (maximum up and down ramp), hydro units, hydro systems (cascaded reservoirs, spillway flow, generator I/O characteristic), and inelastic demand. Numerical tests of a day ahead market are presented.

关键词： Power systems Reservoirs Power system modeling Electricity supply industry Power generation Large-scale systems mixed integer linear programming Packaging Character generation Testing

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Planning and Dispatch of Battery Energy Storage in Microgrid for Cycle-life Improvement

Planning and Dispatch of Battery Energy Storage in Microgrid...

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International Conference on Power Electronic Drives

作者： Tripti Gangwar Narayana Prasad Padhy Premalata Jena Department of Electrical Engineering Indian Institute of Technology Roorkee India

Over the past decade, there has been an expansion of distribution networks to smart and intelligent microgrids. Microgrids have stood out over the past few years due to the advantage of reliability and resiliency improvement. Also, to establish the cost-effective operation of microgrids, optimal planning of energy storage is noteworthy. Of all energy storage systems, battery energy storage systems (BESS) are chosen as the most advantageous one for a microgrid (MG) operation. However, planning a BESS should comprehensively include the cycle-life and cost-benefit analysis. The present work considers multi-energy sources and loads comprising a MG to allocate appropriate BESS sizes. A mathematical model is contemplated for both islanded and grid-connected modes of the MGs. The model is formulated as mixed-integer linear programming (MILP) problem and solved using GUROBI. A dispatch model of BESS is also included to enlarge the battery lifetime. Furthermore, a mix of BESS technologies is proposed and validated in a MG test case using YALMIP interfaced with MATLAB.

关键词： Microgrids Mathematical models Power electronics Planning Batteries mixed integer linear programming Reliability

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Study on the location of distribution center: a genetic algorithm combining mechanism of simulated annealing

Study on the location of distribution center: a genetic algo...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Guang-Bin Cui Yi-Jun Li School of Management Harbin Institute of Technology China

ISBN: (纸本)0780384032

The location of distribution center (DC) is one of the most important decision issues for logistics managers. In this paper, 0-1 mixed integer linear programming model of location of distribution center of two-stage logistics chain network is given. The design tasks of this problem involve the choice of distribution center to be opened and the optimal assignment of product flow between suppliers and customers via distribution centers to meet the demand with minimum cost As the solution method, a genetic algorithm combining mechanism of simulated annealing that is proved effective in dealing with the NP-hard problem is proposed.

关键词： Genetic algorithms Simulated annealing Logistics Transportation mixed integer linear programming Technology management Cost function Art Supply chains Production

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Distributed Differentially Private Control Synthesis for Multi-Agent Systems with Metric Temporal Logic Specifications

Distributed Differentially Private Control Synthesis for Mul...

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American Control Conference (ACC)

作者： Nasim Baharisangari Narendhiran Saravanane Zhe Xu School for Engineering of Matter Transport and Energy Arizona State University Tempe AZ

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We propose a distributed differentially private receding horizon control (RHC) approach for multi-agent systems (MAS) with metric temporal logic (MTL) specifications. In the MAS considered in this paper, each agent privatizes its sensitive information from other agents using a differential privacy mechanism. In other words, each agent adds privacy noise (e.g., Gaussian noise) to its output to maintain its privacy. We define two types of MTL specifications for the MAS: agent-level specifications and system-level specifications. Agents should collaborate to satisfy the system-level MTL specifications while each agent must satisfy its own agentlevel MTL specifications at the same time. In the proposed distributed RHC approach, each agent communicates with its neighboring agents to acquire their estimate of the system-level trajectory and updates its estimate of the system-level trajectory. Then, each agent synthesizes its own control inputs such that the system-level specifications are satisfied with a probabilistic guarantee while the agent-level specifications are also satisfied with a deterministic guarantee. In the proposed optimization formulation of RHC, we directly incorporate Kalman filter equations to calculate the system-level trajectory estimates. We use mixed-integer linear programming (MILP) to encode the MTL specifications as optimization constraints. Finally, we implement the proposed distributed RHC approach in two scenarios.

关键词： Privacy System dynamics Probabilistic logic Robustness Mathematical models Trajectory mixed integer linear programming

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A rational multiparty information exchange model using extensive games

A rational multiparty information exchange model using exten...

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International Conference on Military Communications and Information Systems (ICMCIS)

作者： Alberto Campos Viet Pham Institute for Research in Technology Comillas Pontifical University Madrid Spain Information Security Group University of London London England

ISBN: (纸本)9781509004720

It is well known that excessive intelligence is mandatory in military procedures, in companies to know about competitors, as well as in markets to decide where to invest in. However, this information is not always fully reliable since it might be given by others with conflicting interests. Consequently, there is no guarantee that the supplied information has not been maliciously crafted to produce negative outputs to the receiving entity. For a formal treatment, a way to represent this problem is via Multi-Party Information Exchange (MPIE) model. Applying extensive games, we propose a MPIE when the information is relayed in non-secret channels. This is a refinement of a previous MPIE by rejecting solutions arisen from empty threats, through finding perfect equilibria in sub-games. The resolution to find such perfect equilibria is based on executing an algorithm that solves mixed integer linear programming (MILP) models. The case studies prove that empty threats are deleted and that a large number of players can be efficiently solved using the proposed algorithm.

关键词： Games Peer-to-peer computing Information exchange Reliability Companies Algorithm design and analysis mixed integer linear programming

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A mixed capability-based and optimization methodology for human-robot task allocation and scheduling

A mixed capability-based and optimization methodology for hu...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Andrea Monguzzi Mahmoud Badawi Andrea Maria Zanchettin Paolo Rocco Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milano Italy

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

In this work, we address two crucial issues that arise in the design of a human-robot collaborative station for the assembly of products: the optimal task allocation and the scheduling problem. We propose an offline method to solve in series the two mentioned issues, considering a static allocation and taking into account several features such as the minimization of postural discomfort, operation processing times, idle times and hence the total cycle time. Our methodology consists of a mixed approach that combines a capability-based method, where the agents' capabilities are tested against a list of predefined criteria, with optimization. In particular, we formulate a modified version of the Hungarian Algorithm to solve also unbalanced assignment problems, where the number of tasks is different from the number of agents. The scheduling policy is obtained by means of a mixed integer linear programming (MILP) formulation, with a multi-objective optimization. Moreover, the concepts of operation, assembly tree and precedence graph are formalized, since they represent the inputs to our method, together with the information on the workstation layout and on the selected kind of robot. Finally, the proposed solution is applied to a case study to define the optimal task allocation and scheduling for two different workstation layouts: the results are compared and the best layout is accordingly selected.

关键词： Layout Collaboration Minimization Workstations mixed integer linear programming Resource management Task analysis

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Resolution of a WDM network design problem using a decomposition approach and a size reduction method

Resolution of a WDM network design problem using a decomposi...

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European Conference on Universal Multiservice Networks (ECUMN)

作者： J. Kuri N. Puech M. Gagnaire Computer Science and Networks Department École Nationale Supérieure des Télécommunications Paris France I U T Université Paris 5 Paris France

Multicommodity flow models have been proposed in the literature to formulate different network design problems as mixed integer linear programming (MILP) problems. The formulations axe important because there are algorithms that find the optimal solution to these problems. However, MILP problems are NP-hard, which makes the solution of design problem instances of non trivial size numerically intractable. In this article we propose a method to tackle the inherent complexity of a WDM network design problem formulated as a multicommodity flow problem. The method allows us to solve WDM network design problems of medium size. We first decompose the design problem into two subproblems that can be solved separately. Multicommodity flow models are used to formulate each subproblem as a MILP problem. We then prune the variables' space associated to each subproblem by eliminating from the formulation useless variables. The solution to the design problem is obtained by solving the subproblems sequentially. To take into account the dependency between subproblems, we introduce a feedback mechanism to exchange information between the algorithms that solve the subproblems.

关键词： WDM networks Optical switches Optical packet switching Telecommunication traffic Cost function Availability Wavelength division multiplexing Optical fiber networks Computer science mixed integer linear programming

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A Hybrid Discrete Jaya Algorithm Based on Gene Expression programming for Heterogeneous Multi-Satellites Cooperative Observation

A Hybrid Discrete Jaya Algorithm Based on Gene Expression Pr...

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Artificial Intelligence and Automation Control (AIAC), International Conference on

作者： Junxiang Yang Lei He College of Systems Engineering National University of Defense Technology Changsha China

ISBN: (数字)9798331529147

ISBN: (纸本)9798331529154

In disaster observation, disasters with different characteristics have different degrees of demand for the selection of observation satellites, which directly affects the imaging quality, specifically involving the matching problem between mission types and satellite types. In this paper, for this Heterogeneous multi-Agile Earth Observation Satellites Scheduling Problem (HAEOSSP), a mixed integer linear programming model is established, and the time-dependent transition time and task matching are taken into account. To solve HAEOSSP, a Hybrid Discrete Jaya algorithm based on Gene Expression programming (HD-Jaya-GEP) method is designed to evolve task assignment rule. Coded with GEP, the Jaya algorithm is discretized by a neighborhood-based strategy, while the single-satellite task scheduling is solved by a mature meta-heuristic algorithm. Finally, simulation experiments are performed to evaluate the generalization of HD-Jaya-GEP, which validates the effectiveness and capability.

关键词： Earth Satellites Disasters Metaheuristics Imaging programming Scheduling mixed integer linear programming Gene expression Standards

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