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

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Job Shop Scheduling Under Time-of-Use Electricity Prices

Job Shop Scheduling Under Time-of-Use Electricity Prices

引用

International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Jingwei Dai Yaowen Yu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Job shop scheduling is an important problem in the operations of manufacturing systems and has great potential for improving electricity efficiency. This paper studies an energy-aware job shop scheduling problem that aims to minimize the total energy cost and total weighted tardiness by selecting an optimal job schedule, considering operation and other constraints. To efficiently model operation constraints and to consider different machine types, a new set of linear integer constraints is developed. The energy-aware job shop scheduling problem considering time-of-use (TOU) electricity prices is then formulated as a mixed-integer linear programming (MILP) problem and solved using the branch-and-cut method. Numerical results tested against three examples demonstrate the computational efficiency and solution quality of our method.

关键词： Schedules Electric potential Job shop scheduling Costs Electricity Computational modeling Numerical models mixed integer linear programming Robots Manufacturing systems

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Optimisation of the operation of an integrated energy system including electric vehicles with carbon trading

Optimisation of the operation of an integrated energy system...

引用

Energy, Power and Electrical Technology (ICEPET), International Conference on

作者： Yue Cheng Honghe Ma School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

In this paper, an integrated energy system IES (IES) is constructed from the perspective of source, network, load and storage by combining a variety of capacity, storage and energy conversion devices. Considering electric vehicle (EV) as a potential demand-side response tool, EV is connected to the IES, and an IES operation optimization model with EV is established. In this paper, for the IES operation optimization problem with EVs, we consider EVs as a kind of demand-side response by combining with the time-sharing tariff mechanism, which guides EV owners to actively participate in the scheduling of the integrated energy system. Finally, in order to actively cooperate with the "dual-carbon" goal promoted by the state, a reward-punishment stepped carbon trading model is proposed, which can be optimized on the basis of the carbon trading model by introducing a reward-punishment mechanism. The mixed integer linear programming analysis is carried out with the help of Cplex solver by using the Yalmip toolbox in Matlab simulation software. linear programming analysis , the results show that the results show that EVs participate in the system scheduling as an incentive-based demand response, which not only reduces the daily operating cost of the IES, but also reduces the charging cost of the EVs, and furthermore, the introduction of carbon trading in the system not only reduces the carbon emissions of the system, reduces the operating cost of the system, but also takes into account the environmental friendliness and the economy of the system operation.

关键词： Costs Systems operation Emissions trading Energy conversion Software Demand response mixed integer linear programming

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Demand & Cost Driven Transportation Planning for Multi-Product Logistics

Demand & Cost Driven Transportation Planning for Multi-Produ...

引用

Intelligent Systems and Machine Learning Conference (ISML)

作者： Shezal Gangwar Rohan Kumar Rajeev Ranjan Data Science & Insights Genpact Bengaluru India

ISBN: (数字)9798350343878

ISBN: (纸本)9798350343885

This research article provides a comprehensive review of the multidirectional transportation problem, which is a more realistic representation of transportation flows in supply chains. While traditional supply chain flows are typically unidirectional, with supplier nodes and demander nodes, resulting in a forward flow of materials/goods from higher tier suppliers (upstream) to the end-consumer (downstream). The multidirectional transportation problem highlights the fact that each location within the network can act as both a supplier and a demander at a given time. Therefore, there is no such upstream to downstream flow. According to the demand of each location, all other locations can supply materials/goods to the deficit location. By acknowledging the locations, it can serve both as suppliers and demanders, the multidirectional transportation problem captures the complexities and interdependencies within supply chains more accurately. After that, a mixed-integer linear programming (MILP) model is applied to find the optimal solutions for the distribution decisions. Additionally, the paper includes a comparative analysis of various solvers to evaluate the performance of the optimization engine. This analysis provides a comprehensive understanding of the strengths and weaknesses of different solvers, helping to identify the most suitable approach for solving multidirectional transportation problems.

关键词： Costs Reviews Supply chains Transportation Machine learning Safety Planning mixed integer linear programming Intelligent systems Optimization

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Online Coordination of BESS and Thermostatically Control Loads for Shared Energy Optimization in Energy Communities

Online Coordination of BESS and Thermostatically Control Loa...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Jerónimo J. Moré Diego Deplano Alessandro Pilloni Alessandro Pisano Mauro Franceschelli UNLP- CONICET Instituto LEICI Fac. de Ingeníera Argentina DIEE University of Cagliari Cagliari Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This paper introduces a mixed-integer linear programming (MILP) optimization scheme aimed at cost optimization in Energy Communities through the coordination of prosumers’ Battery Energy Storage Systems (BESS) and Thermostatically Controlled Loads (TCLs). Inspired by recent guidelines from the Italian Gestore dei Mercati Energetici, we first introduce the concept of shared energy. Shared energy is defined as the minimum value, over a specified time window, between the renewable energy injected into the grid and the total energy consumed by the community. Subsequently, we formulate the coordination problem as a MILP optimization, where the degrees of freedom include the TCLs’ status and the BESS’s State-of-Charge. The effectiveness and performance of the proposed formulation are evaluated through numerical simulations, demonstrating the advantages of the coordinated scheme over uncoordinated ones.

关键词： Renewable energy sources Costs Computer aided software engineering Automation Battery energy storage system Numerical simulation Control systems mixed integer linear programming Optimization Guidelines

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Bi-Level Optimization for Energy Management of Networked Microgrid

Bi-Level Optimization for Energy Management of Networked Mic...

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Sustainable Energy and Future Electric Transportation (SEFET), International Conference on

作者： Arpan Bhowmick Altaf Q. H. Badar Dept. Electrical Engineering NIT Warangal Warangal India

ISBN: (数字)9798350383997

ISBN: (纸本)9798350384000

A Microgrid (MG) is formed by a collection of interconnected loads and distributed energy resources, operating collectively and under control as a distinct entity in relation to the grid. A Networked Microgrid (NMG) comprises of interconnected MGs, facilitating sharing of resources, load balancing, and coordinated operation. NMG may connect to the external power grid for energy import/ export and enhancing overall efficiency. This paper proposes an energy management scheme in an NMG. The proposed scheme consists of two levels. At lower-level, Microgrid Energy Management Systems (MG-EMS) calculate the surplus and shortage of power, generation of Dispatchable Generation (DG), charging and discharging of Electric Vehicle (EV), Battery Energy Storage System (BESS) of individual MGs. At upper-level, Central Energy Management System (CEMS) decides the amount of energy traded between the MGs and between MG and the utility grid with the help of information given by MG-EMS. The NMG considered in this research has three MGs and each MG has EV as a part of it. mixed-integer linear programming (MILP) has been deployed to address this problem. Microsoft Visual Studio is used to implement MILP.

关键词： Visualization Costs Simulation Transportation Microgrids Load management Electric vehicles mixed integer linear programming Energy management systems Optimization

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Dynamic Optimization of CO2 Emissions and Electricity Costs in Smart Factories

Dynamic Optimization of CO2 Emissions and Electricity Costs ...

引用

Electrical and Computer Engineering Researches (ICECER), International Conference on

作者： Seyed Davood Mousavi Martin Griese Thomas Schulte Institute for Energy Research (iFE) Ostwestfalen-Lippe University of Applied Sciences and Arts Lemgo Germany

ISBN: (数字)9798331539733

ISBN: (纸本)9798331539740

This paper presents a robust methodology for optimizing CO 2 emissions and electricity costs in industrial applications, with the aim of developing a flexible and dynamic energy management strategy that balances sustainability and cost-efficiency. Addressing the growing need for sustainable and economically viable energy solutions amidst the global urgency of climate change mitigation, the proposed approach is based on dynamic energy management techniques that minimize dependence on grid electricity, which can fluctuate between energy import and export. A flexible cost function is developed to simultaneously account for CO 2 emissions and electricity prices, enabling a balance between environmental impact and operational costs. The optimization framework employs mixed-integer linear programming (MILP) to derive the optimal energy management strategy, showcasing significant potential for reducing both CO 2 emissions and electricity costs. Although the methodology is demonstrated in a specific industrial setting, its flexible design ensures applicability across various energy profiles and operational scenarios, making it relevant for a wide range of industrial applications.

关键词： Life cycle assessment Costs Accuracy Electricity mixed integer linear programming Batteries Energy management Sustainable development Optimization Carbon emissions

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Optimization of Rescheduling Under Temporary Speed Restrictions in Urban Rail Transit: A MILP Model Approach

Optimization of Rescheduling Under Temporary Speed Restricti...

引用

International Conference on Intelligent Transportation

作者： Xiao Lin Xueliang Wu Du Shang Shuai Su State Key Laboratory of Advanced Rail Autonomous Operation Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing P.R.China Beijing MTR Operation Corporation Limited

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In urban rail operations, temporary speed limits may be imposed on certain sections due to factors such as track cracks, subway track maintenance, line construction, track renovation, or other external operations near track. These issues could prevent trains from running according to the scheduled timetable, leading to trains delay, cancellations, and longer waiting times for passengers. To reduce the impact of these disruptions, this paper introduces a model-based optimization method for scheduling temporary speed limits on urban rail lines. The model aims to minimize the deviation of trains from their planned timetable and the number of train cancellations, while establishing operational constraint models. Ultimately, the model undergoes linearization to facilitate a solution, which is achieved through numerical integration alongside the application of the Big-M method. This paper considers decision variables and constraints related to train speed limit operations and formulates the problem as a mixed integer linear programming (MILP) model, which can be solved by the CPLEX optimizer. An example is provided to illustrate the effectiveness of the proposed train scheduling model. The computational results indicate that the establishment of the optimization model reduces the impact of temporary speed restrictions.

关键词： Rails Hands Machine learning algorithms Processor scheduling Computational modeling Velocity control Numerical models mixed integer linear programming Delays Public transportation

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Optimal Scheduling of an Integrated Photovoltaic - Battery Storage System Considering Energy Capacity Fade and Revamping Strategy

Optimal Scheduling of an Integrated Photovoltaic - Battery S...

引用

International Conference on Smart Energy Systems and Technologies (SEST)

作者： Asja Alic Silvia Zordan Vincenzo Trovato Antonio De Paola Department of Civil Environmental and Mechanical Engineering University of Trento Trento Italy European Commission - Joint Research Center Ispra Italy

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

This paper proposes a revenue-maximization model for an Integrated Photovoltaic - Battery Energy Storage System, where the storage unit is connected behind the meter of the generator. The proposed approach returns an optimal solution that accounts for the capacity degradation pursuant to cyclic actions of the battery. Note that embedding the capacity degradation into an optimization problem is not straightforward due to its intrinsic non-linear feature. Nonetheless, neglecting this phenomenon may expose the battery to significant revamping costs. This is rather concerning when operating systems over a multiyear planning horizon since significant effects of capacity degradation are evident only over long-time intervals. A mixed integer linear programming is presented where the main features of the capacity degradation are accurately integrated by means of ad-hoc reformulation techniques. Furthermore, the model co-optimizes the operation of both the photovoltaic generator and the battery while providing the optimal revamping strategy to replace the degraded cells and boost the energy capacity. Case studies indicate the effectiveness of the proposed model also when different technical parameters of the battery are adopted.

关键词： Degradation Photovoltaic systems Analytical models Costs Computational modeling Optimal scheduling Generators Discharges (electric) Batteries mixed integer linear programming

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Reinforcement Learning-Based Observability-Aware Cyber Restoration of Power Grid

Reinforcement Learning-Based Observability-Aware Cyber Resto...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Shamsun Nahar Edib Vinod M. Vokkarane Yuzhang Lin Department of Electrical and Computer Engineering University of Massachusetts Lowell Lowell Massachusetts USA Department of Electrical and Computer Engineering New York University New York USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The cyber resilience of cyber-physical power grids relies on swift restoration of cyber domain components following major disturbances such as, natural disasters or man-made attacks. The cyber domain restoration problem is inherently stochastic due to uncertainties surrounding initial outage conditions and restoration action failures. Traditionally, optimization-based methods, such as heuristics and mixed-integer linear programming (MILP), are utilized for solving restoration problems. However, these methods suffer from time-consuming processes and limited adaptability to dynamic conditions. To address these challenges, this paper formulates the observability recovery problem (ORP) as a Markov decision process and uses deep reinforcement learning (DRL) to solve the problem. Numerical simulations on the IEEE 30-bus system demonstrate that our proposed approach outperforms the heuristic approach in terms of both performance and computational efficiency. Moreover, when compared to the MILP approach, our method achieves comparable performance while requiring significantly less computation time.

关键词： Uncertainty Markov decision processes Power system dynamics Numerical simulation Deep reinforcement learning Power grids Computational efficiency mixed integer linear programming Observability Resilience

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Optimal Scheduling of Programmable Appliances for Demand Management in Energy Communities

Optimal Scheduling of Programmable Appliances for Demand Man...

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International Conference on Optimization and Applications (ICOA)

作者： Paolo Lazzeroni Gianmarco Lorenti Aldo Canova Maurizio Repetto Dipartimento Energia “Galileo Ferraris” Politecnico di Torino Turin Italy

ISBN: (数字)9798350387353

ISBN: (纸本)9798350387360

Increasing the share of Renewable Energy Sources (RES) in energy consumption is perceived today as essential to decarbonizing energy systems. In this context, the Renewable Energy Communities (RECs) have been recently introduced to create a more decentralized energy system, where each member may share RES-based energy production to increase local self-consumption. To maximize the benefits for each member, the RES-based energy generation should match the demand. Thus, demand management may contribute in this regard by introducing load-shifting for the electric appliances used by REC's members. In this view, different modeling approaches are proposed as mixed integer linear programming and mixed integer Quadratic programming. Solutions can be used to suggest possible changes to the end-users' current habits. Simulations are performed to compare energy, economic, and environmental Key Performance Indicators, including self-consumption, self-sufficiency, and CO 2 emission savings.

关键词： Renewable energy sources Energy consumption Costs Production Optimal scheduling mixed integer linear programming Quadratic programming Sustainable development Carbon emissions Load modeling

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