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Resilience-Based Workforce Routing and Scheduling Problem in Substation System Emergency Operation*

Resilience-Based Workforce Routing and Scheduling Problem in...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Tianbao Liang Yaping Liu Zhanbo Xu Jiang Wu Haoming Zhao Xiaohong Guan Moe Klinns Lab and Systems Engineering Institute of Xi’an Jiaotong University Xi’an China Department of Automation Center for Intelligent and Networked Systems (CFINS) TNLIST Tsinghua University Beijing China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Global climate changes have increased the frequency and consequences of disasters, which affects the stable operation of the electric power network. Thus, substation system as a significant part of electric power network, its optimal emergency operation facing disaster has attracted much attention. This paper focuses on the workforce routing and scheduling problem (WRSP) in the substation system emergency operation, which is formulated as a mixed integer linear programming problem with the objective of maximizing system resilience. Task association constraint model and technicians routing constraint model are established to describe the cooperative relationship between technicians of different crews and the complex relationship between tasks respectively. Task and feeder output correlation constraint model is established to correlate the execution of tasks in continuous time with the discrete time output of the substation feeders. In this way, the technician assignment is independent of time and the problem can be efficiently solved by optimization solver. The performance and effectiveness of the developed method is demonstrated using a practical case study. The results show that the developed model can effectively coordinate technicians and tasks, and improve the resilience of this system to disasters.

关键词： Substations Correlation Disasters Routing Numerical models mixed integer linear programming Indexes Optimization Resilience Meteorology

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Multi-Stage Distributionally Robust Unit Commitment Considering the Flexibility of Gas-Fired Units

Multi-Stage Distributionally Robust Unit Commitment Consider...

引用

IEEE General Meeting Power& Energy Society

作者： Mao Liu Xiangyu Kong Longyu Zhang Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin China

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The gas turbine plays a critical role in enhancing the flexibility of the power system due to its capability of rapid start-up and shutdown. To better handle the uncertainties faced in the intraday real-time scheduling process, this study proposes a multi-Stage distributionally robust unit commitment (MDRUC) model based on the Wasserstein metric. Compared with the typical distributionally robust unit commitment (TDRUC) model, the MDRUC model demonstrates higher adaptability under strong uncertainties and provides a larger feasible domain. To address the “curse of dimensionality” encountered in the model's solution process, we propose a mixed approximation rule (MAR), which is transformed into a solvable mixed integer linear programming problem through duality theory. Applying the MDRUC model to the modified 6-bus and 118-bus systems, the operational value of flexibility can be enhanced by up to 4.30% and 0.27%, respectively.

关键词： Adaptation models Uncertainty Costs Systems operation Simulation Data models Real-time systems mixed integer linear programming Power systems Turbines

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A Mathematical Model Integrating Line Balancing, Equipment Selection, and Workforce Management

A Mathematical Model Integrating Line Balancing, Equipment S...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Hamidreza Rezaei Simon Thevenin Audrey Cerqueus LS2N UMR 6004 IMT Atlantique Nantes France

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Designing reconfigurable and adaptable assembly lines is crucial in today’s fast-paced manufacturing world. Due to the intense competition, manufacturing must keep pace with rapidly changing technology. However, this can lead to problems such as the premature end-of-life of equipment. This study explores the integration of second-hand equipment in the assembly line design problem to extend resource lifecycles and reduce costs. We propose a mixed integer linear programming (MILP) model for addressing the assembly line design problem, taking into account line design, equipment management, and workforce management problems aimed at minimizing the total cost of the line. We perform a numerical study to explore the implications of second-hand equipment on the cost of an assembly line. These experiments are based on a simulation where the line is reconfigured in each generation, where a generation corresponds to a modification of the product family. The results of this work indicate a dual effect. On the one hand second-hand equipment significantly reduces the cost of the line. On the other hand, the resulting line requires frequent technician training.

关键词： Training Costs Uncertainty Correlation Mathematical models Numerical models mixed integer linear programming Sustainable development Assembly Investment

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Optimal Hybrid Energy Storage System Scheduling Strategy in Energy Market Considering Battery Cycle Life

Optimal Hybrid Energy Storage System Scheduling Strategy in ...

引用

IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Hongfei Yu Fucong Xu Yuge Chen Weijun Zhang Li Yang Zhenzhi Lin College of Electrical Engineering Zhejiang University Hangzhou China State Grid Fujian Electric Power Co. Ltd Fuzhou China Power Research Institute State Grid Fujian Electric Power Co. Ltd Fuzhou China

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

In the context of large-scale renewable energy integration, actively guiding hybrid energy storage systems (HESS) to participate in electric power energy trading can effectively address power balance issues in modern power systems. However, high investment costs and long payback periods limit the willingness of HESS owners to participate in the energy market. To enhance the techno-economic performance of HESS in the energy market, an optimal HESS scheduling strategy in the energy market considering battery cycle life is proposed in this paper. Firstly, an equivalent full-cycle life model based on depth of discharge (DoD) is developed. Secondly, the proposed battery energy storage (BES) cycle life model is integrated into the optimization scheduling model, presenting an optimal strategy for HESS participation in the energy market. Finally, scenario-based comparative analyses validate the effectiveness of the proposed strategy in increasing the revenue of lithium-ion and vanadium flow HESS in the energy market.

关键词： Renewable energy sources Costs Optimal scheduling Vanadium Hybrid power systems Discharges (electric) Batteries US Department of Defense mixed integer linear programming Investment

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Benders Decomposition for Order Batching and Scheduling Consider Uncertainties

Benders Decomposition for Order Batching and Scheduling Cons...

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Automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Yafeng Wei Ting Qu Yongheng Zhang Kai Zhang Mingxing Li George Q Huang School of Management Jinan University Guangzhou P.R. China Guangdong International Cooperation Base of Science and Technology for GBA Smart Logistics School of Intelligent Systems Science and Engineering Jinan University (Zhuhai Campus) Zhuhai China Shenzhen Research Institute The Hong Kong Polytechnic University Shenzhen P.R. China School of Intelligent Systems Science and Engineering Jinan University (Zhuhai Campus) Zhuhai China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong P.R. China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

Under the trend of mass customization, customer orders show the characteristics of “multi-variety, small batch”, which has a great impact on the scheduling process of batch production enterprises with mass production. This paper studies the problem of order group and batch scheduling with equipment constraints, that is, the order group and batch scheduling that makes the total production cost lowest is found under the equipment and delivery time constraints. Especially, the processing time of different batch equipment is different and uncertain. Firstly, a mixed integer linear programming model is established for order group and batch scheduling problems with equipment constraints. Secondly, in order to realize the optimal decision of the model efficiently, the Benders decomposition is adopted to decompose the original model into the order group master problem and the batch scheduling problem of equipment with different capacities. In view of the uncertain parameters in the model, robust optimization is adopted to transform the uncertainty constraints into robust counterpart. For the convergence problem of decomposed model, the improved Benders cut is added to speed up the convergence. Finally, through numerical experiments, the effectiveness of the algorithm is tested, and its competitiveness is verified in solving the optimal solution of medium-sized or even larger problem cases.

关键词： Uncertainty Job shop scheduling Costs Production Transforms Numerical models mixed integer linear programming Single machine scheduling Optimization Convergence

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Research on the Operation Strategy of Compressed Energy Storage in the Power Market Environment

Research on the Operation Strategy of Compressed Energy Stor...

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New Energy and Electrical Technology (ISNEET), International Symposium on

作者： Tao Wang Zhijie Shi Shiyao Liu Institute of Renewable Energy and Energy Storage Technologies Power China Renewable Energy Company Ltd. Beijing China POWERCHINA HeBei Electric Power Engineering Co. Ltd. Hebei China Hebei Electric Power Design & Survey Technology Innovation Center Hebei China

ISBN: (数字)9798331505905

ISBN: (纸本)9798331505912

In the context of global energy structure transition and environmental protection, compressed air energy storage (CAES) technology has become the key to the enhancement of power system regulation due to its large-scale energy storage capacity, efficient energy conversion efficiency and environmental friendliness. The study uses a mixed integer linear programming model to investigate the economics of compressed air energy storage (CAES) power plants through price arbitrage and FM service market participation strategies in the peak-to-valley tariff system. It is found that CAES power plants charge during low tariff hours and discharge during high tariff hours to maximize profits and provide services in the FM market to increase revenues. The power plant's operating strategy is constrained by factors such as power caps, capacity limits, and self-discharge rates, which need to be allocated appropriately among different markets to optimize overall revenue. The results show that CAES power stations can effectively enhance their economic returns by participating in both price arbitrage and FM service markets under the peak-to-valley tariff system.

关键词： Economics Frequency modulation Atmospheric modeling Tariffs Electricity supply industry Discharges (electric) mixed integer linear programming Resource management Power generation Energy storage

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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...

引用

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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A Novel Superstructure-based Approach to Batch Process Scheduling Problems

A Novel Superstructure-based Approach to Batch Process Sched...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Aadil Bharucha Shamik Misra Ravindra D. Gudi

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

In this work, a novel superstructure-based optimization framework is proposed for batch process scheduling problems. The framework uses a novel maximal flow unit network (m-FUN) representation of the batch processes for the scheduling. The m-FUN representation is developed based on the material flow in and around the processes and storage vessels. The proposed m-FUN framework results in a mixed integer linear programming (MILP) problem and is applied to optimize three case studies taken from the literature. The efficacy of the proposed framework is tested with multiple instances with increasing scheduling horizons and various objectives. The results of this study are compared with other popular solution methods available in the literature. The proposed framework attains the same objective, demonstrating its efficacy in rigorously representing the process nuances and characteristics. Inherent material flow representation in the proposed framework enables seamless incorporation of utility flows, which will be beneficial in integrating utility network design along with the batch scheduling problem.

关键词： Processor scheduling Network topology Scalability Optimization models Batch production systems Topology mixed integer linear programming Computational efficiency Information technology Optimization

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Reverse Supply Chain Network Design Considering Quantity Discount and Collection Policies

Reverse Supply Chain Network Design Considering Quantity Dis...

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Logistics and Industrial Engineering (ICLIE), International Conference on

作者： Nguyen Truong Thi Ho Lam My Ngoc Dinh Thi Phuong Dai Nguyen Van Can Faculty of Industrial Management College of Engineering Can Tho University Viet Nam

ISBN: (数字)9798331510695

ISBN: (纸本)9798331510701

Efficient management of product retrieval and recycling activities in reverse supply chains generates valuable opportunities for businesses to gain more competitive advantages through economic benefit maximization. However, there is a limited scope in the appropriate selection of quantity discount and collection policies for products sold out or collected after use among supply chain members, which are critical for improving supply chain effectiveness. The study addresses this gap by incorporating these crucial policies into a mixed integer linear programming (MILP) model. The model especially investigates various parameters such as product pricing, collection rates, and recycling rates, and is then applied to a case study located in the Mekong Delta region to determine the optimal design of a container supply chain, including suppliers, depots, collection units, recycling units, and customers. The resulting model demonstrates that the proposed policies enhance economic benefits and generate a better balance of interest between stakeholders in the regional supply chain

关键词： Economics Optimization models Supply chains Pricing Containers Industrial engineering Recycling mixed integer linear programming Stakeholders Business

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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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