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Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), International Conference on

作者： Ayandeep Ganguly Arindam Kumar Sil Department of Electrical Engineering Haldia Institute of Technology Kolkata India Dept. of Electrical Engineering Jadavpur University Kolkata India

ISBN: (数字)9798331528614

ISBN: (纸本)9798331528621

With the increasing application of decentralized generation and renewable integration, the problems created by the uncertainty of the renewable sources can be mitigated by the development of energy communities. The formation of energy communities can be made more inclusive in developing countries by considering the distinct energy use characteristics of users from different demographic regions. In this work the appliance based power usage characteristics of two prosumers representing urban and rural regions each have been modelled using LoadProGen and Matlab 2021. These profiles were further used to develop a demographic clustering based time of use tariff which was tested using an appliance preference based demand side management program developed using mixed integer linear programming. On comparing against a uniform tariff applied both to urban and rural participants of the energy community, the proposed method shows significant improvement in community energy cost for domestic application.

关键词： Renewable energy sources Uncertainty Demand side management Tariffs Developing countries Mathematical models mixed integer linear programming MATLAB Testing Load modeling

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Cost-optimal deployment of autonomous mobile lockers co-operating with couriers for simultaneous pickup and delivery operations

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2023年 146卷

作者： Ensafian, Hamidreza Andaryan, Abdullah Zare Bell, Michael G. H. Geers, D. Glenn Kilby, Philip Li, Jun Univ Sydney Inst Transport & Logist Studies Business Sch Sydney NSW 2006 Australia Iran Univ Sci & Technol Sch Railway Engn Tehran Iran CSIRO CSIRO Data61 GPO Box 1700 Canberra ACT 2601 Australia Australian Natl Univ GPO Box 1700 Canberra ACT 2601 Australia

This work is an extension of a study by Li et al. (2021) in which a two-echelon network consisting of multiple depots and a fleet of Autonomous Mobile Lockers (AMLs) co-operating with couriers was examined to address the simultaneous pickup and delivery problem. This work considers the same problem but allows couriers and robots to traverse open routes. Most importantly, couriers can perform multiple missions, allowing them to restart a new mission from any stop. In order to formulate this problem, a mixed-integer linear programming (MILP) model was introduced with the aim of minimizing the total cost. Since the MILP model is not able to solve large-scale problems, an Adaptive Backtracking-Simulated Annealing metaheuristic (ABSM) algorithm was developed whose efficiency was analysed using numerical experimentation. The results show that the ABSM algorithm introduced is able to provide quality solutions within a reasonable amount of time. Also, the proposed algorithm was compared with three variants of the simultaneous pickup and delivery problem and the amount of savings was calculated. Finally, the significant problem parameters were identified and their impact on the value of the objective function was investigated. The results show that significant savings can be achieved when couriers are able to perform multiple open routes in a cooperative system of AMLs and couriers.

关键词： Routing Last-mile delivery robots Multi-trip vehicle routing problem Simultaneous pick and delivery mixed integer linear programming

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Quay crane scheduling with time windows constraints for automated container port

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OCEAN & COASTAL MANAGEMENT 2023年 231卷

作者： Wei, Minghui He, Junliang Tan, Caimao Yue, Jiantao Yu, Hang Shanghai Maritime Univ Sch Econ & Management Shanghai Peoples R China Shanghai Maritime Univ Inst Logist Sci & Engn Shanghai Peoples R China Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai Peoples R China Yanfeng Automot Safety Syst Co Ltd Shanghai Peoples R China

The traditional quay crane of the container terminal is gradually transitioning to automation, which significantly changes the loading and unloading operation mode of the quay crane. In this paper, we study the sequence scheduling of automated quay crane (AQC) with time window constraints. First, the process of AQC handling operation is decomposed, and the mechanism model for AQC operation is established. Then, a mixed integer linear programming model is formulated to optimize the scheduling of AQC considering the time window constraints. Finally, the effectiveness of the optimization model is verified by arithmetic examples, and the management insights of energy efficiency optimization of the quay crane scheduling are given through scenario analysis.

关键词： Automated container port Quay crane scheduling mixed integer linear programming Time window constraints

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An MILP Approach for Modeling and Analyzing the BESS for Smoothing Renewable Fluctuations Considering BESS Capacity Attenuation in the Bulk Power System With High Inverter-Based Resource Penetration

An MILP Approach for Modeling and Analyzing the BESS for Smo...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Hualong Liu Wenyuan Tang Department of Electrical and Computer Engineering North Carolina State University Raleigh USA

ISBN: (数字)9798331516116

ISBN: (纸本)9798331516123

Analyzing the effectiveness of the battery energy storage system (BESS) in smoothing renewable fluctuations correctly is vital to the stable operation of the power system. Therefore, based on stochastic programming and attention-based time series forecasting with learnable and interpretable basis (BasisFormer), we propose a mixed integer linear programming (MILP) approach for modeling the BESS and analyzing the effectiveness of the BESS in smoothing renewable fluctuations in the bulk power system with high inverter-based resources. The approach considers the attenuation of BESS capacity and the uncertainty of renewable generation. First, we present a scenario generation and reduction method based on Latin hypercube sampling (LHS) and the Kantorovich distance. Second, we propose a state of health (SoH) prediction method of the BESS based on BasisFormer. Third, we propose an MILP approach for modeling the BESS and analyzing the effectiveness of the BESS in smoothing renewable fluctuations. Finally, we verify the proposed approach through case studies. The experimental results show that the attenuation of BESS capacity is a crucial factor in correctly analyzing the effectiveness of the BESS in smoothing renewable fluctuations.

关键词： Renewable energy sources Analytical models Fluctuations Smoothing methods Uncertainty Battery energy storage system Attenuation Power systems mixed integer linear programming Scenario generation

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Intelligent Cost-Effective Electric Vehicle Charging Solutions for Cities and Highway Networks

Intelligent Cost-Effective Electric Vehicle Charging Solutio...

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International Communication Systems and Networks and Workshops, COMSNETS

作者： Akshat Lohia Aadesh Pochhi Shivansh Mishra Nilotpal Chakraborty Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati Assam India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

In this work, we address the strategic placement and optimal sizing of electric vehicle charging stations for cities as well as highway traffic to minimize overall cost. We formulate the problem as a mixed integer linear programming (MILP) model and propose a set of greedy algorithms to obtain scalable solutions quickly. For city areas, we propose a systematic approach considering factors like population density and traffic patterns to maximize customer satisfaction and minimize costs. For highways and expressways, we account for deterministic inter-arrival times and maximum waiting times. Additionally, we propose an integrated approach that, when run for two cities and a connecting highway, demonstrates a total cost reduction compared to using separate algorithms for cities and highways.

关键词： Road transportation Greedy algorithms Costs Systematics Urban areas Customer satisfaction Traffic control Electric vehicle charging mixed integer linear programming Population density

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Integrated simulation and optimization framework for quantitative analysis of near-face stockpile mining

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SIMULATION MODELLING PRACTICE AND THEORY 2023年第1期128卷

作者： Gong, Hongshuo Afrapoli, A. Moradi Askari-Nasab, H. Univ Alberta Min Optimizat Lab MOL 6-237 Donadeo Innovat Ctr Engn9211-116 St NW Edmonton AB T6G 1H9 Canada Laval Univ IntelMine Lab Quebec City PQ Canada

A new conceptual mining method called the near-face stockpile (NFS), which combines the in-pit crushing and conveying IPCC system with a pre-crusher stockpile, has recently been proposed for large open pits with sufficient pit bottom width. In the past, stockpiles mainly act as a "buffer" to improve the stability of the production system. However, in NFS ore will be dumped into the precrusher stockpile located at the bottom of the current pit and be fed into the crusher after blending to the desired head grade, instead of being dumped directly into the crusher. Theoretically, this design not only retains the high efficiency and high output of IPCC, but also endows the mining system with better quantity and quality stability. Verifying these advantages and objectively evaluating the NFS method has become a problem worth studying. Since the NFS method exhibits distinctive layout and feeding mechanisms, which distinguish it from other mining methods, a novel simulation model is required for the accurate modeling of the NFS method and quantitatively evaluating the performance of NFS methods. In addition, this paper also proposes an optimization model for short-term production scheduling for NFS method based on the mixed integer linear programming (MILP) method. An oil sands mine case study is implemented to verify the proposed simulation model. One year simulation results reveal that compared to the traditional mining method, the overall production increased by 5.06%, the transporting distance of minerals by trucks was reduced by 17.87%, and the shovels' and crusher's utilization increased by 4.96% and 4.85%, respectively, when using NFS method.

关键词： Near-face stockpiling mixed integer linear programming Simulation and optimization Production planning

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BOOST: Microgrid Sizing Using Ordinal Optimization

BOOST: Microgrid Sizing Using Ordinal Optimization

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IEEE Texas Power and Energy Conference (TPEC)

作者： Mohamad Fares El Hajj Chehade Sami Karaki Chandra Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX USA Electrical and Computer Engineering Department American University of Beirut Beirut Lebanon

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

The transition to sustainable energy systems has highlighted the critical need for efficient sizing of renewable energy resources in microgrids. In particular, designing photovoltaic (PV) and battery systems to meet residential loads is challenging due to trade-offs between cost, reliability, and environmental impact. While previous studies have employed dynamic programming and heuristic techniques for microgrid sizing, these approaches often fail to balance computational efficiency and accuracy. In this work, we propose BOOST, or Battery-solar Ordinal Optimization Sizing Technique, a novel framework for optimizing the sizing of PV and battery components in microgrids. Ordinal optimization enables computationally efficient evaluations of potential designs while preserving accuracy through robust ranking of solutions. To determine the optimal operation of the system at any given time, we introduce a mixed-integer linear programming (MILP) approach, which achieves lower costs than the commonly used dynamic programming methods. Our numerical experiments demonstrate that the proposed framework identifies optimal designs that achieve a levelized cost of energy (LCOE) as low as 8.84 ¢/kWh, underscoring its potential for cost-effective microgrid design. The implications of our work are significant: BOOST provides a scalable and accurate methodology for integrating renewable energy into residential microgrids, addressing economic and environmental goals simultaneously.

关键词： Photovoltaic systems Renewable energy sources Costs Accuracy Microgrids Dynamic programming Batteries mixed integer linear programming Computational efficiency Optimization

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An MILP Approach Based Optimization Techniques for Offshore Wind Farms Electrical Collector Systems

An MILP Approach Based Optimization Techniques for Offshore ...

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Electrical Automation and Artificial Intelligence (ICEAAI), International Conference on

作者： Lijuan Huang Ting Hou Zhen Pan Min Cheng Yining Zhang Qingming Xin Guangxi Power Grid Co. Ltd China Southern Power Grid Co. Ltd Nanning Guangxi China Electric Power Research Institute Co. Ltd China Southern Power Grid Co. Ltd Guangzhou Guangdong China

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

The sizing and placement of the lines between the offshore substation (OS) and the wind turbines (WTs) are optimized using the mixed integer linear programming-based approach to large-scale offshore wind farm collector system planning (OWF-CSP) that we offer in this work. In order to guarantee the radiality of the topology of the offshore wind farm's collector system and expedite the solution process, we discover that the problem is comparable to distribution system planning, where topological constraints from Distribution Network Extension Planning (DNEP) are implemented. The effectiveness of the proposed method is demonstrated by a case study based on an OWF with 42 fixed-location WTs. The OWF-CSP approach suggested in this paper reduces the computational time with the aid of radiality constraints and lowers the investment cost and power loss on the cables in comparison to the conventional design.

关键词： Substations Distribution networks Wind farms Routing Stability analysis Planning mixed integer linear programming Wind turbines Topology Reliability

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Urban Distribution Network Planning Considering Three-Sectioned and Two-Linked Network

Urban Distribution Network Planning Considering Three-Sectio...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Yizhe Zhang Mingqiang Wang Jialiang Wang Chang Xu Zihan Wang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

ISBN: (数字)9798331517540

ISBN: (纸本)9798331517557

Three-sectioned and two-linked lines are widely used in urban distribution networks due to its high dependability and high line load rate. In newly developed urban areas, manually planning three-sectioned and two-linked lines is often challenging and time-consuming. This paper focuses on optimally planning three-sectioned and two-linked lines for practical urban distribution networks. First, this paper analyzes common connection configurations in current urban distribution networks. Next, a mixed-integer linear programming (MILP) model is proposed for directly planning three-sectioned and two-linked lines in distribution network. Finally, an algorithm for verification is introduced to evaluate the resilience of the planned three-sectioned and two-linked lines in distribution network under fault scenarios. The effectiveness and practicality of the proposed model are demonstrated on a real distribution network consisting of 22 blocks.

关键词： Electrical engineering Computational modeling Optimization models Urban areas Distribution networks Planning mixed integer linear programming Computational efficiency Switching circuits Resilience

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Inclusion of frequency nadir constraint in the unit commitment problem of small power systems using machine learning

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2023年 36卷

作者： Rajabdorri, Mohammad Kazemtabrizi, Behzad Troffaes, Matthias Sigrist, Lukas Lobato, Enrique Comillas Pontif Univ IIT ICAI Sch Engn Madrid Spain Univ Durham Durham England

As the intention is to reduce the amount of thermal generation and to increase the share of clean energy, power systems are increasingly becoming susceptible to frequency instability after outages due to reduced levels of inertia. To address this issue frequency constraints are being included in the scheduling process, which ensure a tolerable frequency deviation in case of any contingencies. In this paper, a method is proposed to integrate the non-linear frequency nadir constraint into the unit commitment problem, using machine learning. First, a synthetic training dataset is generated. Then two of the available classic machine learning methods, namely logistic regression and support vector machine, are proposed to predict the frequency nadir. To be able to compare the machine learning methods to traditional frequency constrained unit commitment approaches, simulations on the power system of La Palma island are carried out for both proposed methods as well as an analytical linearized formulation of the frequency nadir. Our results show that the unit commitment problem with a machine learning based frequency nadir constraint is solved considerably faster than with the analytical formulation, while still achieving an acceptable frequency response quality after outages.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Data -driven method mixed integer linear programming Frequency constrained unit commitment Machine learning

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