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Optimization of battery energy storage system (BESS) sizing in different electricity market types considering BESS utilization mechanisms and ownerships

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JOURNAL OF CLEANER PRODUCTION 2024年 470卷

作者： Zhang, Ruixiaoxiao Lee, Minhyun Huang, Lijie Ni, Meng Hong Kong Polytech Univ Dept Bldg & Real Estate Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Res Inst Smart Energy RISE Dept Bldg & Real Estate Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Res Inst Sustainable Urban Dev RISUD Dept Bldg & Real Estate Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Res Inst Smart Energy RISE Kowloon Hong Kong Peoples R China

To elucidate the optimal techno-economic role of battery energy storage system (BESS), this study proposes optimal sizing of BESS in various scenarios based on BESS installation in existing photovoltaic systems. The proposed scenarios include different electricity market types (i.e., peer-to-grid, peer-to-peer, and energy storage sharing) considering utilization mechanism (i.e., individual-design or shared-design) and ownership (i.e., user- owned or developer-owned) of the BESS. Towards this end, this study develops comprehensive and systematic mathematical models for BESS sizing using mixed-integer linear programming algorithm, and the BESS sizing is optimized to maximize the total net present value. The developed models are validated in the Hong Kong context considering four peers, and the empirical data of electric load profile as well as the photovoltaic installed capacity are collected. As a result, it is indicated that the optimal BESS capacity in energy storage sharing scenario is the least. In terms of electricity bill saving, user-owned BESS is regarded as the model yielding the highest electricity bill savings. The breakdown of net present value exposes that under the same ownership, the optimal BESS capacity is determined by different utilization mechanisms. Regarding the total net present value, it is found that developer-owned BESS could achieve the maximum economic merits. Nonetheless, the distribution loss through energy storage sharing is also the highest. The policy implications of this study primarily emphasize incentivizing user-owned BESS, promoting energy storage sharing, supporting shared BESS infrastructure, and encouraging a diversity of electricity trading mechanisms to enhance the integration and efficiency of renewable energy systems.

关键词： Battery energy storage system Sizing optimization mixed-integer linear programming Utilization mechanism and ownership Peer trading Energy storage sharing

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Integrated Models-Driven Framework to Generate Various Online and Print Tests 21st

Integrated Models-Driven Framework to Generate Various Onlin...

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21st International Conference on Computer Information Systems and Industrial Management (CISIM)

作者： Borissova, Daniela Buhtiyarov, Nikolay Yoshinov, Radoslav Garvanova, Magdalena Garvanov, Ivan Bulgarian Acad Sci Inst Informat & Commun Technol Sofia 1113 Bulgaria Bulgarian Acad Sci Lab Telemat Sofia Bulgaria Univ Lib Studies & Informat Technol Sofia 1784 Bulgaria

ISBN: (纸本)9783031105395;9783031105388

The ongoing digital transformation influence all fields from education to economics. That is why many efforts are taken to develop different business models to reflect the new reality. The e-tests are the core of contemporary elearning and are suitable to conduct proper checks about the level of competency for different occupations. In this regard the current article describes an integrated framework based on different optimization models to select a set of questions to compose e-tests or print tests. The basic workflow algorithm of this framework is described. The framework' distinguish feature is the possibility to generate different levels of tests' complexity thanks to the specifics of formulated single criterion mixed-integer and multi-criteria models. The applicability of the integrated models-driven framework is demonstrated by using a test bank with predefined questions with different difficulties. The obtained results prove the possibility to generate tests with different degrees of complexity accordingly to the formulated models.

关键词： Integrated framework Model-driven design mixed-integer linear programming Multi-criteria optimization Tests generation

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Bi-objective optimisation of remanufacturing decisions with component commonality under different reworking scenarios

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2021年第10期34卷 1086-1107页

作者： Sitcharangsie, Sakraan Wong, T. C. Ijomah, Winifred Rajamangala Univ Technol Phra Nakhon Dept Sustainable Ind Management Engn Bangkok 10800 Thailand Univ Strathclyde Dept Design Mfg & Engn Management Glasgow Lanark Scotland

Decision-making for remanufacturing is more complicated than that of traditional manufacturing because used or new components can be selected to remanufacture products. It becomes difficult to determine the various options of the components and their subsequent effect on the options at the same time. In fact, all decisions made in one remanufacturing activity will have a direct impact on the decisions taken in subsequent activities and this will affect profitability. Therefore, a decision-making model is proposed to support businesses in each remanufacturing activity by using mixed-integer linear programming to maximise profit and minimise operational time. It remains unknown whether component commonality always benefits remanufacturing. Therefore, this research contributes to the literature by quantifying and controlling the impact of component commonality on the objectives under different reworking scenarios characterised by the percentage of reworked components, reworking time, and reworking cost. When reworking costs and the percentage of reworked components are higher, the effect of component commonality on profit fluctuation increases. The remanufacturer can control these situations by reducing reworking costs, selecting specific patterns of component commonality that generate high profits or choosing the appropriate percentage of reworked components depending on various scenarios.

关键词： Remanufacturing decision component commonality optimisation mixed-integer linear programming

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A new mixed-integer linear programming model for rescue path planning in uncertain adversarial environment

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COMPUTERS & OPERATIONS RESEARCH 2012年第12期39卷 3420-3430页

作者： Berger, Jean Boukhtouta, Abdeslem Benmoussa, Abdelhamid Kettani, Ossama Def R&D Canada Valcartier Quebec City PQ Canada Def R&D Canada CORA Ottawa ON Canada Modellium Inc Quebec City PQ Canada

Efficient vehicle path planning in hostile environment to carry out rescue or tactical logistic missions remains very challenging. Most approaches reported so far rely on key assumptions and heuristic procedures to reduce problem complexity. In this paper, a new model is proposed to solve the discrete rescue path planning problem for a single agent navigating in uncertain adversarial environment. It relies on a novel and simplified mathematical mixed-integer linear programming formulation aimed at minimizing traveled distance and threat exposure. Exploiting a user-defined survivability function approximation and survivability threshold, the approximate model allows constructing a solution providing an adjustable optimality gap interval on the optimal solution. Experimental results show the value of the proposed approach in computing near optimal solutions reasonably fast for various problem instances. Crown Copyright (c) 2012 Published by Elsevier Ltd. All rights reserved.

关键词： Path planning Constrained shortest path mixed-integer linear programming

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Enhancing power grid resilience to winter storms via generator winterization with equity considerations

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SUSTAINABLE CITIES AND SOCIETY 2024年 114卷

作者： Bilir, Baris Kutanoglu, Erhan Hasenbein, John J. Austgen, Brent Garcia, Manuel Skolfield, J. Kyle Univ Texas Austin Operat Res & Ind Engn Grad Program Austin TX USA Los Alamos Natl Lab Los Alamos NM USA Sandia Natl Labs Livermore CA USA

We develop two-stage stochastic programming models for generator winterization that enhance power grid resilience while incorporating social equity. The first stage in our models captures the investment decisions for generator winterization, and the second stage captures the operation of a degraded power grid, with the objective of minimizing load shed and social inequity. To incorporate equity into our models, we propose a concept called adverse effect probability that captures the disproportionate effects of power outages on communities with varying vulnerability levels. Grid operations are modeled using DC power flow, and equity is captured through mean or maximum adverse effects experienced by communities. We apply our models to a synthetic Texas power grid, using winter storm scenarios created from the generator outage data from the 2021 Texas winter storm. Our extensive numerical experiments show that more equitable outcomes, in the sense of reducing adverse effects experienced by vulnerable communities during power outages, are achievable with no impact on total load shed through investing in winterization of generators in different locations and capacities.

关键词： Equitable community resilience Power grid resilience mixed-integer linear programming Winter storm

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Improving access to housing and supportive services for runaway and homeless youth: Reducing vulnerability to human trafficking in New York City

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IISE TRANSACTIONS 2024年第3期56卷 296-310页

作者： Kaya, Yaren Bilge Maass, Kayse Lee Dimas, Geri L. Konrad, Renata Trapp, Andrew C. Dank, Meredith Northeastern Univ Mech & Ind Engn Boston MA 02115 USA Worcester Polytech Inst Data Sci Program Worcester MA 01609 USA Worcester Polytech Inst WPI Business Sch Worcester MA 01609 USA NYU New York NY USA

Recent estimates indicate that there are over a million runaway and homeless youth and young adults (RHY) in the United States (US). Exposure to trauma, violence, and substance abuse, coupled with a lack of community support services, puts homeless youth at high risk of being exploited and trafficked. Although access to safe housing and supportive services such as physical and mental healthcare is an effective response to the vulnerability of RHY towards being trafficked, the number of youth experiencing homelessness exceeds the capacity of available housing resources in most US communities. We undertake a RHY-informed, systematic, and data-driven approach to project the collective capacity required by service providers to adequately meet the needs of RHY in New York City, including those most at risk of being trafficked. Our approach involves an integer linear programming model that extends the multiple multidimensional knapsack problem and is informed by partnerships with key stakeholders. The mathematical model allows for time-dependent allocation and capacity expansion, while incorporating stochastic youth arrivals and length of stays, services provided in a periodic fashion, and service delivery time windows. Our RHY and service provider-centered approach is an important step toward meeting the actual, rather than presumed, survival needs of vulnerable youth.

关键词： Human trafficking homelessness capacity expansion mixed-integer linear programming homeless shelters

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Overview and advancement of power system topology addressing pre- and post-event strategies under abnormal operating conditions

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2024年 40卷

作者： Yaldiz, Abdurahman Gokcek, Tayfur Ates, Yavuz Erdinc, Ozan Yildiz Tech Univ Dept Elect Engn Istanbul Turkiye

The transition towards increased utilization of renewable energy and electric vehicles (EVs), along with the growing use of various other electrical devices, poses challenges to the stable and resilient operation of electric power systems (EPS), especially in the face of natural phenomena associated with climate change. This means that accurate topology and balanced EPS plays a key role to increase the capacity to respond quickly and in a coordinated manner to disaster situations such as cyber-attacks, earthquakes and floods. In this study, a new approach is presented to quickly and accurately detect topology attacks in EPS, thus contributing to making safer and more resilient. The proposed methods provide insights into maintaining uninterrupted electricity service by enabling EPS management through both post- and pre-event operational strategies. This approach is created by identifying faulty points with the obtained topology information and creating microgrid (MG) groups. Machine learning techniques have been integrated into the data intrusion attack detection (DIAD) system, enabling the detection of manipulated or faulty smart meters (SM). Concurrently, a topology identification (TI)-based graph learning algorithm is propounded to determine the exact fault locations before and after the event. For MV region restoration after determining the TI region, a mixed-integer linear programming (MILP) approach is employed to optimize the load restoration process in the MG regions. This approach aims to minimize losses and restore critical loads to their previous state as quickly as possible using flexible and emergency power balancing systems, including grid-support storage systems (GSSs), photovoltaic systems (PVs), electric vehicle charging stations (EVCS), and mobile generators. Moreover, a detailed compilation is presented under the topics of EPS topology, phase identification (PI) and its effect on power system resiliency (PSR), shedding light on the future developme

关键词： Smart grid Phase identification Power system resiliency Grid support storage system Topology identification Optimization mixed-integer linear programming Machine learning

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Function-dependent neural-network-driven state feedback control and self-verification stability for discrete-time nonlinear system

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NEUROCOMPUTING 2024年 609卷

作者： Wang, Jingya Feng, Xiao Yu, Yongbin Wang, Xiangxiang Han, Xinyi Shi, Kaibo Zhong, Shouming Shen, Jiarun Cai, Jingye Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu 610054 Sichuan Peoples R China Chengdu Univ Sch Elect Informat & Elect Engn Chengdu 610106 Sichuan Peoples R China Univ Elect Sci & Technol China Sch Math Sci Chengdu 611731 Sichuan Peoples R China

Deep learning significantly impacts neural network controller synthesis. Despite the higher efficiency of deep learning algorithms compared to traditional model-based controller design methods, the performance of these neural network controllers lacks theoretical guarantees. Initially, this paper proposes an architecture to synthesize the state feedback controller and Lyapunov function, called function-dependent neural-network- driven (NN-driven) architecture. The discrete-time nonlinear system dynamics, state feedback controller and Lyapunov function in this architecture are all designed using neural networks, which can improve the efficiency of stability verification and control performance. To realize self-verification of system stability by neural networks, three optimization problems are designed based on Lyapunov stability conditions and training speed constraints, solved using mixed-integer linear programming (MILP) solvers. Additionally, a MILP-based algorithm called Stability Counter-examples Updating Training Set (SCUTS) is proposed to simultaneously train the state feedback controller and Lyapunov function neural networks. Finally, experiments conducted on a second-order discrete-time nonlinear system, an inverted pendulum with NN-driven dynamics and an inverted pendulum with Lagrangian dynamics demonstrate the effectiveness of this work. Experimental results indicate that this work outperforms previous research on synthesizing neural network controllers in both the neural network training speed and the control system stabilization speed.

关键词： Function-dependent Neural-network-driven Self-verification Lyapunov stability mixed-integer linear programming Nonlinear system

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Energy-efficient train control incorporating inherent reduced-power and hybrid braking characteristics of railway vehicles

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2024年 163卷

作者： Peng, Yang Lu, Shaofeng Chen, Feng Liu, Xiao Tian, Zhongbei South China Univ Technol Shien Ming Wu Sch Intelligent Engn Guangzhou Peoples R China Univ Liverpool Sch Elect Engn & Elect Liverpool England Univ Birmingham Sch Elect Elect & Syst Engn Birmingham England

With the increasing awareness of carbon neutrality, the application of energy -efficient train control (EETC) to rail transportation systems continues to attract attention from industry and academia. In many classic EETC studies, train models are commonly simplified with pure regenerative braking and constant power characteristics during high speeds, to simplify the complexity of the model. In this paper, a realistic model incorporating hybrid braking characteristics combining regenerative and mechanical braking, and reduced -power characteristics at high speeds into the EETC problem is proposed to improve control precision of the train and the modeling precision of the energy consumption and time. This study addresses the minimum -time train control (MTTC) problem and EETC problem considering nonlinear traction characteristics based on the mixed -integer linear programming (MILP) method, and nonlinear traction and braking characteristics are approximated via a piecewise linear (PWL) modeling technique. Results indicate that the proposed alternative models achieves some deviations from the realistic model in terms of time, energy consumption, and control strategies. The deviations between models in energy consumption and time accumulate as the number of operating stations increases. Therefore, the choice of an appropriate model depends on the precision requirements of various scenarios. In scenarios demanding higher precision, selecting the proposed realistic model is crucial for more accurate computation of energy consumption and time and for obtaining more precise control strategies.

关键词： Energy-efficient train control Minimum-time train control Reduced-power characteristics Hybrid braking characteristics mixed-integer linear programming Railway vehicles

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The impact of optimal parcel locker locations on costs and the environment

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INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT 2022年第4期52卷 324-350页

作者： Peppel, Marcel Spinler, Stefan WHU Otto Beisheim Sch Management Inst Logist Management Vallendar Germany

Purpose Last-mile delivery is associated with a negative environmental impact and high costs. The purpose of this paper is to develop an approach to designing stationary parcel locker (SPL) networks while minimizing both CO2 equivalent (CO(2)e) emissions and costs during delivery and pick-up. Design/methodology/approach This study uses a multinomial logit model to evaluate recipients' willingness to use SPLs based on their availability at home and travel distance. To determine optimal SPL locations, this study formulates a mixed-integer linear programming model. Findings The empirical study of different regional clusters reveals that optimal SPL locations can generate cost savings of up to 11.0%. SPLs have a positive impact on total CO(2)e emission savings in urban areas (i.e. up to 2.5%), but give rise to additional emissions (i.e. 4.6%) in less populated areas due to longer travel distances during the pick-up process. Originality/value This paper optimizes SPL locations and the ecological effect of SPLs by minimizing emissions and costs simultaneously. Furthermore, it extends existing discrete choice models by also including recipients' availability at home, increasing the accuracy of recipients' preferences. So far, the effect of SPLs has been studied for metropolitan areas only. A global logistics service provider shared a real dataset which allows us to study seven different regional clusters ranging from rural areas to large cities. Thus, this study contributes to the field of sustainable urban logistics.

关键词： Last-mile delivery Parcel locker location Sustainable delivery mixed-integer linear programming Scenario analysis

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