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Designing a two-stage model for a sustainable closed-loop electric vehicle battery supply chain network: A scenario-based stochastic programming approach

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 190卷

作者： Saeedi, Mehran Parhazeh, Sina Tavakkoli-Moghaddam, Reza Khalili-Fard, Alireza Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Istinye Univ Res Ctr Performance & Prod Anal Istanbul Turkiye

Transportation is a fundamental requirement of modern life. Vehicles powered by fossil fuels are highly polluting. This study develops a two-stage stochastic programming model to establish a sustainable closed-loop supply chain for Electric Vehicle (EV) batteries. The model considers economic, environmental, and social criteria, including cost, energy consumption, carbon emissions, and job creation. The epsilon-constraint method and three multi-objective meta-heuristic algorithms are utilized to solve problems. Implementing this model in a case study of an EV battery supply chain aids managerial decision-making for optimal center establishment, flow determination, and inventory setting. Finally, essential parameters are analyzed, and several important managerial insights are prepared. The results suggest that investing in used battery collection significantly reduces costs and carbon emissions.

关键词： Sustainable closed -loop supply chain Electric vehicle battery Multi -objective optimization Meta -heuristic algorithms two -stage stochastic programming

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State Estimation of Asymmetrical Distribution Networks by μ-PMU Allocation: A Novel stochastic two-stage programming

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ELECTRIC POWER SYSTEMS RESEARCH 2022年第0期213卷

作者： Abdolahi, Arya Kalantari, Navid Taghizadegan Azarbaijan Shahid Madani Univ Dept Elect Engn Tabriz Iran

Distribution system state estimation provides essential data for the system monitoring and control, which some uncertain parameters such as the intermittent and varying output of distributed generation (DG), random meter errors, and inaccurate network parameters make situational awareness (SA) of distribution systems a challenging issue. To address these issues, this paper develops an innovative two-stage stochastic programming model, where in the first stage, optimal mu-PMU placement is implemented aiming at minimizing the installation cost of mu-PMU and maximizing the number of measurement redundancy and the system observability in the presence of partially zero injection nodes (PZIN), while in the second stage state estimation of three-phase asymmetric DG -integrated distribution systems is performed to enhance SA. By applying the proposed model, the optimal lo-cations of mu-PMUs in the presence of PZINs and various contingencies were achieved, and the distribution system state estimation was obtained with high accuracy and low error percentage. The feasibility of the proposed methodology is verified on the modified IEEE 85-bus distribution system.

关键词： State estimation two -stage stochastic programming ?-PMU placement Situational awareness Distributed generation Asymmetrical distribution network

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Integrated strategic energy mix and energy generation planning with multiple sustainability criteria and hierarchical stakeholders

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第2期308卷 864-883页

作者： Irawan, Chandra Ade Jones, Dylan Hofman, Peter S. Zhang, Lina Univ Nottingham Ningbo Nottingham Univ Business Sch China Ningbo Peoples R China Nottingham Ningbo China Beacons Excellence Res & I Ningbo Peoples R China Univ Portsmouth Ctr Operat Res & Logist Sch Math & Phys Portsmouth England James Cook Univ Singapore Singapore Univ Exeter Univ Exeter Business Sch Ctr Simulat Analyt & Modelling Exeter England

This paper proposes a combination of two optimization models for simultaneously determining strategic energy planning at both national and regional levels. The first model deals with a single-period energy mix where the electricity production configuration at a future date (e.g., 2050), based on the available generation sources, is optimally obtained. An optimization model, based on a non-linear goal programming method, is designed to ensure a mixed balance between national and regional goals. The desired energy mix configuration, which is the solution obtained by solving the first model, is then fed into the second model as the main data input. In the second model, a multiple-period generation expansion plan is designed which optimizes the energy transition over the time horizon from the present until the future planning date (2050). The model considers uncertain parameters, including the regional energy demand, fuel cost, and national peak load. A two-stage stochastic programming model is developed where the sample average approximation approach is used as a method of solution. The practical use of the proposed models has been assessed through application to the electricity generation system in China.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Multiple objective programming Energy planning Goal programming two -stage stochastic programming

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The submodularity of two-stage stochastic maximum-weight independent set problems

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THEORETICAL COMPUTER SCIENCE 2022年 937卷 50-62页

作者： Li, Min Xiao, Hao Liu, Qian Zhou, Yang Shandong Normal Univ Sch Math & Stat Jinan 250014 Peoples R China

In this paper, we extend the maximal independent set problem to two-stage stochastic case: given an independence system associated with one deterministic weight function and a random weight function, the goal is to find two nonoverlapping independent subsets from these two stages with the maximum total weight. In this paper, we study the sub -modularity of three kinds of two-stage independent set problems with max-weight. When the independent set problem is a matroid constraint, we can show its submodularity. How-ever, neither submodular nor supermodular maximization problem can be obtained for the knapsack independent set problem by designing a counterexample. At last, we show that the robust two-stage stochastic maximum-weight uniform matroid problem can be formu-lated as a gamma-submodular problem with cardinality constraint and also give a lower bound for gamma.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Submodularity two -stage stochastic programming Matroid Knapsack

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Multi-facility aggregate production planning with prosumer microgrid: A two-stage stochastic program

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JOURNAL OF CLEANER PRODUCTION 2022年 367卷

作者： Islam, Sayed Rezwanul Novoa, Clara Jin, Tongdan Texas State Univ Ingram Sch Engn San Marcos TX 78666 USA

The U.S. industries accounted for 37% of the wind turbine capacity installed in 2020 and corporate solar pur-chases have totaled $22 billion over the last 10 years. However, affordability and intermittency of renewable generation are still the main obstacles for firms to power their operations using wind and solar energy. Aggregate production planning models that incorporate onsite renewable energy (APPMs-RE) are the state-of-the-art to facilitate renewable adoption. A large number of APPMs are available in the literature, but renewables-based APPMs are still inadequately investigated. This paper proposes a novel APPM-RE because it optimizes wide-ranging RE decisions such as microgrid capacity, energy storage, prosumer energy transactions, and demand response along with production, machine usage, and workforce levels to minimize cost. The model is a two-stage stochastic program considering uncertainties in product demand, labor and machine capacity, and power gen-eration. The research goals are to (1) investigate the feasibility of decarbonizing the production, transportation, and warehousing operations, (2) examine the system affordability under practical hourly load requirements, (3) assess the cost-benefit of a prosumer energy transaction mechanism (PETM), (4) identify the effect in cost and microgrid capacity of time-of-use tariff, and (5) demonstrate the suitability of a two-stage stochastic program-ming model. The numerical experiments relying on climate analytics of six U.S. cities represent a broad scope of climate conditions. The managerial insights derived from this study are: (1) renewable microgrids with PETM may attain net-zero carbon operations with an affordable levelized cost of energy, and (2) time-of-use stimulates more adoption of solar generation than the flat rate.

关键词： two -stage stochastic programming Aggregate production planning Energy prosumer Climate data analytics Microgrid sizing Time-of-use

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stochastic energy community trading model for day-ahead and intraday coordination when offering DER?s reactive power as ancillary services

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SUSTAINABLE ENERGY GRIDS & NEtwoRKS 2022年 32卷

作者： Garcia-Munoz, Fernando Teng, Fei Junyent-Ferre, Adria Diaz-Gonzalez, Francisco Corchero, Cristina Univ Politecn Cataluna ETS Engn Ind Barcelona Dept Engn Elect Avinguda Diagonal 647 Pl 2 Barcelona 08028 Spain Imperial Coll London Dept Elect & Elect Engn London England IREC Catalonia Inst Energy Res C Jardins Dones Negre 1 Pl 2A St Adria Del Besos 08930 Spain Univ Politecn Catalunya BarcelonaTech Dept Stat & Operat Res Jordi Girona 1-3 Barcelona 08034 Spain

A two-stage stochastic programming energy trading model is presented in this article to measure the distributed energy resources' capability to provide reactive power as ancillary services from an energy community to the distribution system operator. The formulation proposed models the day-ahead and the intraday markets as first and second-stage decisions, respectively, using the second-order cone relaxation of the optimal power flow to represent the network limitations. In addition, the model considers that the energy community trades energy operating under a collaborative scheme and minimizing the global cost. Likewise, the formulation (i) includes community batteries to study the effect on the total cost, (ii) identifies the extra energy charged and discharged by the agents' batteries to face the uncertainty related to the intraday market, as an agents' flexibility service for the community, and (iii) prevents the simultaneous buying and selling of energy in the local energy market by an agent. The model has been programmed in Python-Pyomo and tested in three radial distribution systems under three different scenarios showing that the DERs can (i) self-satisfy the reactive power demand, (ii) provide reactive power to the DSO, and (iii) decrease the community cost significantly in an eventual ancillary services market.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Peer -to -peer energy trading Local energy markets Smart grids Reactive power Ancillary services two -stage stochastic programming

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Global sensitivity analysis and stochastic optimization of multi-energy complementary distributed energy system considering multiple uncertainties

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JOURNAL OF CLEANER PRODUCTION 2023年第1期389卷

作者： Zhang, Jiqiang Zhu, Li Wang, Yue Sun, Yong Yan, Zhexing Zhou, Bo Jiangxi Normal Univ Coll City Construct Nanchang 330200 Peoples R China Tianjin Univ Sch Architecture Tianjin 300072 Peoples R China Asia Pacific Econ Cooperat APEC Natl Energy Adm NE APEC Sustainable Energy Ctr Tianjin 300072 Peoples R China Tianjin Univ Sch Architecture Tianjin 300072 Peoples R China

Multiple uncertainties exist in the planning and design of multi-energy complementary distributed energy system (DES). In order to solve this problem, a more complete framework of two-stage stochastic programming (TSP) approach for optimal multi-energy complementary DES planning and design under multiple uncertainties is proposed. The developed TSP model is formulated as a mixed integer linear programming, which is intended to minimize the equivalent annual cost (EAC) of the multi-energy complementary DES. Probability scenarios of key uncertain parameters selected by treed Gaussian process method for the TSP model are generated and reduced using discrete approximations of probability distributions method and random vector sampling method. The developed method framework is applied to a case study high-rise office building in planning stage to illustrate the TSP model's output. And multiple evaluation indicators including configuration, economy, energy and envi-ronment are used to compare and analyze the optimal schemes obtained by deterministic model and TSP model under different building load scenarios. The results show that of the 26 uncertain parameters considered only 7 are selected as the key parameters for the TSP model in this paper. EAC of the optimal multi-energy comple-mentary DES may be overestimated if without considering key uncertain parameters. Thus, the deterministic optimization practices and the cost estimates resulting from them can be considered unreliable. Moreover, the multi-energy complementary DES would want to increase CO2 emission to achieve better economic performance. Finally, the energy share distribution of all scenarios in the stochastic model provides more reliable and more accurate information for decision-makers.

关键词： Distributed energy system Multi -energy complementary Multiple uncertainties Global sensitivity analysis two -stage stochastic programming Scenario generation and reduction

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Dynamic vehicle routing problem for flexible buses considering stochastic requests*

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2023年第1期148卷

作者： Ma, Wanjing Zeng, Lin An, Kun Tongji Univ Urban Mobil Inst Shanghai Peoples R China Tongji Univ Key Lab Rd & Traff Engn Minist Educ 4800 Caoan Rd Shanghai 201804 Peoples R China

Flexible buses provide on-demand services to one or more local communities in a specific geographical area. Bus routes can be adjusted dynamically according to real-time passenger demand in a cost-effective manner. This study investigated the dynamic bus-routing problem considering stochastic future passenger demand. A two-stage stochastic programming model was formulated to minimise the total vehicle travel time cost and penalty for rejecting requests. A rolling horizon scheme was adopted to handle the dynamic changes in passenger requests and vehicle routes. A vector-similarity-based clustering and adaptive large neighbourhood searching (VSC-ALNS) algorithm was developed to solve this problem. Vehicles and passengers were matched and clustered into groups based on vector similarity, and vehicle routes were generated using an adaptive large-neighbourhood search algorithm for each cluster. The effectiveness of the proposed method was evaluated in four cases with different demand intensities using Shanghai taxi order data. The results indicate that flexible buses are more suitable for moderate demand cases, ranging from 20 to 50 requests per square kilometre per hour.

关键词： Flexible bus Dynamic routing Passenger -vehicle matching two -stage stochastic programming Adaptive large neighbourhood search

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A risk-based decision-making scheme for short-sea liner fleet renewal to achieve carbon reduction targets

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RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT 2024年 54卷

作者： Zhao, Yuzhe Ma, Yiji Peng, Zhongxiu Zhou, Jingmiao Dalian Maritime Univ Collaborat Innovat Ctr Transport Studies Dalian 116026 Peoples R China Dalian Univ Foreign Languages Business Sch Dalian 116044 Peoples R China

This paper presents a green fleet renewal decision model for carbon reduction technologies in the short and medium-term planning horizon. The objective is to explore the commercial decisions over green fleet renewal made by short-sea liner shipping companies in response to the carbon reduction targets set by the International Maritime Organization. To address the environmental constraints and uncertainty surrounding operational demand and fuel prices, a two-stage stochastic programming model was developed. This model integrates various factors including ship buying and selling, retrofitting, operation area allocation, and speed determination, intending to maximize expected profits. When it comes to fleet renewal issues involving investments in carbon reduction technologies, the conditional value at risk was utilized to manage the risk of bankruptcy. The study also examines the relationship between bankruptcy risk and expected profit, offering time- and risk-related strategies for liner shipping companies operating in short seas.

关键词： Fleet renewal problem two -stage stochastic programming Green ships Carbon emission reduction Conditional value at risk

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