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An efficient interactive framework for improving resilience of power-water distribution systems with multiple privately-owned microgrids

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年 116卷 105550-000页

作者： Najafi, Javad Peiravi, Ali Anvari-Moghaddam, Amjad Guerrero, Josep. M. Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Razavi Khorasan Iran Aalborg Univ Dept Energy Technol Aalborg Denmark

Resilience improvement of power distribution networks against natural disasters is an important problem. Water network similar to other important infrastructures depends on power networks. In this paper, resilience improvement is defined as increasing the users' accessibility to water and power after natural disasters. Microgrids with appropriate operation can provide energy to restore disconnected loads in distribution networks. In the proposed interactive framework, a stochastic energy management program for microgrids is designed that not only determines the amount of energy can be delivered to distribution systems, but also considers the reliability of local loads during emergency conditions. Each microgrid provides a list of bid-quantity energy blocks to the distribution system operator (DSO) during the emergency period. Then, the DSO chooses the best plan to restore disconnected loads considering inaccessibility values to power and water and also the damage of power and water distribution networks. Demand response actions in microgrids are also considered as effective tools for the energy management program, and their impact on the distribution system resilience is investigated. The proposed model is tested on the modified IEEE 33-bus distribution system with multiple microgrids, and the effectiveness of the proposed method is validated accordingly.

关键词： Microgrids Natural disasters Resilience stochastic linear programming Water network

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Volumetric Barrier Cutting Plane Algorithms for stochastic linear Semi-Infinite Optimization

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IEEE ACCESS 2020年 8卷 4995-5008页

作者： Alzalg, Baha Gafour, Asma Alzaleq, Lewa Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Univ Jordan Dept Math Amman 11942 Jordan Washington State Univ Dept Math & Stat Pullman WA 99164 USA

In this paper, we study the two-stage stochastic linear semi-infinite programming with recourse to handle uncertainty in data defining (deterministic) linear semi-infinite programming. We develop and analyze volumetric barrier cutting plane interior point methods for solving this class of optimization problems, and present a complexity analysis of the proposed algorithms. We establish our convergence analysis by showing that the volumetric barrier associated with the recourse function of stochastic linear semi-infinite programs is a strongly self-concordant barrier and forms a self-concordant family on the first-stage solutions. The dominant terms in the complexity expressions obtained in this paper are given in terms of the problem dimension and the number of realizations. The novelty of our algorithms lies in their ability to kill the effect of the radii of the largest Euclidean balls contained in the feasibility sets on the dominant complexity terms.

关键词： Semi-infinite programming stochastic linear programming interior-point methods volumetric barrier cutting plane

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Container fleet renewal considering multiple sulfur reduction technologies and uncertain markets amidst COVID-19

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JOURNAL OF CLEANER PRODUCTION 2021年 317卷 128361-128361页

作者： Zhao, Yuzhe Ye, Jiajun Zhou, Jingmiao Dalian Maritime Univ Collaborat Innovat Ctr Transport Studies Dalian Peoples R China Dalian Univ Foreign Languages Business Sch Dalian Peoples R China

The onset of 2020 is marked by stricter restrictions on maritime sulfur emissions and the spread of Coronavirus Disease 2019 (COVID-19). In this background, liner companies now face the challenge to find suitable sulfur reduction technologies, make reasonable decisions on fleet renewal, and prepare stable operation plans under the highly uncertain shipping market. Considering three sulfur reduction technologies, namely, fuel-switching, scrubber, and liquefied natural gas (LNG) dual-fuel engine, this paper develops a robust optimization model based on two-stage stochastic linear programming (SLP) to formulate a decision plan for container fleet, which can deal with various uncertainties in future: freight demand, ship charter rate, fuel price, retrofit time and Sulfur Emission Control Area (SECA) ratio. The main decision contents include ship acquisition, ship retrofit, ship sale, ship charter, route assignment, and speed optimization. The effectiveness of our plan was verified through a case study on two liner routes from the Far East to Northwest America, operated by COSCO Shipping Lines. The results from SLP model show that large-capacity fuel-switching ships and their LNG dual-fuel engine retrofits should be included in the long-term investment and operation plan;slow-steaming is an important operational decision for ocean liner shipping;if the current SECA boundary is not further expanded or the sulfur emission restrictions not further tightened, the scrubber ship will have no advantage in investment cost and operation. However, considering the probabilities of more flexible scenarios, the results from the robust model suggest that it is beneficial to install scrubber on medium-capacity fuel-switching ships, and carry out more LNG dual-fuel engine retrofits for large-capacity fuel-switching ships. Compared with SLP, this robust strategy greatly reduces sulfur emissions while slightly pushing up carbon emissions.

关键词： Maritime fleet renewal problem (MFRP) Sulfur reduction technologies stochastic linear programming Robust optimization Sulfur emission control area (SECA)

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Resilience improvement planning of power-water distribution systems with multiple microgrids against hurricanes using clean strategies

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JOURNAL OF CLEANER PRODUCTION 2019年 223卷 109-126页

作者： Najafi, Javad Peiravi, Ali Anvari-Moghaddam, Amjad Guerrero, Josep M. Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Razavi Khorasan Iran Aalborg Univ Dept Energy Technol Aalborg Denmark

This paper proposes a comprehensive planning framework including a main problem and two sub-problems to enhance the resilience of power distribution network (PDN) and water distribution network (WDN) with multiple microgrids against hurricanes. The main problem which is formulated in stochastic programming aims to minimize the investment cost of resilience improvement strategies and the expected inaccessibility values of loads to power and water under hurricanes. Line hardening in PDN, upgrading the energy storage size in microgrids and water tanks in WDN are considered as three clean candidate strategies. In analyzing each scenario of the main problem, the microgrids which are connected to the PDN are modeled as emergency sources through the first stochastic sub -problem that can restore disconnected loads and water pumps. Water pumps as critical loads are equipped with emergency generators with limited fuel capacity. If there are some water pumps which cannot be restored in each scenario of the main problem, their emergency generators will be scheduled with the second subproblem of the model. The proposed model is tested on the modified IEEE 33-bus PDN with multiple microgrids and a designed WDN, and the effectiveness of the proposed method is validated accordingly. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Microgrids Resilience improvement planning stochastic linear programming Power network Water network

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Note on "A new equivalent transformation for interval inequality constraints of interval linear programming"

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FUZZY OPTIMIZATION AND DECISION MAKING 2019年第2期18卷 259-262页

作者： Li, Dechao Shi, Jiaheng Huang, Hongying Zhejiang Ocean Univ Sch Math Phys & Informat Sci Zhoushan 316000 Peoples R China Key Lab Oceanog Big Data Min & Applicat Zhejiang Zhoushan 316022 Peoples R China

This note provides a counterexample to demonstrate some flaws in a recent paper by Chen et al. It pinpoints the logic error in the proof of Theorem 5.2 and discusses some remedial works.

关键词： Interval linear programming Modeling the interval uncertainty Uniform distribution stochastic linear programming

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About One Approach to the Planning in Retail with the stochastic Parameters 15

About One Approach to the Planning in Retail with the Stocha...

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15th International Asian School-Seminar on Optimization Problems of Complex Systems (OPCS)

作者： Novikov, Artem Sobolev Inst Math Novosibirsk Russia

ISBN: (纸本)9781728129860

Retail is one of the largest industries for financial investments in Russia. There are various mathematical descriptions for the development of retail projects. Earlier in Ill the researchers considered the resource region development model and a corresponding linear stochastic programming problem, where the budget constraints are assumed to vary in a random manner at specified interval;and the methods of its solving. In this paper, we propose new models for planning retail investment projects related to carrying out promo efficiency in the retail chain. As well as in In these models are based on linear stochastic programming problems, where the dimension of the problems increases essentially, and the stochastic parameters appear in market behaviour. To solve this problem, we put forward the method based on its reduction to the deterministic one. For the numerical check of the algorithms we use the data on transactions of the LLC NSK Holdi.

关键词： modelling of the investment projects retail stochastic linear programming forecasting

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A Dynamic stochastic Optimization for Recharging Plug-In Electric Vehicles

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IEEE TRANSACTIONS ON SMART GRID 2018年第5期9卷 4154-4161页

作者： Liu, Siyan Etemadi, Atnir H. George Washington Univ Dept Elect & Comp Engn Washington DC 20052 USA

This paper presents a recharging scheme for plug-in (hybrid) electric vehicles. Despite their many advantages such as reducing carbon footprint, lower fuel cots, and high performance, uncoordinated recharging of electric vehicles in a high-penetration system can increase system peak load and create new peaks in the demand profile, hence, reducing system reliability and operational integrity. To optimize electric vehicle recharging costs and prevent such reliability problems, a dynamic stochastic optimization method is proposed that formulates a stochastic linear programming approach taking into account load, electricity pricing, and renewable energy generation uncertainties, and solves the day-ahead problem in an offline fashion. A second online stage is also proposed that uses offline solutions, collects real-time system data, and adjusts recharging schedules to obtain a better recharging scheme once system uncertainties are revealed. The proposed method is robust to variations in different stochastic parameters, has a low communication requirement, and benefits both users and the power utility. Recharging system structure, data models, and mathematical formulation of the proposed method are presented. Results demonstrate that unlike other recharging schemes, the proposed method does not increase system peak, does not create new peaks, and fills the valleys of demand profile to optimize power system operations.

关键词： Electric vehicle recharging schemes stochastic linear programming

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Benders decomposition with special purpose method for the sub problem in lot sizing problem under uncertain demand

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OPERATIONS RESEARCH PERSPECTIVES 2019年 6卷

作者： Witthayapraphakorn, Aphisak Charnsethikul, Peerayuth Kasetsart Univ Ind Engn Dept 50 Ngam Wong Wan Rd Bangkok 10900 Thailand

We propose herein the application of Benders decomposition with stochastic linear programming instead of the mix integer linear programming (MILP) approach to solve a lot sizing problem under uncertain demand, particularly in the case of a large-scale problem involving a large number of simulated scenarios. In addition, a special purpose method is introduced to solve the sub problem of Benders decomposition and reduce the processing time. Our experiments show that Benders decomposition combined with the special purpose method (BCS) requires shorter processing times compared to the simple MILP approach in the case of large-scale problems. Furthermore, our BCS approach shows a linear relationship between the processing time and the number of scenarios, whereas the MILP approach shows a quadratic relationship between those variables, indicating that our approach is suitable in solving such problems.

关键词： Benders decomposition stochastic linear programming Large-scale problem Lot sizing problem Uncertain demand

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About One Approach to the Planning in Retail with the stochastic Parameters

About One Approach to the Planning in Retail with the Stocha...

引用

International Asian School-Seminar Optimization Problems of Complex Systems

作者： Artem Novikov Sobolev Inst. of Math.

ISBN: (纸本)9781728129877

Retail is one of the largest industries for financial investments in Russia. There are various mathematical descriptions for the development of retail projects. Earlier in [1] the researchers considered the resource region development model and a corresponding linear stochastic programming problem, where the budget constraints are assumed to vary in a random manner at specified interval;and the methods of its solving. In this paper, we propose new models for planning retail investment projects related to carrying out promo efficiency in the retail chain. As well as in [1], these models are based on linear stochastic programming problems, where the dimension of the problems increases essentially, and the stochastic parameters appear in market behaviour. To solve this problem, we put forward the method based on its reduction to the deterministic one. For the numerical check of the algorithms we use the data on transactions of the LLC NSK Holdi.

关键词： Modelling of the investment projects Retail stochastic linear programming Forecasting Retail stores stochastic programming stochastic models stochastic Investments development model

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Optimal Scheduling of Frequency Services Considering a Variable Largest-Power-Infeed-Loss

Optimal Scheduling of Frequency Services Considering a Varia...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Badesa, Luis Teng, Fei Strbac, Goran Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

ISBN: (纸本)9781538677032

Low levels of inertia due to increasing renewable penetration bring several challenges, such as the higher need for Primary Frequency Response (PFR). A potential solution to mitigate this problem consists on reducing the largest possible power loss in the grid. This paper develops a novel modelling framework to analyse the benefits of such approach. A new frequency-constrained stochastic Unit Commitment (SUC) is proposed here, which allows to dynamically reduce the largest possible loss in the optimisation problem. Furthermore, the effect of load damping is included by means of an approximation, while its effect is typically neglected in previous frequency-secured-UC studies. Through several case studies, we demonstrate that reducing the largest loss could significantly decrease operational cost and carbon emissions in the future Great Britain's grid.

关键词： Frequency services stochastic linear programming unit commitment wind energy

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