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Multi-energy microgrids: An optimal despatch model for water-energy nexus

SUSTAINABLE CITIES AND SOCIETY 2022年第0期77卷 103573-103573页

作者： Jalilian, Faezeh Mirzaei, Mohammad Amin Zare, Kazem Mohammadi-Ivatloo, Behnam Marzband, Mousa Anvari-Moghaddam, Amjad Univ Tabriz Fac Elect & Comp Engn Tabriz Iran Northumbria Univ Elect Power & Control Syst Res Grp Ellison Pl Newcastle Upon Tyne NE1 8ST Tyne & Wear England Aalborg Univ Dept Energy Technol Integrated Energy Syst Lab DK-9220 Aalborg Denmark

This paper proposes an integrated scheduling model for optimal despatch of cooling, heating, power, gas and water sources in an energy-water microgrid, where the microgrid operator participates in the power, heat, and gas markets and utilizes energy conversion facilities to meet various demands. Further, the role of water and energy storage systems (WESSs) and demand response program (DRP) is investigated on optimal scheduling of the combined cooling, heating, power, gas, and water-based microgrid. In addition, a multi-objective two-stage stochastic optimization model is adopted to minimize the total cost, including operating and emission costs and the amount of potable water extracted from water wells due to the uncertainties of electrical demand, wind power, and electricity market price. Moreover, the epsilon-constraint method and fuzzy satisfying approach are applied to obtain the optimal solution in the multi-objective problem. Ultimately, the simulation results confirm the advantages of simultaneous consideration of WESSs and DRP on the total cost of the proposed energy-water microgrid.

关键词： Energy-water nexus Multi-energy microgrid Energy storage systems Multi-objective optimization two-stage stochastic programming

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two-stage stochastic Max-Weight Independent Set Problems 1

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15th Annual International Conference on Combinatorial Optimization and Applications (COCOA)

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

ISBN: (数字)9783030926816

ISBN: (纸本)9783030926816;9783030926809

The two-stage stochastic maximum-weight independent set problem extends the classical independent set problem. Given an independent system associated with one deterministic weight function and a random weight function both defined over the same ground set, the problem is to select two nonoverlapping independent subsets, one in the first stage and the other in the second stage, whose union has the maximum total expected weight. In this paper, we show that this problem can be formulated as a submodular function maximization subject to a matroid constraint if the independent system is a matroid. Furthermore, we also show that the two-stage stochastic maximum-weight knapsack independent set problem is neither submodular nor supermodular maximization problem by designing a counterexample.

关键词： Submodular Matroid Knapsack two-stage stochastic programming

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two-stage stochastic program for disassembly lot-sizing under random ordering lead time

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IFAC-PapersOnLine 2022年第10期55卷 1363-1368页

作者： Ilhem Slama Oussama Ben-Ammar David Garcia Alexandre Dolgui LINEACT CESI campus de Lyon EuroMov Digital Health in Motion Univ Montpellier IMT Mines Ales Ales France IMT Atlantique LS2N-CNRS La Chantrerie 4 rue Alfred Kastler - B.P. 20722 44307 Nantes France

This study addresses disassembly lot-sizing that determines the ordering and disassembly schedules of end-of-life (EOL) products and subassemblies to satisfy items demands. A stochastic version with uncertain ordering lead time (OLT) is considered for the first time. Here, OLT represents the time elapsed between placing an order and receiving it (only an EOL product can be ordered). stochastic integer programming model is developed for the objective of minimizing the expected sum of setup, purchase, inventory and backlog costs. To test the performance of the proposed model, computational experiments were done on various test instances and are reported. The results show that the performance of the proposed model depends on the size of the ordering lead times, the number of periods and components.

关键词： Disassembly lot-sizing random ordering lead times two-stage stochastic programming

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Decision-Dependent Multiobjective Multiperiod stochastic Model for Parking Location Analysis in Sustainable Cities: Evidence from a Real Case

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JOURNAL OF URBAN PLANNING AND DEVELOPMENT 2022年第1期148卷 05021052-05021052页

作者： Aydin, Nezir Yildiz Tech Univ Dept Ind Engn TR-34349 Istanbul Turkey

Unorganized city growth causes traffic congestion, and, in return, this forces governments to invest in costly buildings such as public parking lots. The demand for parking spaces has further increased due to rapid population growth, especially in metropolitan areas. One solution to this problem is to locate new public parking lots within city centers so that car owners can use these facilities instead of on-street parking. In this study, a facility location and allocation scheme was engaged to determine the optimal number of and locations for public parking lots. A multiobjective, multiperiod, decision-dependent, two-stage, stochastic mathematical model was developed to fulfill the decision makers' aims via different objectives. In the model, three objectives were considered: minimizing total facility establishment and operational cost, minimizing average unsatisfied demand, and minimizing CO2 emissions. The proposed framework is the first in parking lot literature to address the multiobjectivity of decision-dependent demand within an uncertain environment. The weighted sum method was used to develop the multiobjective model, and two-stage stochastic programming was applied to manage the uncertainty. Hence, the proposed model satisfies critical gaps, predominantly in relation to the problem of parking lot location, and most importantly in creating sustainable cities. The results provide meaningful outcomes for decision makers in terms of optimizing unsatisfied demand, tackling CO2 emissions, and determining the optimal number and location of public parking lots. Furthermore, the robustness of the model was tested through sensitivity analyses.

关键词： Sustainable cities Uncertainty two-stage stochastic programming Multiobjective Mathematical model Parking lot Off-street parking Weighted sum

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Impact of implementing a price-based demand response program on the system reliability in security-constrained unit commitment problem coupled with wind farms in the presence of contingencies

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ENERGY 2022年 255卷

作者： Mansourshoar, Paria Yazdankhah, Ahmad Sadeghi Vatanpour, Mohsen Mohammadi-Ivatloo, Behnam Sahand Univ Technol Dept Elect Engn Tabriz Iran Sahand Univ Technol Renewable Energy Res Ctr Tabriz Iran Islamic Azad Univ Dept Elect Engn Ilkhchi Branch Ilkhchi Iran Univ Tabriz Fac Elect & Comp Engn Tabriz Iran Mugla Sitki Kocman Univ Elect & Elect Engn Dept Mugla Turkey

Large scale penetration of highly intermittent wind energy sources has caused new challenges to the reliable operation of power systems. To address these challenges, demand response program is considered as an efficient solution to manage shift-able loads. In this paper, the impact of demand response on power system reliability has been evaluated by developing a two-stage stochastic security constraint unit commitment that considers both the wind volatility and line outages at the same time. The allocation of ramping products and spinning reserves to cover these uncertainties has also been modeled. wind curtailment and load shedding are considered as alternative strategies, and an optimal exchange between them and the use of spinning reserves and flexible ramping products has been modeled in the objective function. To assess the system reliability, the expected load not served (ELNS) index was evaluated in different cases. The proposed scheme as a mixed-integer linear programming problem was solved by a scenario-based two-stage stochastic programming method. The IEEE test systems 6-bus, modified 24-bus, and 118-bus were examined numerically. The results show that the simultaneous consideration of demand response and flexible ramping product coordinated with wind energy has adequate flexibility to reduce the reliability index and system operational cost. (C) 2022 Published by Elsevier Ltd.

关键词： Security constrained unit commitment(SCUC) two-stage stochastic programming Demand response (DR) Wind energy intermittency Post contingency Reliability

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Day-ahead stochastic scheduling of integrated multi-energy system for flexibility synergy and uncertainty balancing

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ENERGY 2020年第0期196卷 117130-000页

作者： Turk, Ana Wu, Qiuwei Zhang, Menglin Ostergaard, Jacob Tech Univ Denmark DTU Ctr Elect Power & Energy CEE Dept Elect Engn DK-2800 Lyngby Denmark

Secure operation of the power system is challenged by the high level of uncertainty and fluctuation introduced by renewable energy sources. More flexibility is needed to cope with the uncertainty and improve the utilization of renewable energy. A prominent solution to provide flexibility, and simultaneously increase the efficiency of the system, is the integration of different energy sectors. This paper proposes a two-stage stochastic scheduling scheme of an integrated multi-energy system, which considers the wind power uncertainty and the synergy of different energy sectors to achieve the optimal economic operation of the whole system with minimum curtailment of wind power. In the first stage, energy and reserve scheduling of generating units is performed, while accommodation of wind power production is realized through reserves in the second stage. In the proposed scheme, the electric power system, natural gas system, and district heating system are coordinated to achieve more flexibility, both in the day-ahead and real-time stage. The stochasticity of the wind power uncertainty is represented by realistic scenarios with corresponding probabilities, which are obtained from a scenario generation algorithm based on historical observations taking into account the temporal correlation of wind power. The simulation results on a small-scale test system show that both, the economic efficiency and wind power utilization, have been improved with more flexibility and more reliable scenario set. It is shown, that the total system cost is reduced and reserves are optimized. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Integrated multi-energy system Temporal-correlated scenario set two-stage stochastic programming Wind power uncertainty

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Passive Beamforming and Information Transfer Design for Reconfigurable Intelligent Surfaces Aided Multiuser MIMO Systems

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2020年第8期38卷 1793-1808页

作者： Yan, Wenjing Yuan, Xiaojun He, Zhen-Qing Kuai, Xiaoyan Univ Elect Sci & Technol China Ctr Intelligent Networking & Commun Natl Lab Sci & Technol Commun Chengdu 611731 Peoples R China

This paper investigates the passive beamforming and information transfer (PBIT) technique for multiuser multiple-input multiple-output (Mu-MIMO) systems with the aid of reconfigurable intelligent surfaces (RISs), where the RISs enhance the primary communication via passive beamforming (P-BF) and at the same time deliver additional information by the on-off reflecting modulation (in which the RIS information is carried by the on/off state of each reflecting element). For the P-BF design, we propose to maximize the achievable user sum rate of the RIS-aided Mu-MIMO channel and formulate the problem as a two-step stochastic program. A sample average approximation (SAA) based iterative algorithm is developed for the efficient P-BF design of the considered scheme. To strike a balance between complexity and performance, we further propose a simplified P-BF algorithm by approximating the stochastic program as a deterministic alternating optimization problem. For the receiver design, the signal detection at the receiver is a bilinear estimation problem since the RIS information is multiplicatively modulated onto the reflected signals of the reflecting elements. To solve this bilinear estimation problem, we develop a turbo message passing (TMP) algorithm in which the factor graph associated with the problem is divided into two modules: one for the estimation of the user signals and the other for the estimation of the on-off state of each RIS element. The two modules are executed iteratively to yield a near-optimal low-complexity solution. Furthermore, we extend the design of the Mu-MIMO PBIT scheme from single-RIS to multi-RIS, by leveraging the similarity between the single-RIS and multi-RIS system models. Extensive simulation results are provided to demonstrate the advantages of our P-BF and receiver designs.

关键词： Optimization Receivers MIMO communication Wireless networks Estimation Array signal processing Approximation algorithms Reconfigurable intelligent surface (RIS) intelligent reflecting surface (IRS) large intelligent surface (LIS) passive beamforming and information transfer (PBIT) two-stage stochastic programming bilinear signal estimation turbo message passing (TMP)

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A Decomposition Algorithm for the two-stage Chance-Constrained Operating Room Scheduling Problem

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IEEE ACCESS 2020年 8卷 80160-80172页

作者： Najjarbashi, Amirhossein Lim, Gino J. Univ Houston Dept Ind Engn Houston TX 77204 USA

The required time for surgical interventions in operating rooms (OR) may vary significantly from the predicted values depending on the type of operations being performed, the surgical team, and the patient. These deviations diminish the efficient utilization of OR resources and result in the disruption of projected surgery start times. This paper proposes a two-stage chance-constrained model to solve the OR scheduling problem under uncertainty. The goal is to minimize the costs associated with OR opening and overtime as well as reduce patient waiting times. The risk of OR overtime is controlled using chance constraints. Numerical experiments show that the proposed model provides a better trade-off between minimizing costs and reducing solution variability when compared to two existing models in the literature. It is also shown that the three models converge as the overtime probability threshold approaches one. Moreover, it is observed that the individual chance constraints result in the opening of fewer rooms, lower waiting times, and shorter solution times when compared to that of joint chance constraints. A decomposition algorithm is applied that solves large test instances of the OR scheduling problem, that of which is known to be NP-hard. Strong valid inequalities are derived in order to accelerate the convergence speed. The proposed approach outperformed both a commercial solver and a basic decomposition algorithm after solving all test instances with up to 89 surgeries and 20 ORs in less than 48 minutes.

关键词： Chance constraints mixed-integer programming operating room scheduling two-stage stochastic programming uncertainty

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Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration

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IEEE TRANSACTIONS ON SMART GRID 2020年第2期11卷 1030-1043页

作者： Yao, Shuhan Wang, Peng Liu, Xiaochuan Zhang, Huajun Zhao, Tianyang Nanyang Technol Univ Interdisciplinary Grad Sch Singapore 639798 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Nanyang Technol Univ Energy Res Inst NTU Singapore 639798 Singapore

Mobile energy storage systems (MESSs) provide promising solutions to enhance distribution system resilience in terms of mobility and flexibility. This paper proposes a rolling integrated service restoration strategy to minimize the total system cost by coordinating the scheduling of MESS fleets, resource dispatching of microgrids, and network reconfiguration of distribution systems. The integrated strategy takes into account damage and repair to both the roads in transportation networks and the branches in distribution systems. The uncertainties in load consumption and the status of roads and branches are modeled as scenario trees using Monte Carlo simulation method. The operation strategy of MESSs is modeled by a stochastic multi-layer time-space network technique. A rolling optimization framework is adopted to dynamically update system damage, and the coordinated scheduling at each time interval over the prediction horizon is formulated as a two-stage stochastic mixed-integer linear program with temporal-spatial and operation constraints. The proposed model is verified on two integrated test systems, one is with Sioux Falls transportation network and four 33-bus distribution systems, and the other is the Singapore transportation network-based test system connecting six 33-bus distribution systems. The results demonstrate the effectiveness of MESS mobility to enhance distribution system resilience due to the coordination of mobile and stationary resources.

关键词： Microgrids stochastic processes Maintenance engineering Roads Optimization Energy storage Mobile energy storage microgrids fleet management rolling optimization two-stage stochastic programming resilience

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A practical assessment of risk-averse approaches in production lot-sizing problems

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第9期58卷 2581-2603页

作者： Alem, Douglas Oliveira, Fabricio Peinado, Miguel Carrion Ruiz Univ Edinburgh Sch Business Management Sci & Business Econ Grp 29 Buccleuch Pl Edinburgh EH8 9JS Midlothian Scotland Aalto Univ Dept Math & Syst Anal POB 11100 Aalto 00076 Finland Univ Castilla La Mancha Dept Elect Engn Ave Carlos III S-N Toledo 45071 Spain

This paper presents an empirical assessment of four state-of-the-art risk-averse approaches to deal with the capacitated lot-sizing problem under stochastic demand. We analyse two mean-risk models based on the semideviation and on the conditional value-at-risk risk measures, and alternate first and second-order stochastic dominance approaches. The extensive computational experiments based on different instances characteristics and on a case-study suggest that CVaR exhibits a good trade-off between risk and performance, followed by the semideviation and first-order stochastic dominance approach. For all approaches, enforcing risk-aversion helps to reduce the cost-standard deviation substantially, which is usually accomplished via increasing production rates. Overall, we can say that very risk-averse decision-makers would be willing to pay an increased price to have a much less risky solution given by CVaR. In less risk-averse settings, though, semideviation and first-order stochastic dominance can be appealing alternatives to provide significantly more stable production planning costs with a marginal increase of the expected costs.

关键词： lot-sizing two-stage stochastic programming risk-aversion CVaR semideviation first-order stochastic dominance second-order stochastic dominance

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