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4th Energy Conversion and Economics Annual Forum, ECE Forum 2024

作者： Wang, Yufan Wu, Song Gao, Hongjun He, Shuaijia College of Electrical Engineering Sichuan University Sichuan Province Chengdu610065 China

ISBN: (纸本)9781837242627

In this study, we present a stochastic planning model for the planning and operation of a grid-interactive energy hub. The model emphasises demand response (DR) and Vehicle-to-Grid (V2G) technology. We explored the behavioural model of electric vehicles (EVs) to achieve optimal planning, energy efficiency improvement, and optimal interaction with the grid for energy hubs by simulating the impact of EVs' one-day charging and discharging behaviour on energy hub planning and operation, in conjunction with the construction of mathematical models for photovoltaic (PV), combined heat and power unit (CHP), and absorption chiller (AC) equipment. Through model optimisation, we analyse the operation of the energy hub under different dispatch schemes. The results show that the integrated consideration of DR and EV reverse discharge can reduce the investment cost of the energy hub equipment by 2.6%, improve the energy utilisation efficiency, and facilitate the 'peak shaving and valley filling' of the grid. The results provide a theoretical basis and practical guidance for the planning and operation of energy hubs. © The Institution of Engineering & Technology 2024.

关键词： stochastic programming

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Developing a national pandemic vaccination calendar under supply uncertainty

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2024年 124卷

作者： Karakaya, Sirma Balcik, Burcu Ozyegin Univ Ind Engn Dept Nisantepe Mah Orman Sk TR-34794 Istanbul Turkiye

During the COVID-19 pandemic, many countries faced challenges in developing and maintaining a reliable national pandemic vaccination calendar due to vaccine supply uncertainty. Deviating from the initial calendar due to vaccine delivery delays eroded public trust in health authorities and the government, hindering vaccination efforts. Motivated by these challenges, we address the problem of developing a long-term national pandemic vaccination calendar under supply uncertainty. We propose a novel two-stage mixed integer programming model that considers critical factors such as multiple doses, varying dosing schemes, and uncertainties in vaccine delivery timing and quantity. We present an efficient aggregation-based algorithm to solve this complex problem. Additionally, we extend our model to allow for dynamic adjustments to the vaccine schedule in response to mandatory policy changes, such as modifications to dose intervals, during ongoing vaccinations. We validate our model based on a case study developed by using real COVID-19 vaccination data from Norway. Our results demonstrate the advantages of the proposed stochastic optimization approach and heuristic algorithm. We also present valuable managerial insights through extensive numerical analysis, which can aid public health authorities in preparing for future pandemics.

关键词： Operations research for pandemic response Vaccine COVID-19 Scheduling stochastic programming

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Value of sorting and recovery in post-disaster relief aid distribution

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2024年 122卷

作者： Alegoz, Mehmet Acar, Muge Salman, F. Sibel Eskisehir Tech Univ Dept Ind Engn TR-26555 Eskisehir Turkiye Koc Univ Dept Ind Engn TR-34450 Istanbul Turkiye Eskisehir Tech Univ Dept Ind Engn 2 Eylul Campus TR-26555 Eskisehir Turkiye

In-kind donations gathered from the public after a disaster typically consist of an unknown and disorganized composition of both "useful"and "useless"items. Sending the donations directly to the affected people without any pre-processing leads to not only extra shipment and handling costs but also congestion in the disaster areas, and even chaos in local distribution. Motivated by this fact, we investigate the effect of relief aid sorting and subsequent recovery of items that do not fulfill immediate needs under demand, donation quantity, and donation type uncertainties. To this end, we propose a supply network configuration with sorting centers for pre-processing and optimize it by a three-stage stochastic programming model. We compare the case of the sorted donations with the case where donations are directly sent to points of distribution to victims. We apply the proposed model to the Istanbul earthquake case under different parameter settings and derive various managerial insights. We observe that sorting the donated relief aid items and sending only the useful ones to disaster victims may decrease the expected total cost, in addition to some intangible benefits, but at the same time may increase the expected time of the deliveries. However, it is possible to cope with this response time deterioration by increasing the workforce level at the sorting centers with an acceptable additional cost.

关键词： Relief aid sorting Relief aid supply chain Reverse logistics stochastic programming Disaster preparedness and response

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Multi-echelon green open-location-routing problem: A robust-based stochastic optimization approach

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SCIENTIA IRANICA 2021年第2期28卷 985-1000页

作者： Vakili, R. Shirazi, M. Akbarpour Gitinavard, H. Kharazmi Univ Dept Econ Tehran Iran Amirkabir Univ Technol Dept Ind Engn & Management Syst 424 Hafez Ave Tehran Iran

In recent years, it has been proven that promoting and observing environmental competence could play an instrumental role in enhancing companies/countries' industries in terms of sustainable development. In this study, a Green Open Location-Routing Problem with Simultaneous Pickup and Delivery (GOLRPSPD) is considered to minimize general costs. In addition to the significance of cost minimization, the objective function aims at promoting environmental competency in terms of the costs of CO2 emissions and fuel consumptions. Meanwhile, in a complex situation, using precise information could yield unreliable results in which considering uncertainty theories could prevent data loss. In this respect, this study assumed the pickup and delivery demand and travel time as probabilistic parameters. To address the issue, a robust stochastic programming approach was developed to reduce the deviations of imprecise information. Moreover, the proposed approach was applied based on five scenarios to decide the best decision in different situations. In addition, a practical example of the multi-echelon open-location-routing model was provided to represent the feasibility and applicability of the presented robust stochastic programming approach. Finally, comparative and sensitivity analyses were carried out to demonstrate the validity of the proposed approach and, also, to point out the robustness and sensitiveness of the obtained results regarding some significant parameters. (C) 2021 Sharif University of Technology. All rights reserved.

关键词： Open-location-routing problem Green logistic stochastic programming Robust optimization Uncertainty

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The spot and balancing markets for electricity: open- and closed-loop equilibrium models

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COMPUTATIONAL MANAGEMENT SCIENCE 2022年第2期19卷 309-346页

作者： Boomsma, Trine Krogh Pineda, Salvador Heide-Jorgensen, Ditte Molgard Univ Copenhagen Dept Math Sci Univ Pk 5 DK-2100 Copenhagen O Denmark Univ Malaga Dept Elect Engn Edif Ingn Off 2-085DC Doctor Ortiz Ramos S-N E-29071 Malaga Spain Bankdata Erritso Bygade 102 DK-7000 Fredericia Denmark

The increasing penetration of inflexible and fluctuating renewable energy generation is often accompanied by a sequential market setup, including a day-ahead spot market that balances forecasted supply and demand with an hourly time resolution and a balancing market in which flexible generation handles unexpected imbalances closer to real-time and with a higher time resolution. Market characteristics such as time resolution, the time of market offering and the information available at this time, price elasticities of demand and the number of market participants, allow producers to exercise market power to different degrees. To capture this, we study oligopolistic spot and balancing markets with Cournot competition, and formulate two stochastic equilibrium models for the sequential markets. The first is an open-loop model which we formulate and solve as a complementarity problem. The second is a closed-loop model that accounts for the sequence of market clearings, but is computationally more demanding. Via optimality conditions, the result is an equilibrium problem with equilibrium constraints which we solve by an iterative procedure. When compared to the closed-loop solution, our results show that the open-loop problem overestimates the ability to exercise market power unless the market allows for speculation. In the presence of a speculator, the open-loop formulation forces spot and balancing market prices to be equal in expectation and indicates substantial profit reductions, whereas speculation has less severe impact in the closed-loop problem. We use the closed-loop model to further analyse market power issues with a higher time resolution and limited access to the balancing market.

关键词： Electricity markets Market power stochastic programming Complementarity modelling Cournot competition

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From Probabilistic PV Power Forecasting to stochastic Programing: a Method for Microgrid Planning Under Uncertainty

From Probabilistic PV Power Forecasting to Stochastic Progra...

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Workshop on Blockchain for Renewables Integration (BLORIN)

作者： Mathieu, Valentin Pichenot, Gregoire Quoc Tuan Tran Univ Grenoble Alpes CEA LITEN INES Le Bourget Du Lac France

ISBN: (纸本)9781665472494

Recently, probabilistic PV forecasting emerged at a good level of maturity, questioning its role and potential in microgrid planning. Forecasts can take various forms but this paper focuses firstly on a procedure to obtain empirical distribution from quantiles. Secondly, correlation structure of studied variables is explored using copula theory. After addressing scenario Monte-Carlo generation and reduction methods, the interest of stochastic programming using created trajectories is discussed.

关键词： PV probabilistic forecasting scenario generation scenario reduction stochastic programming uncertainty microgrid

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Parallel Identical Machines Scheduling to Minimize the Maximum Inter-completion Time with Uncertain Processing Time 10th

Parallel Identical Machines Scheduling to Minimize the Maxim...

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10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM)

作者： Sui, Yang Wang, Zhaojie Shandong Univ Sci & Technol Coll Energy & Min Engn Qingdao Peoples R China Donghua Univ Glorious Sun Sch Business & Management Shanghai Peoples R China

Motivated by parallel machines scheduling in practice that receive unplanned urgent job under uncertain environment, and it usually requires a response as soon as possible since its high-priority. This paper considers the response time to urgent job in a worst-case as an evaluation indicator. To the best of our knowledge, this paper is the first to study a parallel identical machine scheduling problem, which is to minimize the largest waiting time of an urgent job with the uncertain processing time of regular jobs. The objective of this problem is depicted to minimize the inter-completion time, that is, the maximum difference of the completion times between any two consecutively completed jobs. We first establish a stochastic programming model, and propose a scenario-reduction based sample average approximation method to solve this uncertain problem. Copyright (C) 2022 The Authors.

关键词： Scheduling Urgent job Inter-completion time Parallel machines stochastic programming

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Column-and-constraint generation approach to partition-based risk-averse two-stage stochastic programs

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ANNALS OF OPERATIONS RESEARCH 2025年 1-31页

作者： Lee, Jongheon Lee, Kyungsik Incheon Natl Univ Dept Ind & Management Engn 119 Acad Ro Incheon 22012 South Korea Seoul Natl Univ Dept Ind Engn 1 Gwanak Ro Seoul 08826 South Korea

Typically, two-stage stochastic programs have been modeled and solved based on the finite support assumption, but the large number of scenarios makes it hard to solve, and there also are potential risks of inaccurate estimation of underlying distribution. In this paper, to mitigate the drawbacks, we present a novel risk-averse two-stage stochastic program with finite support, which we call partition-based risk-averse two-stage stochastic program. In the program, a set of scenarios is partitioned into several groups, and the second-stage cost is defined as the expectation of risk levels for all of the groups. In particular, the conditional value-at-risk is considered as a risk measure for each group, and so the risk level of the model is affected by a quantile parameter or a partition of a given set of scenarios. In order to solve the model exactly for a given partition, a column-and-constraint generation algorithm is proposed. In addition, a scenario partitioning algorithm to enable the risk level of the model to be close to a given target is devised, and partitioning schemes for combining it with the proposed column-and-constraint generation algorithm are proposed. Extensive numerical experiments were performed that demonstrated the effectiveness of the proposed partitioning schemes and the efficiency of the proposed solution approach.

关键词： stochastic programming Risk-averse stochastic program Scenario partitioning Column-and-constraint generation Partitioning scheme

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Evaluating a stochastic-programming-Based Bidding Model for a Multireservoir System

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IEEE TRANSACTIONS ON POWER SYSTEMS 2014年第4期29卷 1748-1757页

作者： Aasgard, Ellen K. Andersen, Gorild S. Fleten, Stein-Erik Haugstvedt, Daniel SINTEF Energy NO-7491 Trondheim Norway Steria Norway NO-0051 Oslo Norway Norwegian Univ Sci & Technol Dept Ind Econ & Technol Management NO-7491 Trondheim Norway

Hydropower producers need to schedule when to release water from reservoirs and participate in wholesale electricity markets where the day-ahead production is physically traded. A mixed-integer linear stochastic model for bid optimization and short-term production allocation is developed and tested through a simulation procedure implemented for a complex real-life river system. The stochastic bid model sees uncertainty in both spot market prices and inflow to the reservoirs. The same simulation procedure is also implemented for a practice-based deterministic heuristic method similar to what is currently used for bid determination in the industry, and the results are compared. The stochastic approach gives improvements in terms of higher obtained average price and higher total value than the deterministic alternative. It also performs well in terms of startup costs. In the presence of river flow travel delay, the practice-based method is even more outperformed by the stochastic model.

关键词： Bidding electricity markets hydro scheduling price taker reservoirs simulation stochastic programming

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stochastic resource leveling in projects with flexible structures

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COMPUTERS & OPERATIONS RESEARCH 2024年 169卷

作者： Li, Hongbo Zheng, Linwen Chen, Rui Zhang, Xianchao Shanghai Univ Sch Management Shanghai 200444 Peoples R China Jiaxing Univ Key Lab Med Elect & Digital Hlth Zhejiang Prov Jiaxing 314001 Peoples R China

In project management, efficient utilization of resources plays a key role in project success, and resource leveling is an effective technique to optimize resource usage. During project execution, there are often uncertainties that complicate resource leveling. Furthermore, existing research on resource leveling typically assumes a fixed project structure. However, this is not always the case in practice, because there may be a variety of optional technical solutions for some activities, leading to a flexible project structure. Therefore, considering both stochastic activity durations and flexible project structures, we propose and study the stochastic resource leveling problem with flexible project structures (SRLP-PS). The solution of the SRLP-PS is in the form of a scheduling policy. We design two algorithms for solving the NP-hard SRLP-PS: (a) an exact algorithm based on stochastic programming, in which we formulate a scenario-based non-linear stochastic programming model and linearize it into an equivalent deterministic mixed-integer linear programming model that can be directly solved by CPLEX;and (b) an improved differential evolution algorithm, which is equipped with several problem-specific components, such as two mutation operators balancing exploration and exploitation, initialization, and local improvement search. Extensive computational experiments on a large number of benchmark instances are performed to validate our algorithms, which are also compared with state-of-the-art meta-heuristics. The computational results reveal the effectiveness and competitiveness of our algorithms. We also analyze the value of stochastic information based on the exact algorithm and the meta-heuristics, respectively.

关键词： Project scheduling Resource leveling Flexible project structures stochastic activity durations stochastic programming Differential evolution algorithm

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