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An optimal capacity allocation method for integrated energy systems considering uncertainty

AIP ADVANCES 2023年第8期13卷

作者： Zhang, Yuliang Zhang, Jianguo Chen, Yujie Qingdao Huanghai Univ Coll Intelligent Mfg Qingdao 266427 Peoples R China

The randomness and fluctuation of wind power output will cause certain waste in capacity allocation of integrated energy system. Therefore, a robust chance constrained optimization model is proposed to solve the shortcomings of the traditional model in wind power output analysis, such as weak reliability and conservative results. First, the uncertainty of wind power output is analyzed. Second, a robust chance constrained optimization model combining stochastic programming and robust optimization is established to deal with the uncertainty of the output power of the integrated energy system objectively. Finally, the results are compared with the existing integrated energy system capacity configuration, and the validity of the model is verified. The results show that the robust chance constrained optimization model proposed in this paper can effectively reduce the capacity cost by 38.2% while ensuring the robustness of the system in wind power uncertainty analysis.

关键词： stochastic programming

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Considering Forward Electricity Prices for a Hydro Power Plant Risk Analysis in the Brazilian Electricity Market

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ENERGIES 2023年第3期16卷 1173页

作者： Lauro, Arthur Kitamura, Daniel Lima, Waleska Dias, Bruno Soares, Tiago Univ Fed Juiz de Fora Elect Energy Dept UFJF BR-36036330 Juiz De Fora Brazil Inst Syst & Comp Engn Technol & Sci Ctr Power & Energy Syst P-4200465 Porto Portugal

The Brazilian Power System is mainly composed of renewable generation from hydroelectric and wind. Hence, spot and forward electricity prices tend to represent the inherently stochastic nature of these resources, while risk management is a measure taken by agents, especially hydro power plants (HPPs) to hedge against deep financial losses. A HPP goal is to maximize its profit considering uncertainties in forward electricity prices, spot prices, and generation scaling factor (GSF) for years ahead. Therefore, the objective of this work is to simulate the real decision-making process of a HPP, where they need to have a perspective of the forward market and future spot price assessment to negotiate forward electricity contracts. To do so, the present work models the uncertainty in electricity forward prices via two-stage stochastic programming, assessing the benefits of the stochastic solution in comparison to the deterministic one. In addition, different risk aversion levels are assessed using conditional value at risk (CVaR). An important conclusion is that the results show that the greater the HPP risk aversion is, the greater the energy selling via electricity forward contracts. Moreover, the proposed model has benefits in comparison to a deterministic approach.

关键词： decision making under uncertainty electricity forward price stochastic programming risk management renewable energy sources

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Farmland allocation in the conversion from conventional to organic farming

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第3期311卷 1103-1119页

作者： Jahantab, Mahboubeh Abbasi, Babak Le Bodic, Pierre RMIT Univ Sch Accounting Informat Syst & Supply Chain Melbourne VIC 3000 Australia Monash Univ Fac Informat Technol Clayton Vic 3800 Australia

Organic farming enhances food quality and public health, and contributes to a more sustainable environment. Although certified organic farmland grew from 11 to 72.3 million hectares between 1999 and 2019, it constituted only 1.5 percent of the world's agricultural farmland in 2019. The main impediment to the conversion from conventional to organic farming is the financial difficulties that farmers experience during the transition period in terms of decrease in yield and increase in farming costs owing to transitional practices. Furthermore, uncertainty in crop price and yield may aggravate the adverse effects of transitional practices. This article presents a multi-period optimization model for the allocation of farmland among crops and agricultural practices which allows farmers to plan a transition to organic farming while incurring a bounded shortfall of income. We calibrate our model to represent a grower of corn and soybean in Iowa and, using a seemingly unrelated regression model, crops revenues are simulated and utilized in the numerical experiments. The results show that i) our optimized crop rotation pattern outperforms other policies in the agriculture industry, including monoculture and systematic crop rotation, and that ii) our gradual conversion plan mitigates the chance of profit shortfalls.& COPY;2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://***/licenses/by-nc-nd/4.0/ )

关键词： OR in agriculture Conversion to organic farming Farmland allocation stochastic programming Sustainable operations

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Budget allocation of food procurement for natural disaster response

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第2期311卷 754-768页

作者： Dang, Duc-Cuong Currie, Christine S. M. Onggo, Bhakti Stephan Chaerani, Diah Achmad, Audi Luqmanul Hakim Univ Southampton Southampton Business Sch Southampton SO171BJ England Univ Southampton Math Sci Southampton SO171BJ England Univ Padjadjaran Fac Math & Nat Sci Dept Math Sumedang 45363 Indonesia Univ Passau Chair Algorithms Intelligent Syst D-94032 Passau Germany

This paper studies a variant of the lot sizing problem that arises in the context of disaster management. In this problem, a fixed budget has to be allocated efficiently over multiple time periods to procure large quantities of a staple food that will be stored and later delivered to people affected by disaster strikes whose numbers are unknown in advance. Starting from the deterministic model where perfect infor-mation is assumed, different formulations to address the uncertainties are constructed: classical robust optimisation, risk-minimisation stochastic programming, and adjustable robust optimisation. Experiments conducted using data from West Java, Indonesia allow us to discuss the advantages and drawbacks of each method. Our methods constitute a toolbox to support decision makers with making procurement decisions and answering managerial questions such as which annual budget is fair and safe, or when storage peaks are likely to occur.& COPY;2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Humanitarian logistics Disaster management Procurement lot sizing Robust optimisation stochastic programming

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Optimal risk-driven operation of renewable-penetrated distribution network during natural-disasters: A resiliency-oriented analysis

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SUSTAINABLE CITIES AND SOCIETY 2023年 99卷

作者： Wen, Mingming Lv, Zhaoheng Mamonov, Konstantin Guangdong Ocean Univ Sch Management Zhanjiang 524088 Peoples R China Guangdong Coastal Econ Belt Dev Res Inst Zhanjiang 524088 Peoples R China OM Beketov Natl Univ Urban Econ Kharkiv 17 Marshal Bazhanov St UA-1002 Kharkiv Ukraine

The increasing penetration of renewable energy sources in distribution networks has brought new challenges in ensuring reliable and resilient operation during natural disasters. The proposed approach considers the uncertainties associated with renewable energy sources, natural disasters, and demand using scenario-based stochastic programming to minimize the expected operational cost of the distribution network. Due to the huge uncertainties related to renewable resources, an efficient risk analysis is applied to obtain a sense of the worst realizations of uncertainties using the downside risk constraints method. Besides, two types of demand response schemes (DRSs) are considered to prevent widespread blackouts in the distribution network. This study provides insights into the integration of renewable energy sources in distribution networks and highlights the importance of considering resiliency optimization of this networks. The effectiveness of the proposed approach is demonstrated through simulations on a 33-bus test distribution system, and the results show successful ride-through of the islanding hours with 100% risk reduction by only 2.91% increase in operation cost over the considered scenarios, while risks may still be present in other set of scenarios. Overall, this research contributes to the investigate the uncertainty-driven operational risks of renewable energy integration of resilient distribution network.

关键词： Renewable resources natural disasters resiliency-oriented operation stochastic programming downside risk constraints distribution network

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DATA-DRIVEN APPROXIMATION OF CONTEXTUAL CHANCE-CONSTRAINED stochastic PROGRAMS

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SIAM JOURNAL ON OPTIMIZATION 2023年第3期33卷 2248-2274页

作者： Rahimian, Hamed Pagnoncelli, Bernardo Clemson Univ Dept Ind Engn Clemson SC 29634 USA Univ Cote dAzur SKEMA Business Sch Lille France

Uncertainty in classical stochastic programming models is often described solely by independent random parameters, ignoring their dependence on multidimensional features. We describe a novel contextual chance-constrained programming formulation that incorporates features, and argue that solutions that do not take them into account may not be implementable. Our formulation cannot be solved exactly in most cases, and we propose a tractable and fully data-driven approximate model that relies on weighted sums of random variables. We obtain a stochastic lower bound for the optimal value and feasibility results that include convergence to the true feasible set as the number of data points increases, as well as the minimal number of data points needed to obtain a feasible solution with high probability. We illustrate our findings in a vaccine allocation problem and compare the results with a naive sample average approximation approach.

关键词： chance constraints data-driven optimization stochastic programming large deviations

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A Decision-Dependent stochastic Approach for Joint Operation and Maintenance of Overhead Transmission Lines After Sandstorms

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IEEE SYSTEMS JOURNAL 2023年第1期17卷 1489-1500页

作者： Yin, Wenqian Feng, Shuanglei Hou, Jiazuo Qian, Chengchen Hou, Yunhe Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China HKU Shenzhen Inst Res & Innovat Shenzhen 518057 Peoples R China China Elect Power Res Inst Renewable Energy Res Ctr Beijing 200223 Peoples R China State Grid Shanghai Municipal Elect Power Co Shanghai 200122 Peoples R China

A sandstorm is one of the extreme weather events causing extensive damage to overhead transmission lines (OTLs). Due to potential postsandstorm insulator flashover, OTLs face high failure probabilities, and implementing in-time maintenance on OTLs is crucial to mitigate postsandstorm losses. Aiming at determining an optimal maintenance sequence of targeted OTLs, this article proposes a decision-dependent stochastic approach for the joint operation and maintenance of OTLs. First, considering the inherent dependency of the uncertain availability of OTLs on maintenance decisions, the multiperiod maintenance process of OTLs is modeled as a stochastic process with decision-dependent uncertainty (DDU). Second, a two-stage stochastic model with DDU is formulated, where the maintenance sequence and unit commitment decisions are made in the first stage and the second stage comprises scenariowise operation. Then, to tackle the coupling relation between decisions and DDU, a unique modeling transformation technique is adopted to convert the established decision-dependent stochastic model into a computationally efficient form. Case studies verify the effectiveness of the proposed method for postsandstorm maintenance scheduling.

关键词： Maintenance engineering Power transmission lines Insulators stochastic processes Wind power generation Generators Schedules Decision-dependent uncertainty joint operation and maintenance sandstorm stochastic programming wind power generation

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Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system

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ENERGY 2023年 265卷

作者： Vahid-Ghavidel, Morteza Shafie-khah, Miadreza Javadi, Mohammad S. Santos, Sergio F. Gough, Matthew Quijano, Darwin A. Catalao, Joao P. S. Inst Syst & Comp Engn Technol & Sci INESC TEC Porto Portugal Univ Porto FEUP Fac Engn Porto Portugal Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Portucalense Univ Infante D Henrique UPT Porto Portugal REMIT Porto Portugal Univ Estadual Paulista UNESP Ilha Solteira Brazil

The optimal management of distributed energy resources (DERs) and renewable-based generation in multi -energy systems (MESs) is crucial as it is expected that these entities will be the backbone of future energy sys-tems. To optimally manage these numerous and diverse entities, an aggregator is required. This paper proposes the self-scheduling of a DER aggregator through a hybrid Info-gap Decision Theory (IGDT)-stochastic approach in an MES. In this approach, there are several renewable energy resources such as wind and photovoltaic (PV) units as well as multiple DERs, including combined heat and power (CHP) units, and auxiliary boilers (ABs). The approach also considers an EV parking lot and thermal energy storage systems (TESs). Moreover, two demand response (DR) programs from both price-based and incentive-based categories are employed in the microgrid to provide flexibility for the participants. The uncertainty in the generation is addressed through stochastic pro-gramming. At the same time, the uncertainty posed by the energy market prices is managed through the application of the IGDT method. A major goal of this model is to choose the risk measure based on the nature and characteristics of the uncertain parameters in the MES. Additionally, the behavior of the risk-averse and risk -seeking decision-makers is also studied. In the first stage, the sole-stochastic results are presented and then, the hybrid stochastic-IGDT results for both risk-averse and risk-seeker decision-makers are discussed. The pro-posed problem is simulated on the modified IEEE 15-bus system to demonstrate the effectiveness and usefulness of the technique.

关键词： Demand response Distributed energy resources Microgrid Multi -energy system stochastic programming

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A variant SDDP approach for periodic-review approximately optimal pricing of a slow-moving a item in a duopoly under price protection with end-of-life return and retail fixed markdown policy

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EXPERT SYSTEMS WITH APPLICATIONS 2023年 212卷

作者： Yildiz, Baris Sutcu, Muhammed Abdullah Gul Univ Ind Engn Dept TR-38170 Kayseri Turkiye

In this paper, we examine a selling environment where a manufacturer-controlled retailer and an independent retailer sell a slow-moving A item. The manufacturer offers the independent retailer a price protection contract stipulating that the manufacturer reimburses the independent retailer in case of a reduction in the wholesale price. The price set by the independent retailer is assumed to be determined by Retail Fixed Markdown (RFM) policy. The manufacturer also offers the independent retailer a special discount rate for the replenishment orders and the retailers are assumed to follow (R, S) inventory replenishment policy. The manufacturer adopts a periodic-review pricing strategy and the mean demand observed by each retailer in a given period depends on the prices. We also take the customers choosing no-purchase option into account. We employ multinomial logit (MNL) models to forecast customers' preferences based on retail prices. The retailers' market shares are esti-mated by customized choice probability functions. We propose stochastic programming models to determine the manufacturer's pricing strategy. Then, we propose a variant stochastic Dual Dynamic programming (SDDP) algorithm to determine the manufacturer's approximately optimal pricing strategy by getting around three curses of dimensionality. Then, we move on to the observations on the impact of four critically important contractual parameters on the price, the market shares and the expected total net profits and finally discuss some possible approaches for the selection of the best compromise values of those contractual parameters.

关键词： Price protection End -of -life returns Price commitment policies Retail fixed markdown policy stochastic dual dynamic programming stochastic programming

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stochastic planning for low-carbon building integrated energy system considering electric-heat-V2G coupling

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期151卷

作者： Xiong, Zuxun Shen, Xinwei Wu, Qiuwei Guo, Qinglai Sun, Hongbin Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Tsinghua Univ Inst Ocean Engn Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

The low-carbon building has been proposed to mitigate the climate change caused by environmental problems and realize carbon neutrality in urban areas. In addition, the integrated energy system (IES) has been developed to reduce renewable energy curtailment in the power distribution system and improve energy efficiency due to the independent operation of traditional energy systems. In this paper, we propose a stochastic planning method for low-carbon building IES, in which the Vehicle to Grid (V2G) is also considered to further increase the flexibility of low-carbon buildings. The proposed planning method optimizes the investment and operation costs, and CO2 emission of the building IES, to achieve the maximum benefit of the low-carbon building and help realize carbon neutrality. By considering the uncertainty of distributed renewable energy, multi-energy load fluctuation and the random behavior of EV users, a two-stage stochastic programming model is formulated with chance constraints, in which the heuristic moment matching scenario generation (HMMSG) and sample average approximation (SAA) methods are applied to deal with the uncertainties. In the case study, a real IES office building in Shanghai, where photovoltaic (PV), energy storage system (ESS), fuel cell (FC), EV, etc. are included as planning options, is used as the test system to verify the effectiveness of the proposed planning method, and the functions of the ESS and EV in IES are analyzed in detail in different operation scenarios. The case study results show that the proposed planning scheme can reduce the total cost and carbon emission significantly. (c) 2017 Elsevier Inc. All rights reserved.

关键词： Chance constraint Energy storage system Electric vehicle Low-carbon building integrated energy system stochastic programming

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