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Long-term complementary operation of a large-scale hydro-photovoltaic hybrid power plant using explicit stochastic optimization

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APPLIED ENERGY 2019年第Mar.15期238卷 863-875页

作者： Li, He Liu, Pan Guo, Shenglian Ming, Bo Cheng, Lei Yang, Zhikai Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Hubei Peoples R China Hubei Prov Collaborat Innovat Ctr Water Resources Wuhan 430072 Hubei Peoples R China

The complementary operation of hydro-photovoltaic (PV) hybrid power plants has become important in the modern power systems. However, the strong variations involved in the streamflow and PV generation lead to uncertainties in the complementary operations. To improve the long-term complementary operation performance of a large-scale hydro-PV hybrid power plant, this study developed long-term stochastic optimization methods that simultaneously consider the uncertainty of the streamflow and PV power output. A multi-objective optimization model was established to maximize the total energy production and guaranteed rate. The model was then solved using stochastic dynamic programming to obtain the operation decisions (carryover storage), which are functions of the initial storage, streamflow, and PV output. Finally, four schemes for deriving the operation rules were constructed: (1) stochastic optimization of the hydropower station directly plus PV output, (2) stochastic optimization of the hydro-PV hybrid power plant considering stochastic streamflow and deterministic PV output, (3) stochastic optimization of the hydro-PV hybrid power plant considering independent stochastic streamflow and PV output, and (4) stochastic optimization of the hydro-PV hybrid power plant considering correlative stochastic streamflow and PV output. The proposed methods were applied to the Longyangxia hydro-PV hybrid power plant in Qinghai province, China, which is the largest hydro-PV plant in the world. The performance of the four schemes was compared across calibration and validation periods. The results show that: (1) the complementarity of hydropower and PV power in long-term operations is highly necessary, (2) considering the uncertainty of stochastic streamfiow and PV output simultaneously improves the efficiency of complementary operations, and (3) stochastic optimization of the hydro-PV hybrid power plant considering the independent stochastic streamflow and PV output gives the best pe

关键词： Hydro-PV hybrid power plant Uncertainty Streamflow PV output stochastic dynamic programming

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An approximate dynamic programming approach for sequential pig marketing decisions at herd level

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第3期276卷 1056-1070页

作者： Pourmoayed, Reza Nielsen, Lars Relund Aarhus Univ Dept Econ & Business Econ Fuglesangs Alle 4 DK-8210 Aarhus V Denmark

One of the most important operations in the production of growing/finishing pigs is the marketing of pigs for slaughter. While pork production can be managed at different levels (animal, pen, section, or herd), it is beneficial to consider the herd level when determining the optimal marketing policy due to inter-dependencies, such as those created by fixed transportation costs and cross-level constraints. In this paper, we consider sequential marketing decisions at herd level. A high-dimensional infinite horizon Markov decision process (MDP) is formulated which, due to the curse of dimensionality, cannot be solved using standard MDP optimization techniques. Instead, approximate dynamic programming (ADP) is applied to solve the model and find the best marketing policy at herd level. Under the total expected discounted reward criterion, the proposed ADP approach is first compared with a standard solution algorithm for solving an MDP at pen level to show the accuracy of the solution procedure. Next, numerical experiments at herd level are given to confirm how the marketing policy adapts itself to varying costs (e.g., transportation cost) and cross-level constraints. Finally, a sensitivity analysis for some parameters in the model is conducted and the marketing policy found by ADP is compared with other well-known marketing polices, often applied at herd level. (C) 2019 Elsevier B.V. All rights reserved.

关键词： OR in agriculture Approximate dynamic programming Markov decision process Herd management stochastic dynamic programming

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Shared Steering Torque Control for Lane Change Assistance: A stochastic Game-Theoretic Approach

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第4期66卷 3093-3105页

作者： Ji, Xuewu Yang, Kaiming Na, Xiaoxiang Lv, Chen Liu, Yahui Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Univ Cambridge Dept Engn Cambridge CB2 1PZ England Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

The challenging issue of "human-machine copilot" opens up a new frontier to enhancing driving safety. However, driver-machine conflicts and uncertain driver/external disturbances are significant problems in cooperative steering systems, which degrade the system's path-tracking ability and reduce driving safety. This paper proposes a novel stochastic game-based shared control framework to model the steering torque interaction between the driver and the intelligent electric power steering (IEPS) system. A six-order driver-vehicle dynamic system, including driver/external uncertainty, is established for path-tracking. Then, the affine linear-quadratic-based path-tracking problem is proposed to model the maneuvers of the driver and IEPS. Particularly, the feedback Nash and Stackelberg frameworks to the affine-quadratic problem are derived by stochastic dynamic programming. Two cases of copilot lane change driving scenarios are studied via computer simulation. The intrinsic relation between the stochastic Nash and Stackelberg strategies is investigated based on the results. And the steering-in-the-loop experiment reveals the potential of the proposed shared control framework in handling driver-IEPS conflicts and uncertain driver/external turbulence. Finally, the copiloting experiments with a human driver further demonstrate the rationality of the game-based pattern between both the agents.

关键词： Affine-quadratic game driver-machine conflicting shared steering control stochastic dynamic programming

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Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

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WATER 2020年第6期12卷 1793-1793页

作者： Rehana, Shaik Rajulapati, Chandra Rupa Ghosh, Subimal Karmakar, Subhankar Mujumdar, Pradeep Int Inst Informat Technol Hyderabad Lab Spatial Informat Hyderabad 500032 India Univ Saskatchewan Ctr Hydrol Saskatoon SK S7N 1K2 Canada Indian Inst Technol Dept Civil Engn Mumbai 400076 Maharashtra India Indian Inst Technol Environm Sci & Engn Dept Mumbai 400076 Maharashtra India Indian Inst Sci Interdisciplinary Ctr Water Res Dept Civil Engn Bangalore 520011 Karnataka India

Regional water resource modelling is important for evaluating system performance by analyzing the reliability, resilience and vulnerability criteria of the system. In water resource systems modelling, several uncertainties abound, including data inadequacy and errors, modeling inaccuracy, lack of knowledge, imprecision, inexactness, randomness of natural phenomena, and operational variability, in addition to challenges such as growing population, increasing water demands, diminishing water sources and climate change. Recent advances in modelling techniques along with high computational capabilities have facilitated rapid progress in this area. In India, several studies have been carried out to understand and quantify uncertainties in various basins, enumerate large temporal and regional mismatches between water availability and demands, and project likely changes due to warming. A comprehensive review of uncertainties in water resource modelling from an Indian perspective is yet to be done. In this work, we aim to appraise the quantification of uncertainties in systems modelling in India and discuss various water resource management and operation models. Basic formulation of models for probabilistic, fuzzy and grey/inexact simulation, optimization, and multi-objective analyses to water resource design, planning and operations are presented. We further discuss challenges in modelling uncertainties, missing links in integrated systems approach, along with directions for future.

关键词： reservoir operation stochastic dynamic programming fuzzy optimization reservoir-river system water quantity-quality management climate change

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Staff assignment policies for a mass casualty event queuing network

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ANNALS OF OPERATIONS RESEARCH 2019年第1-2期283卷 411-442页

作者： Lodree, Emmett J. Altay, Nezih Cook, Robert A. Univ Alabama Culverhouse Coll Commerce & Business Adm Tuscaloosa AL 35487 USA Depaul Univ Driehaus Coll Business Chicago IL 60604 USA

We study parallel queuing systems in which heterogeneous teams collaborate to serve queues with three different prioritization levels in the context of a mass casualty event. We assume that the health condition of casualties deteriorate as time passes and aim to minimize total deprivation cost in the system. Servers (i.e. doctors and nurses) have random arrival rates and they are assigned to a queue as soon as they arrive. While nurses and doctors serve their dedicated queues, collaborative teams of doctors and nurses serve a third type of customer, the patients in critical condition. We model this queueing network with flexible resources as a discrete-time finite horizon stochastic dynamic programming problem and develop heuristic policies for it. Our results indicate that the standard c mu rule is not an optimal policy, and that the most effective heuristic policy found in our simulation study is intuitive and has a simple structure: assign doctor/nurse teams to clear the critical patient queue with a buffer of extra teams to anticipate future critical patients, and allocate the remaining servers among the other two queues.

关键词： Humanitarian logistics Medical emergency stochastic dynamic programming Monte Carlo simulation

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Welfare Implications of Water Scarcity: Higher Prices of Desalination

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ENVIRONMENTAL & RESOURCE ECONOMICS 2019年第4期73卷 995-1022页

作者： Saglam, Yigit Victoria Univ Wellington Sch Econ & Finance POB 600 Wellington 6140 New Zealand

In this paper, we evaluate the welfare implications of shortages in renewable resources, and investigate the effects of cross-subsidization on these shortages. We set up a stochastic dynamic programming model in which a benevolent supplier allocates the resource for multiple user groups subject to revenue and resource constraints. The supplier also has access to an external source that can be utilized at a certain cost. The solution to the model gives the optimal sectoral prices, and demand for the external source. We find out that saving budget surplus during periods of scarcity allows the planner to charge prices below average costs when the resource is abundant. Using data from Turkey, we simulate our dynamic model to quantify the implications of cross-subsidization on water use across user groups.

关键词： Renewable resource Water shortages stochastic dynamic programming Desalination Cross-subsidization

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Risk, Risk Aversion, and Agricultural Technology Adoption A Novel Valuation Method Based on Real Options and Inverse stochastic Dominance

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Q Open 2021年第2期1卷

作者： Spiegel, Alisa Britz, Wolfgang Finger, Robert Institute for Food and Resource Economics University of Bonn Meckenheimer Allee 174 Bonn 53115 Germany Agricultural Economics and Policy Group ETH Zurich Sonneggstrasse 33 Zurich 8092 Switzerland

Risk and risk preferences belong to the key determinants of investment-based technology adoption in agriculture. We develop and apply a novel approach in which an inverse second order stochastic dominance approach is integrated into a stochastic dynamic farm-level model to quantify the effect of both risk and risk aversion on the timing and scale of agricultural technology adoption. Our illustrative example on short rotation coppice adoption shows that risk aversion leads to technology adoption that takes place earlier, but to a smaller extent. In contrast, higher levels of risk exposure lead to postponed but overall larger adoption. These effects would be obscured if technology adoption is not analyzed in a farm-scale context or considered as a now-or-never decision, the still dominant approach in the literature. © 2021 The Author(s). Published by Oxford University Press in association with European Agricultural and Applied Economics Publications Foundation.

关键词： farm-level investment decision inverse stochastic dominance perennial energy crop Risk preferences stochastic dynamic programming

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Modeling producer responses with dynamic programming: a case for adaptive crop management

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AGRICULTURAL ECONOMICS 2019年第1期50卷 101-111页

作者： Boussios, David Preckel, Paul V. Yigezu, Yigezu A. Dixit, Prakash N. Akroush, Samia M'hamed, Hatem Cheikh Annabi, Mohamed Aw-Hassan, Aden Shakatreh, Yahya Hadi, Omar Abdel Al-Abdallat, Ayed Abu El Enein, Jamal Ayad, Jamal ERS USDA Washington DC 20250 USA Purdue Univ Dept Agr Econ W Lafayette IN 47907 USA ICARDA Amman Jordan NARC Amman Jordan INRAT Tunis Tunisia Univ Jordan Fac Agr Amman Jordan

Past research found agricultural producers' conditional responses during the growing season are important adaptations to weather and other stochastic events. Failing to recognize these responses overstates the risks confronting producers and understates their ability to respond to adverse circumstances. dynamic programming (DP) provides a means for determining optimal long-term crop management plans. However, most applications in the literature base their analysis on annual time steps with fixed strategies within the year, effectively ignoring conditional responses during the year. We suggest an alternative approach that captures the strategic responses within a cropping season to random weather variables as they unfold, reflecting farmers' ability to adapt to weather realizations. We illustrate our approach by applying it to a typical cereal farm in Karak, Jordan. The results show that including conditional within-year responses to weather reduces the frequency of fallowing by 23% and increases expected income by 9%.

关键词： Crop rotation stochastic dynamic programming Systems analysis Risk Bioeconomic

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stochastic optimal switching model for migrating population dynamics

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JOURNAL OF BIOLOGICAL dynamicS 2019年第1期13卷 706-732页

作者： Yoshioka, Hidekazu Tanaka, Tomomi Aranishi, Futoshi Izumi, Tomoki Fujihara, Masayuki Shimane Univ Grad Sch Nat Sci & Technol Matsue Shimane Japan Shimane Univ Fisheries Ecosyst Project Ctr Matsue Shimane Japan Ehime Univ Grad Sch Agr Matsuyama Ehime Japan Kyoto Univ Grad Sch Agr Kyoto Japan

An optimal switching control formalism combined with the stochastic dynamic programming is, for the first time, applied to modelling life cycle of migrating population dynamics with non-overlapping generations. The migration behaviour between habitats is efficiently described as impulsive switching based on stochastic differential equations, which is a new standpoint for modelling the biological phenomenon. The population dynamics is assumed to occur so that the reproductive success is maximized under an expectation. Finding the optimal migration strategy ultimately reduces to solving an optimality equation of the quasi-variational type. We show an effective linkage between our optimality equation and the basic reproduction number. Our model is applied to numerical computation of optimal migration strategy and basic reproduction number of an amphidromous fish Plecoglossus altivelis altivelis in Japan as a target species.

关键词： stochastic dynamic programming fish migration Hamilton-Jacobi-Bellman equation basic reproduction number Plecoglossus altivelis altivelis

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Medium-term scheduling of a hydropower plant participating as a price-maker in the automatic frequency restoration reserve market

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ELECTRIC POWER SYSTEMS RESEARCH 2020年 185卷 106399-106399页

作者： Perez-Diaz, Juan, I Guisandez, Ignacio Chazarra, Manuel Helseth, Arild Univ Politecn Madrid Dept Hydraul Energy & Environm Engn C Prof Aranguren 3 Madrid 28040 Spain SINTEF Energy Res Sem Saelands Vei 11 N-7465 Trondheim Norway

This paper presents a novel optimization model for the calculation of the water value of a hydropower plant. The model has a time horizon of 1 year with 1-day decision stages, considers sales of both energy and frequency restoration reserves (FRR) and is solved by stochastic dynamic programming. The novelty of the model is that it considers the producer's price-making ability in the FRR market. The proposed model is used to obtain the water values of an existing hydropower plant. The water values are then used to simulate the day-ahead scheduling of the hydropower plant in a 100-year scenario. The results are compared to those obtained without considering the producer's price-making ability in the FRR market. The profit increase is modest compared to the uncertainty existing in the day-ahead scheduling in all analysed cases. However, the water spillage is significantly lower if the producer's price-making ability in the FRR market is considered when computing the water value. This last result may have important implications for the plant's operation, especially when the reservoir is also used for the purpose of flood control, as the one used as case study in the paper, and many others all over the world.

关键词： Hydroelectric power generation Water value Frequency restoration reserve market Price-maker producer Mixed integer quadratic programming stochastic dynamic programming

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