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Optimal Control and Learning Strategies When Environmental Costs are Cumulative

IFAC Proceedings Volumes 1989年第17期22卷 99-102页

作者： S.C. Peck Hung-po Chao T.J. Teisberg Electric Power Research Institute 3412 Hillview Avenue Palo Alto CA 94304 USA Teisberg Associates 25 Applecrest Road Weston MA 02193 USA

There is a class of environmental problems in which environmental costs are cumulative, i.e., dependent upon cumulative prior discharges. Examples may include the acidification of a group of lakes due to atmospheric deposition, or climatic change from the build-up of carbon dioxide in the atmosphere. Typically, these problems also involve great uncertainty - about the rate at which discharges accumulate, the magnitude of environmental costs at any accumulation level, and the ultimate extent of damages, if discharges were to accumulate indefinitely. When this is true, appropriate strategies will generally involve both control and learning. The purpose of this paper is to illustrate some general characteristics of such strategies. In the first part of the paper, we use an analytical model to examine optimal control strategies for an hypothetical pollutant, for which damages are known with certainty. In this context, we explore the implications of a threshold below which there are no costs of the discharge, and of a ceiling over which the costs of the discharge cease to rise. The key result is that it is optimal for the marginal cost of emission reduction to rise exponentially until the threshold of damage is reached and then to decline to zero at which time the ceiling of damage is reached. The second part of the paper develops a stochastic dynamic programming formulation, in which we introduce a simple kind of uncertainty about environmental costs, and allow for joint control and learning strategies. One interesting result is illustrated; environmental outcomes actually may be less “conservative”, if future learning may result in a downward revision of initially high estimates of environmental costs.

关键词： Pollution Environmental control Learning Nonlinear costs Economics stochastic dynamic programming

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Temporal Difference Learning Waveform Selection

Temporal Difference Learning Waveform Selection

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2009 ISECS International Colloquium on Computing, Communication, Control, and Management

作者： Bin Wang College of Information Science and Engineering Northeastern University Shenyang,China Jinkuan Wang,Xin Song,Yinghua Han Engineering Optimization and Smart Antenna Institute Northeastern University at Qinhuangdao Qinhuangdao,China

The largest difference between cognitive radar and other adaptive radar is the adaptivity of transmitter in cognitive radar. How to optimally decide or select the radar waveform for next transmission based on the observation of past radar returns is one of the important issues. In this paper,with the stochastic dynamic programming model of waveform selection,we use the method of temporal difference learning to solve this problem and realize the adaptivity of waveform selection. The simulation results show that the uncertainty of state estimation using temporal difference learning is less than that using fixed waveform.

关键词： cognitive radar waveform selection stochastic dynamic programming temporal difference learning

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Optimal Utilization of Storage and the Induced Price Elasticity of Demand in the Presence of Ramp Constraints

Optimal Utilization of Storage and the Induced Price Elastic...

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IEEE Conference on Decision and Control

作者： Ali Faghih Mardavij Roozbehani Munther A. Dahleh Electrical Engineering and Computer Science (EECS) Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT) Cambridge MA LIDS MIT EECS Department at MIT

ISBN: (纸本)9781612848006

This paper is concerned with optimal utilization of storage, characterization of the economic value of storage in the presence of ramp-rate constraints and stochastically-varying electricity prices, and characterization of the price elasticity of demand induced by optimal utilization of storage. The ramp constraints limit the charging and discharging rate of storage, and can be due to the physical limitations of the storage device or the power lines. Such constraints make analytical characterization of optimal policies particularly difficult. In this paper, the optimal utilization problem is addressed in a finite-horizon stochastic dynamic programming framework, and an analytical characterization of the value function along with recursive formulas for computation of the associated optimal policy are derived. It is shown that the value function associated with the dynamic programming problem is a piecewise linear convex function of the storage state, i.e., the amount of stored energy. Furthermore, while the economic value of storage capacity is a non-decreasing function of price volatility, it is shown that due to finite ramping rates, the value of storage saturates quickly as the capacity increases, regardless of price volatility. Finally, it is shown that optimal utilization of storage by consumers could induce a considerable amount of price elasticity, particularly near the average price.

关键词： Value of Storage Ramp Constraints Price Elasticity of Demand stochastic dynamic programming

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Predicting resilience of migratory birds to environmental change

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2024年第19期121卷 1页

作者： Lisovski, Simeon Hoye, Bethany J. Conklin, Jesse R. Battley, Phil F. Fuller, Richard A. Gosbell, Ken B. Klaassen, Marcel Lee, Chengfa Benjamin Murray, Nicholas J. Bauer, Silke Alfred Wegener Inst Sect Polar Terr Environm Syst Helmholtz Ctr Polar & Marine Res D-14473 Potsdam Germany Univ Wollongong Sch Earth Atmospher & Life Sci Wollongong NSW 2522 Australia Univ Groningen Groningen Inst Evolutionary Life Sci Conservat Ecol Grp NL-9700 Groningen Netherlands Massey Univ Zool & Ecol Grp Palmerston North 4442 New Zealand Univ Queensland Sch Environm Brisbane Qld 4072 Australia Victorian Wader Study Grp Blackburn Vic 3130 Australia Deakin Univ Ctr Integrat Ecol Sch Life & Environm Sci Geelong Vic 3217 Australia Remote Sensing Technol Inst German Aerosp Ctr D-12489 Berlin Germany Univ Wurzburg Dept Remote Sensing EAGLE M Sc Program D-97074 Wurzburg Germany James Cook Univ Coll Sci & Engn Townsville Qld 4811 Australia Fed Res Inst WSL CH-8903 Birmensdorf Switzerland Swiss Ornithol Inst Dept Bird Migrat CH-6204 Sempach Switzerland Univ Amsterdam Inst Biodivers & Ecosyst Dynam NL-1090 GE Amsterdam Netherlands Swiss Fed Inst Technol Dept Environm Syst Sci CH-8902 Zurich Switzerland

The pace and scale of environmental change represent major challenges to many organisms. Animals that move long distances, such as migratory birds, are especially vulnerable to change since they need chains of intact habitat along their migratory routes. Estimating the resilience of such species to environmental changes assists in targeting conservation efforts. We developed a migration modeling framework to predict past (1960s), present (2010s), and future (2060s) optimal migration strategies across five shorebird species (Scolopacidae) within the East Asian- Australasian Flyway, which has seen major habitat deterioration and loss over the last century, and compared these predictions to empirical tracks from the present. Our model captured the migration strategies of the five species and identified the changes in migrations needed to respond to habitat deterioration and climate change. Notably, the larger species, with single or few major stopover sites, need to establish new migration routes and strategies, while smaller species can buffer habitat loss by redistributing their stopover areas to novel or less - used sites. Comparing model predictions with empirical tracks also indicates that larger species with the stronger need for adaptations continue to migrate closer to the optimal routes of the past, before habitat deterioration accelerated. Our study not only quantifies the vulnerability of species in the face of global change but also explicitly reveals the extent of adaptations required to sustain their migrations. This modeling framework provides a tool for conservation planning that can accommodate the future needs of

关键词： global change biology optimal migration habitat deterioration avian migration stochastic dynamic programming

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Production control of a deteriorated remanufacturing system within an open-loop reverse supply chain

Production control of a deteriorated remanufacturing system ...

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Mediterranean Conference on Control and Automation

作者： F. I. Dehayem Nodem J. P. Kenne Mechanical Engineering Department Production Technologies Integration Laboratory

ISBN: (纸本)9781467383479

Reverse supply chain management is a significant issue for sustainable economy, product recovery and green thinking. In a closed loop reverse supply chain, used products are generally returned to original producers. But in an open loop reverse supply chain, used products are not returned to original producers, outsider firms recover them. This paper focuses on an open-loop reverse supply chain (OLRSC), which includes a single centralized collection point of returned products, a single remanufacturing machine (RM) and a single distribution center. The RM produces parts, and upon a breakdown, either an imperfect repair is undertaken or is replaced with a new identical one. The objective of the control problem is to find the production rate and the repair/replacement policy that minimize total incurred costs over an infinite planning horizon. This paper proposes a stochastic dynamic programming formulation of the problem and derives the optimal policies numerically. A numerical example is included and sensitivity analyses with respect to the system parameters are examined to illustrate the importance and effectiveness of the proposed methodology.

关键词： Reverse supply chain Remanufacturing stochastic dynamic programming Numerical methods Imperfect repairs

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Management Strategies for a Defined Contribution Pension Fund under the Hull-White Interest Rate Model

Management Strategies for a Defined Contribution Pension Fun...

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2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS2017)

作者： Patrick Kandege Mwanakatwe Lixin Song Emmanuel Hagenimana School of Mathematical Sciences Dalian University of Technology

This paper analyzes optimal investment strategies for a DC pension fund under the Hull-White interest rate model. Under this model, the pension fund manager can invest capital in the bank account, stock index, and real estates. The dynamics of the interest rate follows the Hull-White interest rate model, and a drifted Brownian motion drives the financial market. The pension fund manager aims to maximize the expected terminal utility of wealth in a complete market setting under constant relative risk aversion(CRRA). This paper derives the Hamilton-JacobiBellman(HJB) equation associated with the control problem using a dynamic programming technique. We obtain the explicit solution for optimal investment policies by solving the HJB equation and optimal value function. The results show that the optimal proportion invested in risky assets is higher in stock than in a real estate.

关键词： optimal investment strategy defined contribution pension fund stochastic dynamic programming interest rate

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Optimal Electric Energy Storage Operation

Optimal Electric Energy Storage Operation

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IEEE Power and Energy Society General Meeting

作者： Junjie Qin Raffi Sevlian David Varodayan Ram Rajagopal the Institute of Computational and Mathematical Engineering and the Stanford Sustainable Systems Lab Stanford University Stanford CA 94305 the Department of Electrical Engineering and the Stanford Sustainable Systems Lab Stanford University Stanford CA 94305 the Department of Civil and Environmental Engineering and the Stanford Sustainable Systems Lab Stanford University Stanford CA 94305

ISBN: (纸本)9781467327299

Estimating the arbitrage value of storage is an important problem in power systems planning. Various studies have reported different values based numerical solutions of variations of a basic model. In this paper, we instead rely on a closed form solution for storage control. The closed form highlights the right type of forecasting that is required and allows large horizon problems to be solved. We study various scenarios and provide a simple methodology for evaluating the arbitrage value of storage.

关键词： Index Terms-Energy storage operation stochastic dynamic programming warehousing problem

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stochastic Optimization Based on Principal-agent Problem

Stochastic Optimization Based on Principal-agent Problem

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2009 ISECS International Colloquium on Computing, Communication, Control, and Management

作者： Xiaoyu Ren Department of Mathematics Zhejiang University Hangzhou 310027,Zhejiang,P.R.China Xinping Shao Department of Mathematics Zhejiang University Hangzhou 310027,Zhejiang,P.R.China Shenghong Li Department of Mathematics Zhejiang University Hangzhou 310027,Zhejiang,P.R.China

By the theory of stochastic dynamic program- ming,we provide the methods for deriving the optimal *** this paper,we make two models in dynamic state process to maximize the expected utility of the agent and then obtain the famous Hamilton-Jacobi-Bellman equation. Furthermore,we derive explicit form solution and closed- form solution of the optimal equations for given utility functions.

关键词： principal-agent problem stochastic dynamic programming stochastic differential equation stochastic optimal control HJB equation

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Operation of Energy Storage System for Renewable Utilization Enhancement

Operation of Energy Storage System for Renewable Utilization...

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IEEE Power and Energy Society General Meeting

作者： Zhen Shu Kelvin Tan Kian Hock Gooi Hoay Beng Energy Sector DNV GL Singapore Technology Centre School of Electrical and Electronic Engineering Nanyang Technological University

ISBN: (纸本)9781509041695

This paper presents the optimal operation of energy storage system (ESS) applied for renewable utilization enhancement. The problem is formulated with stochastic dynamic programming (SDP) framework, which explicitly incorporates the system uncertainties. The transmission network modeling is particularly considered from the viewpoint of Independent System Operator (ISO). The SDP-based operation policy for ESS, renewable and conventional generation dispatch can accurately adapt to hourly uncertainties in wind and load demand. It is demonstrated to considerably increase wind utilization and reduce energy production cost. Additionally, comparison result shows that the proposed SDP model outperforms look-ahead optimization model as a commonly used approach for operation problems under uncertainty.

关键词： Energy storage system Power system generation dispatch Renewable energy stochastic dynamic programming

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Integrating the management of pasture resource condition with production,profit and supplementary feeding to improve the sustainability of extensive grasslands under climatic uncertainty

Integrating the management of pasture resource condition wit...

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中国—澳大利亚可持续性草地管理研讨会

作者： Karl Behrendt EH Graham Centre for Agricultural Innovation(Industry&Investment NSW and Charles Sturt University) School of Agricultural&Wine SciencesCharles Sturt University

The use of forage conservation and tactical adjustments in stocking rates is regarded as essential to improving the spatial and inter-temporal utilisation of pastures for increased livestock production,profitability and sustainability in extensive grazing *** conundrum faced by managers is that of balancing between short-term utilisation(tactical stocking rate adjustments) and/or the transferring of feed resources(through forage conservation),and its impact on profitability and sustainability of the grassland system in the long term when climate variability is *** risk is embedded within the decision making process and tactical decision rules need to be identified that optimise the spatial and inter-temporal allocation of pasture resources for livestock production.

关键词： pasture utilisation dynamic pasture resource forage conservation stocking rate bioeconomic simulation stochastic dynamic programming

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