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8th International Conference on Green Energy and Applications (ICGEA)

作者： Le -The, Cuong Hoang, Nhat Nguyen-Duc, Tuyen Takano, Hirotaka Hanoi Univ Sci & Technol Sch Elect & Elect Engn Hanoi Vietnam Gifu Univ Fac Engn Dept Elect Elect & Comp Engn Gifu Japan

ISBN: (纸本)9798350349009;9798350349016

As the global trend toward sustainable transportation gains momentum, electric vehicles (EVs) have become increasingly popular due to their ecological advantages. However, as the EV population expands, issues pertaining to power quality, such as voltage stability and load profiles, have emerged. Various solutions have been proposed to mitigate the adverse effects of EV charging. One such approach involves the amalgamation of renewable energy sources (RES) within charging infrastructure, coupled with Vehicle-to-Grid (V2G) technology. In this article, a new method is presented that utilizes RES in conjunction with the forward dynamic programming Algorithm to lower the cost of charging all EVs. This approach also works to even out the demand curve by considering EV owners' travel schedules.

关键词： Electric vehicles V2G forward dynamic programming Excess Renewable Energy

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An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2021年 149卷 283-321页

作者： Mo, Pengli D'Ariano, Andrea Yang, Lixing Veelenturf, Lucas P. Gao, Ziyou Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Eindhoven Univ Technol Sch Ind Engn NL-5600 MB Eindhoven Netherlands Univ Rome Tre Dept Engn Via Vasca Navale 79 I-00146 Rome Italy Erasmus Univ Rotterdam Sch Management Burgemeester Oudlaan 50 NL-3062 PA Rotterdam Netherlands

Subway lines connecting different urban functional zones in large cities have direction dependent and time-variant passenger demand, namely, asymmetry in passenger demand. Most existing studies adopt a symmetric strategy to design operations in both directions and sequentially optimize the different problems associated with operations, thereby failing to meet the asymmetry in passenger demand. This study formulates an asymmetric operation strategy as an integrated mixed-integer non-linear model to optimize the entire operational process of rolling stock from the perspective of service quality and operating costs. Based on the proposed model, an exact algorithm is proposed with speed-up techniques to quickly generate an optimal solution. To this end, the original model is decomposed into several sub-problems that can be exactly solved by using a forward dynamic programming algorithm. Based on actual data from the Beijing subway's Yizhuang line, numerical experiments are conducted to investigate the effectiveness of the asymmetric operation strategy, to identify managerial insights on the integrated optimization, and to evaluate the performance of the proposed methodology. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Subway train timetabling dynamic passenger demand Rolling stock planning Operating costs Energy consumption and regeneration forward dynamic programming

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Multi‐stage Fuzzy Portfolio Optimization Considering Realistic Constraints

World Scientific Research Journal

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World Scientific Research Journal 2022年第6期8卷 566-576页

作者： Changkun Hou Gangzhen Wang

In this paper, we study a kind of multi‐stage fuzzy portfolio problem with the return rate of assets as the mean of possibility, which is a dynamic linear programming problem for maximizing the final wealth under risk control. Based on the theory of possibility measure, the return, risk, degree of diversification and liquidity of portfolio by means of probability mean, absolute deviation, Yager entropy and average turnover rate respectively, and puts forward a multi‐stage fuzzy portfolio model with risk control, liquidity constraint and Yager entropy constraint. forward dynamic programming is used to solve dynamic linear programming directly, and the optimal solution of securities portfolio is obtained. Finally, based on the real data of Shanghai Stock Exchange, the behavior of the model and the proposed algorithm are illustrated.

关键词： Multi‐stage fuzzy portfolio Yager entropy forward dynamic programming Liquidity constraint Trapezoidal fuzzy number

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Automated identification of a complex storage model and hardware implementation of a model-predictive controller for a cooling system with ice storage

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APPLIED THERMAL ENGINEERING 2017年 121卷 922-940页

作者： Thiem, Sebastian Born, Alexander Danov, Vladimir Vandersickel, Annelies Schaefer, Jochen Hamacher, Thomas Siemens AG Corp Technol Gunther Scharowsky Str 1 Erlangen Germany Tech Univ Munich Chair Renewable & Sustainable Energy Syst Munich Germany Tech Univ Munich Inst Energy Syst Munich Germany

Future sustainable energy systems could increase the share of energy converted from fluctuating renewable energy sources by intelligent model-based predictive control of cooling systems with thermal energy storage. This study investigated an experimental cooling system comprising a compression chiller and an ice storage. A runtime-efficient predictive model for partial charge and discharge of ice storage was derived. In addition, techniques for automatic model determination and adaptation were introduced and examined. The experimental setup involved the development and implementation of a model predictive controller (MPC) to minimize operating expenses under dynamic electricity pricing based on a forward dynamic programming algorithm. The objective function included energy charges, compressor start-up costs, and terminal costs that depended on the state of charge and state of the chiller at the end of the optimization horizon. Three examples of cases validated and compared the advantages of the MPC over an open-loop (day ahead) optimal control concept. The cases examined the influence of temperature and load forecast inaccuracy, and investigated the coping mechanism of the system to sudden updates involving price and temperature predictions. The findings illustrated that the MPC achieved significant savings of operating expenses when compared with the open-loop optimal control concept. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Model-predictive control Ice storage Thermal energy storage forward dynamic programming Partial charge and discharge

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Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: A dynamic programming approach based on state-space-time network representations

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2016年第Jul.期89卷 19-42页

作者： Mahmoudi, Monirehalsadat Zhou, Xuesong Arizona State Univ Sch Sustainable Engn & Built Environm Tempe AZ 85281 USA

Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). This paper first proposes a new time-discretized multi-commodity network flow model for the VRPPDTW based on the integration of vehicles' carrying states within space-time transportation networks, so as to allow a joint optimization of passenger-to-vehicle assignment and turn-by-turn routing in congested transportation networks. Our three-dimensional state-space-time network construct is able to comprehensively enumerate possible transportation states at any given time along vehicle space-time paths, and further allows a forward dynamic programming solution algorithm to solve the single vehicle VRPPDTW problem. By utilizing a Lagrangian relaxation approach, the primal multi-vehicle routing problem is decomposed to a sequence of single vehicle routing sub-problems, with Lagrangian multipliers for individual passengers' requests being updated by sub-gradient-based algorithms. We further discuss a number of search space reduction strategies and test our algorithms, implemented through a specialized program in C++, on medium-scale and large-scale transportation networks, namely the Chicago sketch and Phoenix regional networks. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Vehicle routing problem with pickup and delivery with time windows Lagrangian relaxation Time-dependent least-cost path problem forward dynamic programming Ride-sharing service optimization

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Optimal energy management for grid-connected storage systems

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OPTIMAL CONTROL APPLICATIONS & METHODS 2015年第4期36卷 447-462页

作者： Lifshitz, D. Weiss, G. Tel Aviv Univ Sch EE IL-69978 Ramat Aviv Israel

This paper proposes three near-optimal (to a desired degree) deterministic charge and discharge policies for the maximization of profit in a grid-connected storage system. The changing price of electricity is assumed to be known in advance. Three near-optimal algorithms are developed for the following three versions of this optimization problem: (1) The system has supercapacitor type storage, controlled in continuous time. (2) The system has supercapacitor or battery type storage, and it is controlled in discrete time (i.e., it must give constant power during each sampling period). A battery type storage model takes into account the diffusion of charges. (3) The system has battery type storage, controlled in continuous time. We give algorithms for the approximate solution of these problems using dynamic programming, and we compare the resulting optimal charge/discharge policies. We have proved that in case 1 a bang off bang type policy is optimal. This new result allows the use of more efficient optimal control algorithms in case 1. We discuss the advantages of using a battery model and give simulation and experimental results. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： energy storage modeling of batteries constrained optimal control problem bang off bang control forward dynamic programming state space quantization

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A counterexample to a proposed dynamic programming algorithm for optimal bid construction in an auction-based fully distributed manufacturing system

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第1-4期71卷 377-380页

作者： Mizutani, Eiji Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei 106 Taiwan

The paper by Veeramani and Wang (Int J Adv Manuf Technol 28:541-550, 2006) published in this journal offers a general bid construction scheme for minimizing the job flow time in auction-based manufacturing control and claims the optimality of the procedure. The purpose of this note is to provide a small example, in which their proposed new method fails to produce an optimal solution. We also address efficient correct algorithms so as to protect the readers from mistakenly believing that their new procedure is a better way of computing solutions.

关键词： Bid construction scheme forward dynamic programming Setup (or changeover) times Job class scheduling

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Apply Unit Commitment Method in Power Station to Minimize the Fuel Cost

Apply Unit Commitment Method in Power Station to Minimize th...

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The 9th International Conference on Management and Service Science (MASS 2015)

作者： Adel Elhadi M.Yahya Mohamed Shaban Yousif Yahya Department of Industrial Engineering RegdalenAl-Zawia University

The goal of this paper study is to schedule the power generation units to minimize fuel consump-tion cost based on a model that solves unit commitment problems. This can be done by utilizing forward dynamic programming method to determine the most economic scheduling of generating units. The model is applied to power station,which consists of four generating units. The obtained results show that the applications of forward dynamic programming method offer substantial re-duction in fuel consumption cost. The fuel consumption cost has been reduced from $ 116,326 to $ 102,181 within a 24-hour period. This means saving about 12.16% of fuel consumption cost. The study emphasizes the importance of applying modeling schedule programs to the operation of power generation units. Consequently,the less consumption of fuel is,the less losses of power and pollution will be.

关键词： Unit Commitment forward dynamic programming Generation Scheduling Operation Cost

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An Optimal Operation Scheduling for Wind Farm with Storage and Forecasting

An Optimal Operation Scheduling for Wind Farm with Storage a...

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2nd International Conference on Energy, Environment and Sustainable Development (EESD 2012)

作者： Liu, Juncheng Lv, Yuegang Ma, Jingran North China Elect Power Univ Beijing Peoples R China Univ Southern Calif Los Angeles CA USA

ISBN: (纸本)9783037855492

In this paper, the optimal schedule for power output of a wind farm with storage units and forecasting system has been studied. Optimal schedule for wind power output aims at maximizing expected schedule income and minimizing cost over the required period. We present a practical method to solve the problems based on forward dynamic programming algorithm. It is demonstrated by simulation that the method presented in this paper can ensure one to get a feasible and profitable schedule for wind farm.

关键词： Wind power Optimal generation schedule forward dynamic programming Energy storage systems

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forward DIFFERENTIAL dynamic-programming

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1977年第4期21卷 487-504页

作者： VIT, K UNIV SALFORD DEPT ELECT ENGNSALFORD M5 4WTLANCASHIREENGLAND

The dynamic programming formulation of the forward principle of optimality in the solution of optimal control problems results in a partial differential equation with initial boundary condition whose solution is independent of terminal cost and terminal constraints. Based on this property, two computational algorithms are described. The first-order algorithm with minimum computer storage requirements uses only integration of a system of differential equations with specified initial conditions and numerical minimization in finite-dimensional space. The second-order algorithm is based on the differential dynamic programming approach. Either of the two algorithms may be used for problems with nondifferentiable terminal cost or terminal constraints, and the solution of problems with complicated terminal conditions (e.g., with free terminal time) is greatly simplified.

关键词： Optimal control forward dynamic programming differential dynamic programming

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