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stochastic programming model for incentive-based demand response considering complex uncertainties of consumers

IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第20期14卷 4488-4500页

作者： Zheng, Shunlin Sun, Yi Li, Bin Hu, Yajie Qi, Bing Shi, Kun Li, Yuanfei North China Elect Power Univ Sch Elect & Elect Engn 2 Beinong Rd Beijing Peoples R China China Elect Power Res Inst Rd 15 Qinghe Xiaoying Beijing Peoples R China State Grid Fujian Econ Res Inst Rd 221 Xiufeng Fuzhou Peoples R China

Incentive-based demand response (IBDR) has been recognized as a powerful tool to mitigate supply-demand imbalance in electricity market. However, the complex uncertainties of consumers, including participation uncertainty and responsiveness uncertainty, have been a central challenge to implement IBDR programs. In this paper, a stochastic programming model for IBDR considering the complex uncertainties of consumers is proposed. The proposed model can effectively deals with the above two uncertainties. Besides, the model of energy storage unit (ESU) has been improved to cope with properly the deviation between total actual balancing power and required balancing power. Moreover, the model enhances the applicability of IBDR to be applicable to both curtailment IBDR programs and absorbing IBDR programs by adding dynamic parameters. The model is formulated as a bi-level stochastic programming problem based on uncertain programming theory, and corresponding equivalent model is also given to solve the problem effectively. Finally, simulation results verify merits of the proposed model in cutting down total cost of DRA, decreasing risk cost of DRA and reducing balancing power deviation caused by uncertainty of consumers.

关键词： stochastic processes incentive schemes supply and demand pricing demand side management stochastic programming energy storage power markets uncertain programming theory corresponding equivalent model demand response aggregator reducing balancing power deviation two-consumer IBDR stochastic programming model incentive-based demand response complex uncertainties supply-demand imbalance participation uncertainty responsiveness uncertainty total actual balancing power required balancing power curtailment IBDR programmes bi-level stochastic programming problem

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Swarm Intelligence-based stochastic programming model for Dynamic Asset Allocation

Swarm Intelligence-based Stochastic Programming Model for Dy...

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2010 IEEE World Congress on Computational Intelligence

作者： Dang, Jing Edelman, David Hochreiter, Ronald Brabazon, Anthony Univ Coll Dublin Nat Comp Res & Applicat Grp Sch Business Dublin Ireland WU Vienna Univ Econom & Business Dept Math & Stat Vienna Austria

ISBN: (纸本)9781424481262

Asset allocation is critical for the portfolio management process. In this paper, we solve a dynamic asset allocation problem through a multiperiod stochastic programming model. The objective is to maximise the expected utility of wealth at the end of the planning period. To improve the optimisation process of the model, we employ swarm intelligent optimisers, the Bacterial Foraging Optimisation (BFO) and the Particle Swarm Optimisation (PSO) algorithm. A hybrid optimiser using the BFO for initialisation and the Sequential Quadratic programming (SQP) for searching the decision variables is also suggested. The results are compared with the stand-alone SQP and the canonical Genetic Algorithm. We have performed numerical experiments on 2-asset and 4-asset allocation problem respectively. The numerical results suggest that the hybrid method provides a better result especially for the 4-asset case, with improved fitness value and robustness than using BFO, PSO, GA, or SQP alone.

关键词： bacterial foraging optimisation canonical genetic algorithm dynamic asset allocation financial management hybrid optimiser optimisation process particle swarm optimisation particle swarm optimisation planning period portfolio management process quadratic programming robustness sequential quadratic programming stochastic programming stochastic programming model swarm intelligent optimiser

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A stochastic programming model for Closed-loop Supply Chain Network Design Based on Environmental Responsibility

A Stochastic Programming Model for Closed-loop Supply Chain ...

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IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

作者： Yang Yu-xiang Guo Yu-shi Huang Zu-qing China Jiliang Univ Coll Econ & Management Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781479960583

In this paper, a two-stage stochastic programming model is proposed in which uncertainty of demands and the amount of returned products are considered, and specially, the environmental responsibility also considered. A hybrid solution method is developed. Finally, numerical examples are proposed to design a closed-loop supply chain network.

关键词： closed-loop supply chain stochastic programming model hybrid solution method environmental responsibility

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A stochastic programming model for Closed-loop Supply Chain Network Design Based on Environmental Responsibility

A Stochastic Programming Model for Closed-loop Supply Chain ...

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Yang Yu-xiang Guo Yu-shi Huang Zu-qing College of Economics Management China Jiliang University College of Economics and Management China Jiliang University

In this paper,a two-stage stochastic programming model is proposed in which uncertainty of demands and the amount of returned products are considered,and specially,the environmental responsibility also considered.A hybrid solution method is ***,numerical examples are proposed to design a closed-loop supply chain network.

关键词： closed-loop supply chain stochastic programming model hybrid solution method environmental responsibility

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Scenario-based stochastic linear programming model for multi-period disassembly lot-sizing problems under random lead time

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IFAC-PapersOnLine 2019年第13期52卷 595-600页

作者： Slama, I. Ben-Ammar, O. Masmoudi, F. Dolgui, A. IMT Atlantique LS2N UMR-CNRS 6004 La Chantrerie 4 rue Alfred Kastler - B.P. 20722 Nantes44307 France Faculty of Economics and Management Sciences of Sfax MODILS Airport Road km 4 BP 1088 Sfax3018 Tunisia University of Sfax Tunisia

In the last few years, there has been a growing interest in the disassembly scheduling problem to fulfil the demands of individual disassembled parts over a given planning horizon. An analysis of the literature shows that the disassembly lead time is often considered deterministic. Indeed, in real-life systems, this parameter is rarely known and often has uncertain values that can be caused by the complexity of disassembly operation. In this study, a new scenario-based stochastic linear programming model is proposed to deal with a multi-period, single product type and two-level disassembly lot-sizing problem under lead time uncertainty. The demand for each component is known for each time period and the real disassembly lead time of end-of-life product is an independent random discrete variable with a known probability distribution. The proposed model is used to determine the optimal quantity for disassembled end-of-life products in order to minimize the setup cost for end-of-life product and the sum of average inventory holding and backlogging costs for each component, over the planning horizon and all scenarios. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： stochastic models Linear programming Probability distributions stochastic programming stochastic systems Uncertainty analysis Lot sizing problems Random lead time Reverse logistics Scenario based stochastic programming model

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Scenario-based stochastic linear programming model for multi-period disassembly lot-sizing problems under random lead time 9

Scenario-based stochastic linear programming model for multi...

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9th IFAC/IFIP/IFORS/IISE/INFORMS Conference on Manufacturing modelling, Management and Control (IFAC MIM)

作者： Slama, I. Ben-Ammar, O. Masmoudi, F. Dolgui, A. IMT Atlantique LS2N UMR CNRS 6004 4 Rue Alfred Kastler BP 20722 F-44307 Nantes France MODILS Fac Econ & Management Sci Sfax Airport Rd Km 4BP 1088 Sfax 3018 Tunisia Univ Sfax Engn Sch Sfax Lab Mech Modeling & Prod LA2MP Sfax Tunisia

In the last few years, there has been a growing interest in the disassembly scheduling problem to fulfil the demands of individual disassembled parts over a given planning horizon. An analysis of the literature shows that the disassembly lead time is often considered deterministic. Indeed, in real-life systems, this parameter is rarely known and often has uncertain values that can be caused by the complexity of disassembly operation. In this study, a new scenario-based stochastic linear programming model is proposed to deal with a multi-period, single product type and two-level disassembly lot-sizing problem under lead time uncertainty. The demand for each component is known for each time period and the real disassembly lead time of end-of-life product is an independent random discrete variable with a known probability distribution. The proposed model is used to determine the optimal quantity for disassembled end-of-life products in order to minimize the setup cost for end-of-life product and the sum of average inventory holding and backlogging costs for each component, over the planning horizon and all scenarios. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Reverse logistic disassembly lot-sizing problem random lead time stochastic programming model scenario-based approach

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Interactive fuzzy random multiobjective programming based on M-α-Pareto optimality and stochastic programming models

Interactive fuzzy random multiobjective programming based on...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Katagiri, H Sakawa, M Kato, K Nishizaki, I Danjyo, H Hiroshima Univ Grad Sch Engn Higashihiroshima 7398527 Japan

ISBN: (纸本)0780392981

This paper deals with multiobjective linear programming problems involving fuzzy random variable coefficients and provides new solution concepts based on M alpha-Pareto optimality and stochastic programming models. Fuzzy goals are introduced to consider the imprecise of the decision maker's judgment for objective functions. After the formulated problem is transformed into the deterministic one, an interactive algorithm based on the reference point method is constructed to solve the deterministic problem.

关键词： fuzzy random variable multiobjective linear programming M-alpha-Pareto optimality stochastic programming model interactive decision making

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Studies of stochastic programming models using possibility and necessity measures for linear programming problems with fuzzy random variable coefficients

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE 2005年第1期88卷 68-75页

作者： Katagiri, H Sakawa, M Ishii, H Hiroshima Univ Grad Sch Engn Higashihiroshima 7398527 Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan

This paper considers the multi-objective linear programming problem and discusses the case in which the coefficients of the objective function are fuzzy random variables. First, the fuzzy goal is introduced into the objective function, considering the fuzzy decision of the human decision-maker. We consider a model in which the possibility or the necessity that the objective function value achieves the fuzzy goal is maximized on the basis of fuzzy programming or possibility programming. It is noted that the possibility or necessity fluctuates stochastically, and a decision-making process based on the stochastic programming model is proposed. After modifying the problem with constraint into an equivalent deterministic problem, the convex programming problem with a parameter is introduced. Then, an algorithm is proposed in which the optimal solution is derived, combining nonlinear programming and the bisection method. (C) 2004 Wiley Periodicals, Inc.

关键词： fuzzy random transform possibility measure necessity measure stochastic programming model convex programming

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Valuation of Reverse Mortgages Using stochastic programming models

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财务金融学刊 2019年第4期27卷 61-88页

作者：何曉緯劉明郎曾郁婷

The aging society problems spread all around the world in recent years. The elders face economic impact and financial difficulties after they retired. The reverse mortgage (RM) programs are then introduced to alleviate the elders' income shortages in many countries. In this paper we propose a bi-objective stochastic programming model to evaluate the fair payment of RM programs. We use Lee-Carter model (1992), CIR-SR model (1985), and Geometric Brownian motion model to forecast mortality, interest rates, and house prices, respectively. Numerical tests and sensitivity analyses using data from Taiwan are also performed to demonstrate the valuation procedure of RM programs.

关键词： Reverse mortgage home equity conversion mortgage stochastic programming model

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modelling a resilient yard template under storage demand fluctuations in a container terminal

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ENGINEERING OPTIMIZATION 2019年第9期51卷 1547-1566页

作者： He, Junliang Tan, Caimao Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai Peoples R China Shanghai Maritime Univ Engn Res Ctr Container Supply Chain Technol Minist Educ Shanghai Peoples R China

This article investigates the generation of a resilient yard template, which has the property of resilience under storage demand fluctuations. A stochastic programming model is formulated aiming at minimizing the risk of containers without available storage slots being assigned in the designated area. Furthermore, a corresponding particle swarm optimization algorithm is proposed for solving the model. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model and solution approaches.

关键词： Container terminal resilient yard template storage demand fluctuation stochastic programming model

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