检索结果-内蒙古大学图书馆

作者： Antoine Verrier Universite de recherche Paris Sciences et Lettres PSL Research University

学位级别：博士

In liberalised power markets the inability of consumers to adapt their demand in accordance to wholesale prices is increasingly challenged. Nowadays technical progress within the smart grid industry constitutes promising changes for the integration of end-users into the power system, but the deployment of Demand Response (DR) still faces the challenge of its economic viability. This thesis aims to assess the economic value of DR. We rely on an energy-only market model under uncertainty in order to quantify the revenues of DR aggregators, classified by category of consumers and end-uses of electricity. The model is formulated as a multi-stage stochastic linear problem and solved by stochastic dual dynamic programming. It appears that in France, industrial load-shedding and load-shifting of cement, paper, and pulp are profitable. For residential and tertiary consumers, load-shifting of electric heating is not profitable. We also show that the capacity value of DR is crucial. Overall, results show that DR is beginning to become economically attractive, but that fixed costs of smart grid technologies still need to come down further to fully develop its potential.

关键词： Demand Response Aggregator business case Electricity markets Uncertainty stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Hydropower Production Scheduling using Stochastisc dual dynamic programming subject to environmental constraints

Hydropower Production Scheduling using Stochastisc Dual Dyna...

引用

作者： Arvidsen, Håkon Ingvar University of Bergen

学位级别：硕士

Oppgaven utforsker vannkraftproduksjonsplanlegging i Bergsdalen vassdraget, styrt av BKK, ved hjelp av Stokastisk dual Dynamisk Programmering. Systemet er under et sett med miljørestriksjoner, innført av NVE, som utfordrer løsningsmetoden. Approksimasjoner a miljørestriksjonene er presentert og diskutert, siden løsningsmetoden er prioritert.

关键词： optimization Hydropower scheduling stochastic dual dynamic programming renewable energy dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Multi-Stage stochastic programming with CVaR: Modeling, Algorithms and Robustness

Multi-Stage Stochastic Programming with CVaR: Modeling, Algo...

引用

作者： Kozmík, Václav Charles University of Prague

Multi-Stage stochastic programming with CVaR: Modeling, Algorithms and Robustness RNDr. Václav Kozmík Abstract: We formulate a multi-stage stochastic linear program with three different risk measures based on CVaR and discuss their properties, such as time consistency. The stochastic dual dynamic programming algorithm is described and its draw- backs in the risk-averse setting are demonstrated. We present a new approach to evaluating policies in multi-stage risk-averse programs, which aims to elimi- nate the biggest drawback - lack of a reasonable upper bound estimator. Our approach is based on an importance sampling scheme, which is thoroughly ana- lyzed. A general variance reduction scheme for mean-risk sampling with CVaR is provided. In order to evaluate robustness of the presented models we extend con- tamination technique to the case of large-scale programs, where a precise solution cannot be obtained. Our computational results are based on a simple multi-stage asset allocation model and confirm usefulness of the presented procedures, as well as give additional insights into the behavior of more complex models. Keywords: Multi-stage stochastic programming, stochastic dual dynamic programming, im- portance sampling, contamination, CVaR

关键词： Multi-stage stochastic programming stochastic dual dynamic programming importance sampling contamination CVaR

来源：评论

学校读者我要写书评

暂无评论

REGULARIZED DECOMPOSITION OF HIGH-DIMENSIONAL MULTISTAGE stochastic PROGRAMS WITH MARKOV UNCERTAINTY

引用

SIAM JOURNAL ON OPTIMIZATION 2018年第1期28卷 575-595页

作者： Asamov, Tsvetan Powell, Warren B. Princeton Univ Dept Operat Res & Financial Engn Princeton NJ 08544 USA

We develop a quadratic regularization approach for the solution of high-dimensional multistage stochastic optimization problems characterized by a potentially large number of time periods/stages (e.g., hundreds), a high-dimensional resource state variable, and a Markov information process. The resulting algorithms are shown to converge to an optimal policy after a finite number of iterations under mild technical assumptions. Computational experiments are conducted using the setting of optimizing energy storage over a large transmission grid, which motivates both the spatial and temporal dimensions of our problem. Our numerical results indicate that the proposed methods exhibit significantly faster convergence than their classical counterparts, with greater gains observed for higher-dimensional problems.

关键词： multistage stochastic optimization quadratic regularization nested decomposition stochastic dual dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Distribution-free chance-constrained load balance model for the operation planning of hydrothermal power systems coupled with multiple renewable energy sources

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年第PartB期142卷

作者： Morillo, Jose L. Zephyr, Luckny Perez, Juan F. Cadena, Angela Anderson, C. Lindsay Univ Andes Bogota Colombia Laurentian Univ Sudbury ON Canada Cornell Univ Ithaca NY USA

We are interested in the potential risk of short-term load imbalance in hydro-thermal power systems under high integration of renewable energy sources, including wind, solar, and biomass. Toward this end, the shortterm load balance across the system is formulated as a joint chance constraint. Due to non-convexity issues and the lack of information about the joint probability distribution of the renewable energy resources, we analyze a distribution-free robust relaxation and a p-efficiency approximation of the joint chance constraint. Our proposal is embedded within the widespread SDDP algorithm, and compared with the popular CVaR scheme on a simplified version of the Colombian power system.

关键词： Power systems Renewable energy stochastic dual dynamic programming Robust optimization p-efficient points

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Optimal Multipurpose-Multireservoir Operation Model with Variable Productivity of Hydropower Plants

引用

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2011年第3期137卷 258-267页

作者： Goor, Q. Kelman, R. Tilmant, A. Catholic Univ Louvain Earth & Life Inst B-1348 Louvain Belgium Power Syst Res Rio De Janeiro Brazil Swiss Fed Inst Technol Inst Environm Engn Zurich Switzerland UNESCO IHE Dept Management & Inst Delft Netherlands

stochastic dual dynamic programming (SDDP) is one of the few methods available to solve multipurpose-multireservoir operation problems in a stochastic environment. This algorithm requires that the one-stage optimization problem be a convex program so that the efficient Benders decomposition scheme can be implemented to handle the large state-space that characterizes multireservoir operation problems. When working with hydropower systems, one usually assumes that the production of hydroelectricity is dominated by the release term and not by the head (storage) term to circumvent the nonlinearity of the hydropower production function. Although this approximation is satisfactory for high head power stations for which the difference between the maximum and the minimum head is small compared to the maximum head, it may no longer be acceptable when a significant portion of the energy originates from low and/or medium head power plants. Recent developments improve the representation of the nonlinear hydropower function through a convex hull approximation of the true hydropower function. A network of hydropower plants and irrigated areas in the Nile Basin is used to illustrate the difference between the two SDDP formulations on the energy generation and the allocation decisions. DOI: 10.1061/(ASCE)WR.1943-5452.0000117. (C) 2011 American Society of Civil Engineers.

关键词： Hydroeconomic optimization stochastic dual dynamic programming Variable productivity of hydropower plants Nile River Basin

来源：评论

学校读者我要写书评

暂无评论

Worst-Case-Expectation Approach to Optimization Under Uncertainty

引用

OPERATIONS RESEARCH 2013年第6期61卷 1435-1449页

作者： Shapiro, Alexander Tekaya, Wajdi Soares, Murilo Pereira da Costa, Joari Paulo Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Cambridge Syst Associates Cambridge CB5 8AF England Operador Nacl Sistema Eletr BR-20211160 Rio De Janeiro RJ Brazil

In this paper we discuss multistage programming with the data process subject to uncertainty. We consider a situation where the data process can be naturally separated into two components: one can be modeled as a random process, with a specified probability distribution, and the other one can be treated from a robust (worst-case) point of view. We formulate this in a time consistent way and derive the corresponding dynamic programming equations. To solve the obtained multistage problem, we develop a variant of the stochastic dual dynamic programming method. We give a general description of the algorithm and present computational studies related to planning of the Brazilian interconnected power system.

关键词： multistage stochastic programming robust optimization time consistency dynamic equations stochastic dual dynamic programming sample average approximation risk-neutral and risk-averse approaches case studies

来源：评论

学校读者我要写书评

暂无评论

Water values and marginal costs for power generation planning under more restrictive constraints and a more detailed representation of hydro plants

引用

ELECTRIC POWER SYSTEMS RESEARCH 2024年 235卷

作者： da Cruz, Cristiane Barbosa Brandao, Lilian Chaves Diniz, Andre Luiz CEPEL Rio De Janeiro Brazil

Power generation planning for real large-scale systems is a complex multistage stochastic problem, which requires modeling approximations for the representations of system components and operating constraints in order to be efficiently solved by the stochastic dual dynamic programming (SDDP) approach. This paper presents an analysis of the impacts of a more detailed representation of the hydro plants and the inclusion of more restrictive hydraulic constraints in the recourse functions that are built by the SDDP strategy, as well as in the simulation outputs of this problem. While some results are rather obvious - as the increase in systems costs - others are counterintuitive, such as the decrease in thermal generation levels and water values in some situations. Results are presented for the individualized modeling of the hydro plants in the official models applied for long-term hydrothermal planning in Brazil.

关键词： Power generation planning stochastic dual dynamic programming Water values Hydraulic constraints

来源：评论

学校读者我要写书评

暂无评论

Uncertainty modeling with the open source framework urbs

引用

ENERGY STRATEGY REVIEWS 2020年 29卷

作者： Stueber, Magdalena Odersky, Leonhard Tech Univ Munich Chair Renewable & Sustainable Energy Syst Munich Germany

The transition of the energy system to a renewable energy source based system requires methods on how to incorporate uncertainty in modeling the energy system. There are different approaches starting from mainly variation based approaches up to including stochastic programming. For this work, a modified version of stochastic dual dynamic programming (SDDP) has been implemented into the open source framework urbs. The framework consists of a linear optimization for energy dispatch and expansion planning and has been extended to include uncertain inputs for volatile energy sources like wind or solar. Different paths on how much these sources are providing for the feed-in can be modeled by packing one or more time steps to so-called realizations with different probabilities. The solution algorithm itself is based on a modified Benders decomposition approach, which is adapted to the constraints specifically relevant for power system analysis. The relation of SDDP and Benders decomposition is used to overcome the exponential growth of variables typically involved in classic stochastic programming. The novel approach is tested on a case study of Germany and shows how a more realistic economic dispatch can be calculated with a stochastic approach compared to a deterministic one.

关键词： Linear optimization stochastic dual dynamic programming Open source Economic dispatch

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：