检索结果-内蒙古大学图书馆

Solving two-stage robust optimization problems using a column-and-constraint generation method

OPERATIONS RESEARCH LETTERS 2013年第5期41卷 457-461页

作者： Zeng, Bo Zhao, Long Univ S Florida Dept Ind & Management Syst Engn Tampa FL 33620 USA

In this paper, we present a column-and-constraint generation algorithm to solve two-stage robust optimization problems. Compared with existing Benders-style cutting plane methods, the column-and-constraint generation algorithm is a general procedure with a unified approach to deal with optimality and feasibility. A computational study on a two-stage robust location-transportation problem shows that it performs an order of magnitude faster. (c) 2013 Elsevier B.V. All rights reserved.

关键词： two-stage robust optimization Cutting plane algorithm Location-and-transportation

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimization scheduling for integrated energy systems considering ammonia energy and waste heat utilization

引用

ENERGY CONVERSION AND MANAGEMENT 2024年 319卷

作者： Yang, Shuoshi Wu, Hao Song, Jianzhao Li, Haolin Chen, Haipeng Northeast Elect Power Univ Key Lab Modern Power Syst Simulat & Control & Rene Minist Educ Jilin 132012 Peoples R China Northeast Elect Power Univ Dept Elect Engn Jilin 132012 Peoples R China TBEA Shenyang Transformer Grp Co Ltd Shenyang 110144 Peoples R China State Grid Jilin Elect Power Co Ltd Baishan Power Supply Co Baishan 134300 Peoples R China

To balance the stability and economic benefits of integrated energy systems (IES) during low-carbon optimization, this paper proposes a two-stage robust optimization scheduling method that considers ammonia energy and waste heat utilization. Firstly, this paper analyzes the Power-to-Ammonia (P2A) operational mechanism and the energy input-output transformation relationship and establishes a Power-to-Ammonia equipment model incorporating waste heat utilization. Subsequently, the low-carbon operational characteristics of the integrated energy system with cooperative operation between Power-to-Ammonia and coal-fired units are explored by integrating Power-to-Ammonia with ammonia-coal co-firing technology. Then, the paper uses an adjustable uncertainty set to describe the variability of renewable generation (RG) and constructs a max-min structured integrated energy system with a two-stage robust optimization scheduling model to minimize the worst-case scenario system operating costs. Finally, the Column-and-Constraint Generation (C&CG) algorithm decomposes the two-stage robust optimization issue into a master problem and sub-problems for the iterative solution. Furthermore, the proposed method is simulated in an actual integrated energy system in northern China. Simulation results indicate that with the intervention of renewable generation uncertainty, the model developed in this study reduces operating costs and carbon emissions by 13.98 % and 20.95 %, respectively, effectively enhancing the capability for low-carbon economic operation. This study provides crucial theoretical support for advancing the low-carbon energy conversion of integrated energy systems.

关键词： Power-to-ammonia Integrated energy systems Ammonia-coal co-firing Waste heat utilization two-stage robust optimization

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimization for practical reactive power in distribution network based on multiple constraint convex approximation

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 134卷 107414-107414页

作者： Zeng, Xi Wu, Hongbin Ding, Ming Bi, Rui Xu, Bin Ding, Jinjin Hefei Univ Technol Anhui Prov Key Lab Renewable Energy Utilizat & En Hefei 230009 Peoples R China State Grid Anhui Elect Power Res Inst Hefei 230601 Peoples R China

In multi-time-scale optimization frameworks of daily, hourly, and minute levels, centralized optimization has a demand for real-time communication and prediction technology. In the distribution network of an undeveloped area, the minute level optimization does not work because of the lack of accurate prediction and real-time communication. The practical reactive power originally obtained from the minute-level optimization does not exist, and the uncertainty should be considered in hourly level optimization. In this study, a two-stage robust optimization at the hourly level is proposed to minimize the network loss without the minute level optimization. A simple data-based method of modeling multiple uncertainty is proposed, which directly uses historical data with minimal mathematical knowledge. The multiple uncertainty set contains the interval constraint and convex hull of an ellipsoid constraint. The convex hull of the ellipsoid constraint is formed by ellipse tangents. In addition, the practical reactive power cannot be obtained through the common robust inverter dispatch strategy, which sets the maximum available active power as an uncertain variable. A pseudo-decoupling dispatch strategy is proposed to approximate the separation of reactive power and uncertainty and obtain the practical reactive power. The Benders decomposition framework is used to solve the two-stage robust optimization, and a feasible linear constraint generated from the subproblem is added to the master problem. The simulation results demonstrate the effectiveness of the proposed method.

关键词： Multiple uncertainty set Photovoltaic inverter dispatch strategy two-stage robust optimization Distribution systems

来源：评论

学校读者我要写书评

暂无评论

Saddle point approximation approaches for two-stage robust optimization problems

引用

JOURNAL OF GLOBAL optimization 2020年第4期78卷 651-670页

作者： Zhang, Ning Fang, Chang Dongguan Univ Technol Sch Comp Sci & Technol Dongguan 523808 Guangdong Peoples R China Anhui Normal Univ Sch Econ & Management 189 Jiuhua South Rd Wuhu City 241002 Anhui Peoples R China

This paper aims to present improvable and computable approximation approaches for solving the two-stage robust optimization problem, which arises from various applications such as optimal energy management and production planning. Based on sampling finite number scenarios of uncertainty, we can obtain a lower bound approximation and show that the corresponding solution is at least -level feasible. Moreover, piecewise linear decision rules (PLDRs) are also introduced to improve the upper bound that obtained by the widely-used linear decision rule. Furthermore, we show that both the lower bound and upper bound approximation problems can be reformulated into solvable saddle point problems and consequently be solved by the mirror descent method.

关键词： two-stage robust optimization Randomized approach Piecewise linear decision rule Saddle point problem Mirror descent algorithm

来源：评论

学校读者我要写书评

暂无评论

Exploiting the Structure of two-stage robust optimization Models with Exponential Scenarios

引用

INFORMS JOURNAL ON COMPUTING 2021年第1期33卷 143-162页

作者： Doulabi, Hossein Hashemi Jaillet, Patrick Pesant, Gilles Rousseau, Louis-Martin Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ H3G 1M8 Canada Univ Montreal Interuniv Res Ctr Enterprise Networks Logist & Tr Montreal PQ H3C 3J7 Canada MIT Dept Elect Engn & Comp Sci Lab Informat & Decis Syst Operat Res Ctr Cambridge MA 02139 USA Polytech Montreal Dept Comp & Software Engn Montreal PQ H3T 1J4 Canada Polytech Montreal Dept Math & Ind Engn Montreal PQ H3T 1J4 Canada

This paper addresses a class of two-stage robust optimization models with an exponential number of scenarios given implicitly. We apply Dantzig-Wolfe decomposition to exploit the structure of these models and show that the original problem reduces to a single-stage robust problem. We propose a Benders algorithm for the reformulated single-stage problem. We also develop a heuristic algorithm that dualizes the linear programming relaxation of the inner maximization problem in the reformulated model and iteratively generates cuts to shape the convex hull of the uncertainty set. We combine this heuristic with the Benders algorithm to create a more effective hybrid Benders algorithm. Because the master problem and subproblem in the Benders algorithm are mixed-integer programs, it is computationally demanding to solve them optimally at each iteration of the algorithm. Therefore, we develop novel stopping conditions for these mixed-integer programs and provide the relevant convergence proofs. Extensive computational experiments on a nurse planning problem and a two-echelon supply chain problem are performed to evaluate the efficiency of the proposed algorithms.

关键词： integer programming Dantzig-Wolfe decomposition two-stage robust optimization

来源：评论

学校读者我要写书评

暂无评论

A two-stage robust optimization for Centralized-Optimal Dispatch of Photovoltaic Inverters in Active Distribution Networks

引用

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2017年第2期8卷 744-754页

作者： Ding, Tao Li, Cheng Yang, Yongheng Jiang, Jiangfeng Bie, Zhaohong Blaabjerg, Frede Xi An Jiao Tong Univ Dept Elect Engn State Key Lab Elect Insulat & Power Equipment Xian 710049 Peoples R China Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

Optimally dispatching photovoltaic (PV) inverters is an efficient way to avoid overvoltage in active distribution networks, which may occur in the case of the PV generation surplus load demand. Typically, the dispatching optimization objective is to identify critical PV inverters that have the most significant impact on the network voltage level. Following, it ensures the optimal set-points of both active power and reactive power for the selected inverters, guaranteeing the entire system operating constraints (e.g., the network voltage magnitude) within reasonable ranges. However, the intermittent nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust centralized-optimal dispatch model is proposed in this paper to achieve a robust PV inverter dispatch solution considering the PV output uncertainties. In addition, the conic relaxation-based branch flow formulation and the column-and-constraint generation algorithm are employed to deal with the proposed robust optimization model. Case studies on a 33-bus distribution network and comparisons with the deterministic optimization approach have demonstrated the effectiveness of the proposed method.

关键词： Active distribution network column-and-constraint generation algorithm optimal inverter dispatch (OID) photovoltaic generation two-stage robust optimization

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimization for optimal operation of hybrid hydrogen-electricity storage system considering ladder-type carbon trading

引用

JOURNAL OF ENERGY STORAGE 2024年 100卷

作者： Zhang, Luliang Hua, Dingyan Zheng, J. H. Li, Zhigang South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China

The prominent problems of renewable energy curtailment and its uncertainty have become a hot topic. To the end, with consideration of environmental friendliness, energy utilization efficiency and operation cost, this paper proposes a hybrid hydrogen-electricity storage system (HHES) operation framework comprising assorted types of coupling devices and carbon capture system (CCS) under ladder-type carbon trading (LCT) mechanism. By considering energy balance constraints, equipments' operation constraints and erratic rates of RESs and multiple loads, a scheduling model with source-load uncertainties is developed with the goal of minimizing the system's operation cost and carbon emission. Then, a two-stage tri-level robust model is built to find the optimal scheduling plan under multiple uncertainties given the various sources and loads. The first level is to make an optimal dispatch plan and the second level is to find the worst scenario under the given uncertainty set. The third level aims at enhancing renewable energy accommodation rate and reducing load shedding rate in the worst case. Since the model is formed as a tri-level mixed integer optimization problem, the Column and Constraint Generation (CCG) method is adopted to achieve the optimal result. Finally, numerical analyses are performed. The results show that the proposed approach realizes a flexible dispatch of multiple energy and a high utilization level of multiple storages. Furthermore, this paper studies the influence of uncertainty and uncertainty budget parameters with the comparison of the deterministic model and robust models with different uncertainties. The results show that the proposed HHES has strong robustness and can provide a good reference for energy dispatch.

关键词： Hybrid hydrogen-electricity storage system two-stage robust optimization Source-load uncertainties Ladder-type carbon trading

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimization strategy for spatially-temporally correlated data centers with data-driven uncertainty sets

引用

ELECTRIC POWER SYSTEMS RESEARCH 2023年第1期221卷

作者： Yang, Zhihao Trivedi, Anupam Liu, Haoming Ni, Ming Srinivasan, Dipti Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 119260 Singapore

Data center buildings (DCBs) in data center parks consume significant and ever-growing amounts of electric power for processing tremendous data workloads in a modern city. The workloads are divided into two types: interactive workloads (IWs) with spatially transferrable characteristics and batch workloads (BWs) with temporally shiftable characteristics. The unique spatially-temporally workloads show great demand response capability, enabling reducing the electricity cost of DCBs. However, the source-load uncertainties such as the number of arriving workloads, and photovoltaic output affect the cost-efficient operation of DCBs in the elec-tricity market. Inadequate server numbers during worst-case scenarios may result in the inability to fulfill user contracts. This paper presents a model for DCBs that incorporates battery energy storage systems, photovoltaic generation, and electrical loads for processing spatially-temporally correlated workloads. Considering multiple uncertainties, a two-stage robust optimization strategy is proposed to coordinate workload and power for DCBs. To accurately determine the boundaries of the uncertainty sets, a data-driven method using the 1-Wasserstein metric is adopted. This method is reformulated into a distributionally robust chance-constrained programming model. The nested column-and-constraint generation (C&CG) method is used to resolve the established two-stage robust optimization problem with mixed-integer recourse. Finally, case studies verify the effectiveness of the proposed method.

关键词： Data center Demand response Electricity market Nested column-and-constraint generation (C&CG) two-stage robust optimization

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimization of regional integrated energy systems considering uncertainties of distributed energy stations

引用

FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Zong, Xuanjun Yuan, Yue Hohai Univ Coll Energy & Elect Engn Nanjing Peoples R China

For a regional integrated energy system (RIES) composed of an energy supply network and distributed energy station, the uncertainty of distributed photovoltaic (PV) output and the fluctuation of various loads pose significant challenges to the stability of system operation and the accuracy of optimal scheduling. In order to enhance the operational reliability of regional integrated energy systems and reduce the impact of photovoltaic and load uncertainties on distributed energy stations, this study proposes robust optimization method of regional integrated energy systems that takes into account the uncertainty of the distributed energy station. First, the regional integrated energy system is divided into an upper electric-gas energy supply network and a lower distributed energy station. The upper model mainly realizes energy transmission, while the lower model is a two-stage robust optimization model of distributed energy stations in the form of min-max-min, which mainly realizes flexible energy supply of different types of energy. Then, the lower two-stage robust optimization model is simplified and solved using a column and constraint generation (CCG) algorithm. After that, an alternating direction method of multipliers (ADMM) is used to solve the upper and lower models of the regional integrated energy system, and the solution scale is reduced while ensuring the correlation between the energy transmission network and the distributed energy stations. Finally, a test example is provided to illustrate the effectiveness and usefulness of the proposed method. It follows from simulation results that the robust optimization method can effectively reduce the instability of the system operation caused by uncertainty factors and improve the system's anti-interference ability, and in addition, systems with high penetration levels of photovoltaic output will benefit more from robust optimization.

关键词： two-stage robust optimization regional integrated energy system alternating direction method of multipliers column and constraint generation algorithm distributed optimization

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimization model for park integrated energy system based on dynamic programming

引用

APPLIED ENERGY 2022年 308卷 118249-118249页

作者： Wu, Min Xu, Jiazhu Zeng, Linjun Li, Chang Liu, Yuxing Yi, Yuqin Wen, Ming Jiang, Zhuohan Hunan Univ Coll Elect & Informat Engn Changsha Peoples R China Tech Univ Denmark Dept Elect Engn Copenhagen Denmark State Grid Hunan Elect Power Co Ltd Econ Changsha Peoples R China Tech Res Inst Changsha Peoples R China

The promotion and construction of park integrated energy system (PIES) has strengthened the interaction among electric, gas, heating and cooling systems. However, the static programming strategy (SPS) of PIES results in problems such as lower system economics and poorer reliability of energy supply. Therefore, a suitable planning method is required to promote the economic operation of PIES under multiple uncertainties. Based on the background, this study proposes a two-stage robust optimization model based on dynamic programming strategy (DPS) for PIES. Firstly, the coupled devices and energy networks in the system are analyzed in detail to comprehensively identify the complex interactions among multiple energy carriers. Moreover, a DPS is introduced to improve the economic efficiency of PIES. Then, a two-stage robust model is established to solve the heterogeneous uncertainties in the planning strategy. Specifically, the column and constraint generation (C&CG) algorithm is used to solve the optimization model thereby obtain the equipment configuration scheme for each planning phase. Finally, the effectiveness of the proposed method is verified by comprehensive case studies on a test system.

关键词： Column and constraint decomposition Dynamic programming strategy Park integrated energy system two-stage robust optimization

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：