检索结果-内蒙古大学图书馆

Co-optimization of Supply and Demand Resources for Load Restoration of Distribution System Under Extreme Weather

IEEE ACCESS 2021年 9卷 122907-122923页

作者： Zhu, Xi Zeng, Bo Li, Yonggang Liu, Jiaomin State Grid Beijing Elect Power Co Econ & Technol Beijing 100055 Peoples R China North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Baoding 071003 Peoples R China

To deal with the issue of the distribution system (DS) resilience enhancement under extreme weather events, this paper presents a new methodological framework for enhancing the load restoration of DS during a hurricane. As distinct from existing studies, this approach integrates mobile emergency generators (MEGs) and prosumer communities (PCs) incorporating combined heat and power (CHP) units, electric boilers (EBs), photovoltaic (PV) sources, and demand response (DR) resources and comprehensively explores the coordination and flexibility of supply-side and demand-side resources to boost the post-disaster DS recovery. The discussed problem is formulated by using a two-stage robust optimization model. In the first stage, the MEGs are pre-positioned prior to the hurricane with the objective of minimizing the outage cost of the load to promote the capability of DS to resist extreme disturbance. The second stage determines the real-time allocation of MEGs, output power of CHP units and EBs, and the power consumption of electric loads after the hurricane to maximize DS's load recovery considering the worst-case of the uncertainty realization. Since the fragility analysis of network elements has an essential impact on the efficacy of the optimal strategy, we introduce the Z-number-based approach to scientifically determine the failure probability of components considering the effect of the aging of components and the credibility of the failure information obtained from the fragility. The effectiveness of the proposed methodology is examined based on an IEEE 123-bus distribution test system, and the obtained results confirm the validity of the proposed approach in actual implementations.

关键词： Cogeneration Meteorology Hurricanes Resilience Renewable energy sources Couplings Resists Extreme weather events resilience demand response two-stage robust optimization Z-number

来源：评论

学校读者我要写书评

暂无评论

two-stage robust railway line-planning approach with passenger demand uncertainty

引用

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2021年 152卷 102372-102372页

作者： Pu, Song Zhan, Shuguang Chengdu Technol Univ Sch Econ & Management Chengdu 610031 Peoples R China Southwest Jiaotong Univ Sch Transportat & Logist Chengdu 610031 Sichuan Peoples R China

A railway line-planning problem is one of the fundamental problems in the strategic planning of railway operations. Operation zone, frequency, stop schedule, and passenger distribution for each train based on passenger demand are determined to minimize both the operation cost of the railway enterprise and the total travel cost to the passengers. However, passenger demand uncertainty makes balancing transport capacity and fluctuating demand challenging. Therefore, this paper proposes a two-stage robust optimization model wherein the nominal line plan is determined in the first stage (i.e., the case in which passenger demand has no fluctuation) and the rescheduled line plan based on the nominal line plan is determined according to the demand realization in the second stage. A Lagrangian relaxation algorithm and some strengthening techniques are designed. The model and algorithm are tested on real-world instances of the Wuhan-Guangzhou high-speed railway line under uncertain passenger demands. Computational results indicate that the proposed solution algorithm can yield a high-quality solution in 3600 s. In addition, the proposed two-stage robust solution can help minimize both operation and travel costs on average when compared with the nominal solution under uncertainty realization.

关键词： Railway line planning Passenger demand uncertainty two-stage robust optimization Lagrangian relaxation

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective robust optimization of Hybrid AC/DC Distribution Networks Considering Flexible Interconnection Devices

引用

IEEE ACCESS 2021年 9卷 166048-166057页

作者： Wang, Xiaoxue Yang, Wenquan Liang, Dong Hebei Univ Technol State Key Lab Reliabil & Intelligence Elect Equip Tianjin 300401 Peoples R China

Hybrid AC/DC distribution networks with the high-efficiency consumption and high-proportion access of new energy have become a crucial trend for future modern distribution networks. High penetration of renewable energy brings various controllable resources along with uncertainties to hybrid AC/DC distribution networks, making conventional single objective optimization fail to meet optimal operation requirements of flexibility and reliability. In this paper, considering uncertainties of distribution generations and loads, a multi-objective robust optimization model based on various controllable devices is proposed. To increase resource utilization, the proposed method comprehensively and properly models the full variety of possible control means (i.e., flexible distribution switch, voltage source converter, energy storages, et al). Utilizing the abundant control means, a multi-objective optimization which minimizes network losses, voltage deviations and operation cost simultaneously is modeled. Then, based on the multi-objective model, a two-stage robust optimization based on second order cone method and column constraint generation algorithm is proposed to achieve the solution, which can deal with the fluctuation of loads and renewable energy quickly and effectively. Outdoing traditional single objective robust optimization, our multi-objective robust optimization based on various controllable resources can decease the network losses, increase the profits and improve voltage profiles significantly, which obviously improves the safety, flexibility and economy simultaneously. Finally, compared with existing robust optimization, the proposed method is tested in numerous case studies to verify its effectiveness and advantages in a modified IEEE 33-node system.

关键词： optimization Distribution networks Costs Uncertainty Reactive power Voltage control Renewable energy sources Hybrid AC DC distribution networks multi-objective optimization two-stage robust optimization flexible interconnection devices column constraint generation algorithm

来源：评论

学校读者我要写书评

暂无评论

Transactive Energy-Based Joint optimization of Energy and Flexible Reserve for Integrated Electric-Heat Systems

引用

IEEE ACCESS 2021年 9卷 14491-14503页

作者： Zhao, Wei Diao, Hanbin Li, Peiqiang Lv, Xiaoxiu Lei, Ertao Mao, Zhenyu Xue, Wenqi Guangdong Power Grid Corp Elect Power Res Inst Guangzhou 510000 Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 710000 Peoples R China

Implementing integrated electric-heat systems (IEHSs) with coupled power distribution networks and district heating networks is an essential means to solve current energy problems. However, prosumers with multiple energy forms coupled and renewable energy sources with natural uncertainties pose challenges to the operation of IEHSs. This paper proposes a joint energy and reserve dispatch model for IEHSs based on transactive energy, which is a coordinated combination of a bi-level Stackelberg game and two-stage robust optimization. The bi-level Stackelberg game is used to realize the equilibrium of interests among three transacting parties, namely, integrated energy service provider (IESP), multi-carrier prosumer (MCP), and load aggregator (LA). The two-stage robust optimization is employed to ensure the reliability of the system operation under renewable energy uncertainty. In the upper level of the Stackelberg game, the IESP perform pricing and reserve dispatch, while the MCP and LA maximize their benefits via energy management in the lower level. Linearization techniques are utilized to approximate the bi-level Stackelberg game model into a single-level mixed-integer linear programming problem. The converted single-level game model is subsequently regarded as the first stage, while the real-time feasibility check is regarded as the second stage to form a two-stage robust optimization model, which is solved by a modified C&CG algorithm. Case studies demonstrate that the proposed joint energy and reserve dispatch method effectively achieves economic and reliable operation.

关键词： Transactive energy Mathematical model Games optimization Resistance heating Companies Reliability Integrated electric-heat system transactive energy joint energy and reserve dispatch Stackelberg game two-stage robust optimization

来源：评论

学校读者我要写书评

暂无评论

two-stage robust optimal operation of AC/DC distribution networks with power electronic transformers

引用

FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Dong, Heling Tang, Zhong Wei, Minjie Shanghai Univ Elect Power Sch Elect Power Engn Shanghai Peoples R China

Power electronic transformers (PET) are a new type of power electronic equipment with a multi-port flexible dispatch function, which can play the role of a power hub in a system composed of multiple AC-DC hybrid distribution grids for interactive sharing of power in multiple regions. In this study, a two-stage robust optimization operation model of a hybrid AC-DC distribution network with PET is proposed based on PET power transmission and transformation characteristics. The stochastic uncertainty of the distributed renewable energy output in the AC-DC grid is handled by a two-stage robust optimization method to determine the minimum total system operation cost under the worst case of distributed renewable energy output. Finally, a constrained column generation algorithm is used to solve the two-stage robust optimization model in the min-max-min form and verifies the validity of the model in this study.

关键词： optimal dispatching power electronic transformer AC DC distribution network two-stage robust optimization renewable energy distributed generation

来源：评论

学校读者我要写书评

暂无评论

Extended exergy accounting theory to design waste-to-energy management system under uncertainty

引用

ENERGY 2023年第PartB期278卷

作者： Liu, Jianrui Kua, Harn Wei Wang, Chi-Hwa Tong, Yen Wah Zhang, Jingxin Peng, Yinghong Shanghai Jiao Tong Univ Sch Mech Engn Dept Mech Engn 800 Dongchuan Rd Shanghai 200240 Peoples R China Natl Univ Singapore Coll Design & Engn Dept Built Environm 4 Architecture Dr Singapore City 117566 Singapore Natl Univ Singapore Coll Design & Environm Dept Chem & Biomol Engn 4 Engn Dr Singapore City 117585 Singapore NUS Environm Res Inst E2S2 1 CREATE Way15-02 Singapore City 138602 Singapore Shanghai Jiao Tong Univ China UK Low Carbon Coll Shanghai 138602 Peoples R China

This paper seeks to study the waste-to-energy facility location planning problems under uncertainty from an integrated perspective. The extended exergy accounting method is first used to develop a multi-criteria decision analysis framework that unique in unifying multiple criteria of material, energy, social, economic and envi-ronmental aspects into homogeneous exergy terms, thus employing multiple criteria to obtain an integrated decision-making result. robust optimization and mixed-integer linear programming mathematical techniques are applied to formulate the problem as a two-stage robust waste-to-energy facilities location model based on this framework to minimize the exergy expenditure, and determine the technology type, location and capacity size of waste-to-energy fa-cilities over a large urban region. The uncertainty of municipal solid waste supply quantity in each waste gen-eration site is considered. The proposed model was demonstrated using a case study for household food waste treatment in Shanghai, and two treatment scenarios are proposed. Under the same uncertainty, the deployment strategy in scenario II feeds annual 2,655,140 GJ more equivalent primary exergy into the urban ecosystem than the scenario I, indicating that the only deployed on-site biogas plant to disposal household food waste performs better than the centralized incineration and on-site biogas plant combined deployment. A further sensitivity analysis reveals several valuable insights into municipal solid waste management. If the uncertainty is not considered, it may result in a municipal solid waste treatment capacity gap of up to 11.5% and a waste-to-energy system breakdown. Introducing the uncertain budget and range can help the decision-maker adjust the planning scheme flexibly, but the results become more conservative as their values increase. In this case study, it is optimal for decision makers to choose uncertain range mi = 12.5% and uncertain budget & UGamma;= 30.

关键词： Extended exergy accounting two-stage robust optimization Municipal solid waste management Facility location problem Waste to energy technology

来源：评论

学校读者我要写书评

暂无评论

A two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints

引用

FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Nan, Junpei Feng, Jieran Deng, Xu Guan, Li Sun, Ke Zhou, Hao Zhejiang Univ Coll Elect Engn Hangzhou Peoples R China South China Univ Technol Sch Elect Power Engn Guangzhou Peoples R China State Grid Corp China Natl Power Dispatching & Control Ctr Beijing Peoples R China State Grid Zhejiang Elect Power Co Ltd Hangzhou Peoples R China

After proposing the carbon peaking and carbon neutrality target, China further proposed a series of specific carbon emission growth limit sub-targets. How to decarbonize the energy system to ensure the realization of the carbon growth limit sub-targets is a meaningful topic. At present, generation expansion planning of renewable energy in integrated energy systems has been well studied. However, few of the existing studies consider specific carbon emission growth targets. To address this research gap, a two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints is proposed in this paper, which takes into account multiple uncertainties. In this framework, the objective function is to minimize the total operation cost and wind turbine investment cost. The first stage is the decision-making level of the wind turbine capacity configuration scheme. The second stage is the optimal economic dispatching in the worst-case scenario, which is a bi-level problem of max-min form. Thus, the two-stage robust optimization framework constitutes a problem of min-max-min form, which is pretty hard to solve directly with a commercial solver. Therefore, a nested column-and-constraint generation algorithm is adopted and nested iterations are performed to solve the complex problem. Finally, case studies are carried out on a regional electric-gas integrated energy system. The MATLAB/YALMIP simulation platform with the Gurobi solver is used to verify the effectiveness and superiority of the proposed framework. Compared with other four cases, 5,000 Monte Carlo scheduling tests demonstrate that the proposed framework can ensure the system carbon emission to be controlled within a certain limit even in the worst scenario. Due to the consideration of multiple uncertainties, the proposed framework planning results are both robust and economical for investment. This study can provide theoretical support for the actual regional in

关键词： carbon emission carbon growth constraints electric-gas integrated energy system generation expansion planning nested column-and-constraint generation algorithm two-stage robust optimization

来源：评论

学校读者我要写书评

暂无评论

Co-planning of hydrogen-based microgrids and fuel-cell bus operation centers under low-carbon and resilience considerations

引用

APPLIED ENERGY 2023年第1期336卷

作者： Dong, Yuchen Zheng, Weibo Cao, Xiaoyu Sun, Xunhang He, Zhengwen Xi An Jiao Tong Univ Sch Management Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Syst Engn Inst Sch Automat Sci & Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Minist Educ Key Lab Intelligent Networks & Network Secur Xian 710049 Shaanxi Peoples R China

The hydrogen-driven fuel-cell electric buses, which bear the advantages of emission free, high storage content and long mileage range, provide a promising choice for decarbonizing the public transportation system. Also, the operation centers for fuel-cell electric buses can be upgraded as the hydrogen-based microgrids to achieve higher economic benefits and resilience levels. To support the low-carbon and resilience-oriented planning of microgrid-aided bus centers, this paper presents a two-stage robust optimization formulation with integer corrective decisions. In particular, the first-stage problem is to optimize the microgrid siting decisions as well as the capacity configuration of renewable-powered electrolyzers, fuel-cell stacks and hydrogen refueling stations for maximizing the annualized benefits. Then, a min-max problem is introduced in the second-stage to improve the load survival value subject to the planning decisions and the worst-case contingency scenario. Also, various corrective actions, e.g., the emergency response of fuel-cell electric buses using vehicle-to-grid functionality, the energy scheduling of stationary equipment in hydrogen refueling stations and the adaptive network reconfiguration, are considered for resilience enhancement of the local power network. As the resulting robust optimization formulation is with a challenging mixed-integer recourse structure, the nested column -and-constraint generation algorithm is designed. Numerical results on exemplary power network and public transportation system validate the effectiveness of the proposed planning methodology, which has the potential to be profitable under normal operations while improving the load survivability under severe disastrous occasions. Moreover, our customized nested column-and-constraint generation shows a satisfactory solution performance, which facilitates prompt disaster relief actions of energy-transportation network.

关键词： Fuel-cell electric buses Hydrogen-based networked microgrids Low-carbon expansion planning Power network resilience two-stage robust optimization Nested column-and-constraint generation

来源：评论

学校读者我要写书评

暂无评论

Security-constrained robust dynamic power system planning with discrete recourse

引用

ELECTRIC POWER SYSTEMS RESEARCH 2023年第PartA期214卷

作者： Haghighat, Hossein Zeng, Bo Islamic Azad Univ Elect & Comp Engn Dept Jahrom Branch Jahrom Iran Univ Pittsburgh Dept Ind Engn Pittsburgh PA 15260 USA Univ Pittsburgh Dept Elect & Comp Engn Pittsburgh PA 15260 USA

In this study, we present a two-stage robust optimization model for dynamic generation and transmission expansion planning considering discrete recourse decisions and n - K security constraints. Unlike the mainstream literature, our approach exactly considers cost non-convexities, binary commitment decisions, and security constraints. By customizing a nested column-and-constraint generation procedure, we compute this complex problem accurately. On two test systems, we illustrate the efficacy of the method and the impacts of security constraints, and the discreteness of recourse decisions on grid expansions.

关键词： two-stage robust optimization Security-constrained power system expansion planning Nested column-and-constraint generation algorithm Uncertainty Discrete recourse

来源：评论

学校读者我要写书评

暂无评论

Collaborative distribution network design with surging demand and facility disruptions

引用

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2023年第1期262卷

作者： Alikhani, Reza Eskandarpour, Majid Jahani, Hamed Montpellier Business Sch Montpellier France Univ Lille IESEG Sch Management CNRS UMR 9221LEM Lille Econ Management F-59000 Lille France RMIT Univ Sch Accounting Informat Syst & Supply Chain Melbourne Australia

In this paper, we study a new approach to horizontal collaboration, the so-called coalition configuration among partnering companies through sharing distribution centers in a network design problem. Horizontal collaboration is established by making joint decisions and sharing resources among various parties at the same level of the supply chain which improves operational efficiency and competitiveness. In particular, the question we address is which coalition should be formed in each distribution center while the objective function seeks to minimize the total cost in the network. Beyond that, potential uncertainties, i.e., operational and disruption risks, are considered in the collaborative design phase. Thus, this paper studies a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions. A tailored column-and-constraint generation algorithm is utilized to solve the proposed robust model. Extensive numerical experiments have been conducted to analyze solutions obtained by the model in various situations, e.g., when the grand coalition forms, for decisions ranging from fully centralized to fully decentralized settings, for collaborative approaches versus non-collaborative approaches, and under different amounts of uncertainty budgets. The results demonstrate that the coalition formation mechanism proposes some competitive solutions with savings of the grand coalition. We also find that not only does collaboration always increase the flexibility and resilience of the network but also in collaborative approaches, the average price of robustness is comparatively lower than that of non-collaborative approaches.

关键词： Warehouse sharing Collaboration for resilience robust facility location Overlapping coalitions formation two-stage robust optimization Column-and-constraint-generation algorithm

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：