检索结果-内蒙古大学图书馆

Risk-averse decision-making to maintain supply chain viability under propagated disruptions

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2024年第8期62卷 2853-2867页

作者： Sawik, Tadeusz Sawik, Bartosz Reykjavik Univ Dept Engn Reykjavik Iceland AGH Univ Sci &Technol Dept Operat Res Krakow Poland AGH Univ Sci & Technol Dept Business Informat & Engn Management Krakow Poland Univ Publ Navarra Dept Stat Comp Sci & Math Pamplona Spain Univ Calif Berkeley Haas Sch Business Berkeley CA USA Reykjavik Univ Dept Engn IS-101 Reykjavik Iceland AGH Univ Sci & Technol Dept Operat Res PL-30059 Krakow Poland

In this paper, stochastic optimisation of CVaR is applied to maintain risk-averse viability and improve resilience of a supply chain under propagated disruptions. In order to establish the risk-averse boundaries on supply chain viability space, two stochastic optimisation models are developed with the two conflicting objectives: minimisation of Conditional Cost-at-Risk and maximisation of Conditional Service-at-Risk. Then, the risk-averse viable production trajectory between the two boundaries is selected using a stochastic mixed integer quadratic programming model. The proposed approach is applied to maintain the supply chain viability in the smartphone manufacturing and the results of computational experiments are provided. The findings indicate that when the decision-making is more risk-aversive, the size of the viability space between the two boundaries is greater. As a result, more room is available for selecting viable production trajectories under severe disruptions. Moreover, the larger is viability space, the higher is both worst-case and average resilience of the supply chain. Risk-neutral, single-objective decision-making may reduce the supply chain viability. A single-objective supply chain optimisation which moves production to the corresponding boundary of the viability space, should not be applied under severe disruption risks to avoid greater losses.

关键词： Supply chain disruption management supply chain viability supply chain resilience stochastic mixed integer linear programming stochastic mixed integer quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Optimal Bidding Strategy for a DER Aggregator in the Day-Ahead Market in the Presence of Demand Flexibility

引用

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第2期66卷 1509-1519页

作者： Di Somma, Marialaura Graditi, Giorgio Siano, Pierluigi ENEA Agenzia Nazl Nuove Tecnol Energia & Sviluppo Dept Energy Technol I-80055 Portici Italy Univ Salerno Dept Ind Engn I-84084 Fisciano Italy

The penetration of distributed energy resources (DER), including distributed generators, storage devices, and demand response (DR) is growing worldwide, encouraged by environmental policies and decreasing costs. To enable DER local integration, new energy players as aggregators appeared in the electricity markets. This player, acting toward the grid as one entity, can offer new services to the electricity market and the system operator by aggregating flexible DER involving both DR and generation resources. In this paper, an optimization model is provided for participation of a DER aggregator in the day-ahead market in the presence of demand flexibility. This player behaves as an energy aggregator, which manages energy and financial interactions between the market and DER organized in local energy systems (LES), which are in charge to satisfy the multienergy demand of a set of building clusters with flexible demand. A stochastic mixed-integer linear programming problem is formulated by considering uncertainties of intermittent DER facilities and day-ahead market price, to find the optimal bidding strategies while maximizing the expected aggregator's profit. Numerical results show that the method is efficient in finding the bidding curves in the day-ahead market through the optimal management of flexibility requests sent to clusters, as well as of DER in LES and interactions among LES.

关键词： Aggregator distributed energy resources (DER) market bidding strategy stochastic mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Strategic Generation Bidding and Scheduling under Price Uncertainty

引用

IEEE LATIN AMERICA TRANSACTIONS 2018年第5期16卷 1445-1453页

作者： Nunez, Ana C. Gutierrez, G. Gil, Esteban Ctr Nacl Control Energia Mexicali 21350 Baja California Mexico Inst Tecnol Morelia Programa Grad & Invest Ingn Elect Morelia Michoacan Mexico Univ Tecn Federico Santa Maria Dept Ingn Elect Valparaiso Chile

Market deregulation, emergence of new technologies, and the rising penetration of variable renewable generators are increasing electricity price variability and the risk faced by generation portfolios in spot markets. In this paper, we propose a method to suggest bidding strategies for price-taking generators in a day-ahead market under price uncertainty. Electricity price scenarios are generated through a seasonal ARIMA model and grouped into clusters using the Partitioning Around Medoids algorithm (PAM) to obtain representative price scenarios. Expected profits under price uncertainty are maximized using a stochastic mixed integer linear programming (SMILP) formulation that considers the operational restrictions of the thermal units. The problem is solved in XPRESS-Mosel. The results show that explicitly modeling price variability in the optimization can increase the benefits seen by a price-taking generation portfolio by up to 1.4% with respect to a deterministic approach.

关键词： stochastic optimization stochastic mixed integer linear programming strategic bidding

来源：评论

学校读者我要写书评

暂无评论

Reliability enhancement of distribution networks using ESSs ancillary services: A probabilistic MILP methodology

引用

ELECTRIC POWER SYSTEMS RESEARCH 2019年 175卷 105889-000页

作者： Sun, Lingjie Fahim, Fadia Taizhou Vocat & Tech Coll Zhejiang 318000 Taizhou Peoples R China Northeastern Univ Boston MA 02115 USA

This paper proposes a stochastic mixed integer linear programming (MILP) approach aiming at improvement of the reliability level of electric distribution network through a contingency-based energy storage systems (ESSs) incorporation, considering ESSs ancillary services and control sequences in service restoration. Further, charging stations installed in each ESSs are supposed to be purchased from various ESSs service providers with different charging/discharging rates. The proposed fitness function aims to simultaneously minimize the expected total cost of reliability (ETRC) and the expected system average interruption duration index (ESAIDI), to deal with economic and technical reliability aspects, respectively. The ETRC includes total cost of interruption and the total ESSs incorporation cost. In addition, the uncertainties in the restoration process in presence of the ESSs, including distribution system conditions and the available power of the cooperated ESSs during service restoration process are considered by several prospective scenarios. The effectiveness of the proposed methodology is investigated using a standard reliability test system (RBTS-4). The convergence of the proposed MILP approach is compared to the other methodologies presented in recent studies that proves the higher tractability of the proposed approach.

关键词： Energy storage systems Power system reliability Service restoration stochastic mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

stochastic optimization of hybrid electricity supply chain considering carbon emission schemes

引用

SUSTAINABLE PRODUCTION AND CONSUMPTION 2018年 14卷 136-151页

作者： Gonela, Vinay Texas A&M Univ Cent Texas Coll Business Adm Dept Management & Mkt 1001 Leadership Pl Killeen TX 76549 USA

This paper focuses on designing an optimal hybrid electricity supply chain (HESC) that considers carbon emission schemes and uncertainties. Both coal and biomass are used as fuel for electricity generation. Several carbon emission schemes, such as carbon cap and trade, carbon cap, and carbon tax, are considered. In addition, uncertainties such as coal mining rate, biomass yield rate, and electricity conversion rate are considered while designing HESC. A stochastic mixed integer linear programming (SMILP) model is developed that aims to determine optimal HESC under carbon emission schemes and uncertainties. A case study of North Dakota (ND) in the United States (US) is used to demonstrate the effectiveness of the proposed model. The results suggest that carbon emission schemes significantly impact the HESC design. Sensitivity analysis is further conducted to provide managerial insights. (C) 2018 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Electricity supply chain Renewable energy stochastic mixed integer linear programming Sustainability Carbon emission schemes

来源：评论

学校读者我要写书评

暂无评论

Role of Distributed Energy Storage Systems in the Quest for Carbon-free Electric Distribution Systems

Role of Distributed Energy Storage Systems in the Quest for ...

引用

IEEE International Conference on Environment and Electrical Engineering (EEEIC) / IEEE Industrial and Commercial Power Systems Europe (ICPS Europe)

作者： Fitiwi, Desta Z. Santos, Sergio F. Catalao, Joao P. S. Econ & Social Res Inst Dublin Ireland C MAST UBI Covilha Portugal INESC TEC Porto Portugal FEUP Porto Portugal IST UL INESC ID Lisbon Portugal

ISBN: (纸本)9781538651865

This paper presents an extensive analysis in relation to transforming electric distribution networks in order to accommodate large quantities of variable renewable energy sources (vRESs). For this purpose, a multi-stage and stochastic mixed integer linear programming (S-MILP) model is employed. The algebraic model developed optimally allocates energy storage systems (ESSs) along with an optimal dynamic distribution network switching. For the analysis, a standard IEEE 119-bus distribution network system was used as a case study. Test results reveal that the joint optimization of ESSs and network reconfiguration markedly increase flexibility in existing systems, leading to an increase in the levels of renewables integration and utilization. Moreover, the analysis of the results shows the prospect of such systems in going fully "carbonfree", i.e. with vRES power entirely meeting system demand. Generally, the current work demonstrates that a more effective integration and utilization of large-scale vRESs is possible when existing systems are equipped with enabling technologies that are already commercially available.

关键词： Distributed generation energy storage systems network switching renewable energy sources stochastic mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Implementing Dynamic Network Reconfiguration with Renewables and Considering Future Grid Technologies: A Real Case Study

Implementing Dynamic Network Reconfiguration with Renewables...

引用

IEEE International Conference on Environment and Electrical Engineering (EEEIC) / IEEE Industrial and Commercial Power Systems Europe (ICPS Europe)

作者： Pogeira, Jose Santos, Sergio F. Fitiwi, Desta Z. Cruz, Marco R. M. Catalao, Joao P. S. FEUP Porto Portugal C MAST UBI Covilha Portugal ESRI Dublin Ireland INESC TEC Porto Portugal IST UL INESC ID Lisbon Portugal

ISBN: (纸本)9781538651865

Dynamic distribution system reconfiguration (DDSR) is the process of dynamically changing the network's topology during the operational periods of the system. This process together with the integration of distributed renewable energy sources (DRES) and other enabling technologies allow a more efficient operation of such systems in technical and economic terms, facilitating a seamless integration of DRES in larger quantities. When performing such an optimization process, the stochastic nature of DRES (both variability and uncertainty) needs to be taken into consideration. In this paper, an improved dynamic system reconfiguration model is presented where the goal is to minimize the total cost in the system while satisfying various technical constraints so as to maintain the reliability and stability of the system at required levels. The computational tool is tested in a real system encompassing the distribution system of Lagoa (in Sao Miguel Island, Azores), and its effectiveness is properly validated. The numerical results demonstrate great benefits in economic terms, such as reduced losses and improved system reliability.

关键词： Distributed generation dynamic reconfiguration renewable energy sources energy storage systems stochastic mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

引用

APPLIED ENERGY 2017年第Part1期185卷 44-55页

作者： Santos, Sergio F. Fitiwi, Desta Z. Cruz, Marco R. M. Cabrita, Carlos M. P. Catalao, Joao P. S. Univ Beira Interior C MAST P-6201001 R Fonte Do Lameiro Covilha Portugal Comillas Pontifical Univ Calle Alberto Aguilera 23 Madrid 28015 Spain Univ Porto INESC TEC P-4200465 Oporto Portugal Univ Porto Fac Engn P-4200465 Oporto Portugal Univ Beira Interior CISE P-6201001 R Fonte Do Lameiro Covilha Portugal Univ Lisbon Inst Super Tecn INESC ID Av Rovisco Pais 1 P-1049001 Lisbon Portugal

Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network's switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not significant. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Energy storage Distributed generation Network reinforcement Network switching Renewable energy sources stochastic mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Dynamic Reconfiguration of Distribution Network Systems: A Key Flexibility Option for RES Integration 17

Dynamic Reconfiguration of Distribution Network Systems: A K...

引用

17th IEEE International Conference on Environment and Electrical Engineering (IEEE EEEIC) / 1st IEEE Industrial and Commercial Power Systems Europe Conference (IEEE I and CPS Europe)

作者： Dantas, F. V. Fitiwi, D. Z. Santos, S. F. Catalao, J. P. S. INESC TEC Porto Portugal FEUP Porto Portugal C MAST UBI Covilha Portugal INESC ID IST UL Lisbon Portugal

ISBN: (纸本)9781538639177

The growing trend of variable energy source integration in power systems (especially at a distribution level) is leading to an increased need for flexibility in all levels of the energy flows in such systems: the supply, the network and the demand sides. This paper focuses on a viable flexibility option that can be provided by means of a dynamic network reconfiguration (DNR), an automatic changing of line statuses in response to operational conditions in the system. The ultimate aim is to assess the impacts of such flexibility on the utilization levels of variable power sources (mainly, solar and wind) integrated at a distribution level. To perform this analysis, a stochastic mixed integer linear programming (S-MILP) operational model is developed in this work. The objective of the optimization problem is to minimize the sum of the most relevant cost terms while meeting a number of model constraints. The proposed model dynamically finds an optimal configuration of an existing network system in accordance with the system's operational conditions. The operation scale in the current work is one day, but with the possibility of an hourly reconfiguration. The standard IEEE 41-bus system is employed to test the proposed model and perform the analysis. Numerical results generally show that DNR leads to a more efficient utilization of renewable type DGs integrated in the system, reduced costs and losses, and a substantially improved system performance especially the voltage profile in the system.

关键词： Distributed generation network reconfiguration renewable energy sources stochastic mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Planning of Power Distribution Systems with High Penetration of Renewable Energy Sources Using stochastic Optimization

Planning of Power Distribution Systems with High Penetration...

引用

作者： Sergio da Fonseca Santos UNIVERSIDADE DA BEIRA INTERIOR

学位级别：博士

Driven by techno-economic and environmental factors, there is a global drive to integrate more distributed energy resources in power systems, particularly at the distribution level. These typically include smart-grid enabling technologies, such as distributed generation (DG), energy storage systems and demand-side management. Especially, the scale of DG sources (mainly renewables) integrated in many distribution networks is steadily increasing. This trend is more likely to continue in the years to come due to the advent of emerging solutions, which are expected to alleviate existing technical limitations and facilitate smooth integration of DGs. The favorable agreements of countries to limit greenhouse gas (GHG) emissions and mitigate climate change are also expected to accelerate the integration of renewable energy sources (RESs). However, the intermittent and volatile nature of most of these RESs (particularly, wind and solar) makes their integration in distribution networks a more challenging task. This is because such resources introduce significant operational variability and uncertainty to the system. Hence, the development of novel methodologies and innovative computational tools is crucial to realize an optimal and cost-efficient integration of such DGs, minimizing also their side effects. Novel methodologies and innovative computational tools are developed in this thesis that take into account the operational variability and uncertainty associated with the RES power generation, along with the integration of smart-grid enabling technologies. The developed methodologies and computational tools are tested in real-life power systems, as well as in standard test systems, demonstrating their computational proficiency when compared with the current state-of-the-art. Due to the inherent uncertainty and variability of RESs, stochastic programming is used in this thesis. Moreover, to ensure convergence and to use efficient off-the-shelf solvers, the problems addresse

关键词： Distributed Generation (DG) Energy Storage Systems (ESSs) Investment planning Network reinforcement Renewable Energy Sources (RES) Smart grids stochastic mixed integer linear programming Variability and uncertainty

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：