检索结果-内蒙古大学图书馆

bi-level optimization model of hydrogen-blended gas units and multi-type energy storage system considering low-carbon operation

引用

ENERGY 2025年 314卷

作者： Li, Jinhang Chen, Heng Li, Jingjia Zhang, Yixi Pan, Peiyuan bian, Jiayu Yu, Zhiyong North China Elect Power Univ Beijing 102206 Peoples R China State Grid Xinjiang Elect Urumqi 830000 Peoples R China

With the integrated energy system as the future roadmap, harnessing multiple energy storage technologies and hydrogen energy collaboratively is pivotal for achieving cleanliness and decarbonization in the energy sector. This paper proposes a bi-level economic optimization model that considers the collaborative low-carbon approach of natural gas blending with hydrogen and multi-type energy storage. It leverages the flexible interaction and operation of electricity, thermal, and hydrogen energy storage in the integrated energy system to achieve optimal collaboration and complementarity among multiple energy sources. At the same time, a natural gas blending with hydrogen model is adopted to provide multiple pathways for the utilization of hydrogen energy in the integrated energy system. In the bi-level optimization model, the upper-level model achieves optimal capacity planning and economic benefits for the multi-type energy storage system. In contrast, the lowerlevel model achieves the overall optimal low-carbon operation of the integrated energy system.

关键词： bi-level optimization model Multi-type energy storage Hydrogen blending in natural gas Low-carbon economy

来源：评论

学校读者我要写书评

暂无评论

bi-level optimization model of integrated biogas energy system considering the thermal comfort of heat customers and the price fluctuation of natural gas

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期151卷

作者： Qin, Minglei Yang, Yongbiao Chen, Sijie Xu, Qingshan Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China Nanjing Ctr Appl Math Nanjing 211135 Peoples R China

biogas is a pervade renewable energy source in rural areas, which can be used to generate power, heating and gas to satisfy the multi-energy needs of users. However, the energy efficiency and thermal comfort of heat customers after the connection of biogas digester is a challenging modelling problem. This paper establishes a bi-level optimization model of integrated biogas energy system considering the thermal comfort of heat customers and the price fluctuation of natural gas. In detail, using the penalty factor to describe the thermal comfort and using the DBN (Dynamic Bayesian network) model to predict natural gas fluctuations. The upper optimization target is the largest profit of the energy agency, and the lower objective is the minimum heating cost considering the penalty factor. The uncertainty of weights and biases in DBN prediction is addressed using the Sparrow search algorithm, and the uncertainty in probability results is tackled using an improved Latin hypercube sampling method. The optimization results show the proposed bi-level model can greatly increase the profit of energy agency by 18.5%, and the DBN prediction model has 89.3% prediction accuracy. Furthermore, the influence of diverse biogas scales and operation modes of the system, fluctuated natural gas price effects and various penalty factors of the user economy and comfort during heating are also analyzed.

关键词： bi-level optimization model biogas digester Natural gas price DBN model Thermal comfort

来源：评论

学校读者我要写书评

暂无评论

A resource bi-level optimization model of water-energy-food-carbon nexus in a regional agricultural system under multi-stakeholder conditions

引用

RENEWABLE ENERGY 2025年 241卷

作者： Feng, Tingting Liu, bin Ren, Hourui Zhu, Yide Zhang, Yue Luo, Xiangyi Zhou, Zhongli Chengdu Univ Technol Coll Management Sci Chengdu 610059 Peoples R China Chengdu Univ Technol Geomath Key Lab Chengdu 610059 Sichuan Peoples R China Chengdu Univ Technol Sch Math Sci Chengdu 610059 Peoples R China Xi An Jiao Tong Univ Sch Future Technol Xian 710049 Peoples R China Qingdao Univ Technol Coll Management Engn Qingdao 266520 Peoples R China

The conflict between low-carbon development, energy security, and resource shortages presents significant challenges to agricultural advancement. Thus, the aim of this study is to achieve the sustainable management of agricultural resources. To this end, a bi-level optimization model for agricultural resources is developed. This model examines the interrelation among water-energy-food-carbon, assesses the efficiency of bioenergy production within regional agricultural systems, and facilitates the balancing of objectives among different stakeholders. Key decision variables include water resource allocation, crop planting areas, and livestock populations. At the upper decision-making level, the model seeks to maximize agriculture economic benefits, reduce carbon emissions, improve bioenergy production efficiency, and minimize land resource inequality. At the lower decision-making level, it prioritizes economic benefits and yield of agricultural products. To solve the model, an integrated approach combining weighted bias and fuzzy methods was utilized. To validate the model's applicability, a case study was conducted in Sichuan Province. The results demonstrated that, after optimization, agricultural water resource allocation reached 168.56 x 108 m3. Planting areas for vegetables, rice, and tubers decreased by 0.78 %, 5.46 %, and 1.54 %, respectively, while livestock populations for pigs, cattle, and sheep declined by 29.91 %, 11.75 %, and 7.46 %. The regional average bioenergy production efficiency was 12218.08 KJ/MJ. Notably, the indirect carbon emissions caused by CH4 emissions accounted for 50.51 % of total emissions. The proposed model outperformed alternative approaches, effectively balancing multi-level objectives and providing a robust framework for optimizing agricultural resource management while addressing stakeholder conflicts.

关键词： Water-energy-food-carbon Multi-stakeholder Carbon emissions bioenergy bi-level optimization model

来源：评论

学校读者我要写书评

暂无评论

bi-level optimization model applications in managing air emissions from ships:A review

引用

Communications in Transportation Research 2021年第1期1卷 171-175页

作者： Jingwen Qi Shuaian Wang Harilaos Psaraftis Department of Logistics&Maritime Studies The Hong Kong Polytechnic UniversityHung HomHong Kong SARChina Department of Technology Management and EconomicsTechnical University of DenmarkDenmark

Ship air emissions are recognized as one of the key concerns of the maritime *** authorities have issued various regulations to manage air emissions from *** the authorities are policy makers,the effectiveness of policies is up to the shipping industry who operates the vessels and terminals to fulfill maritime transportation *** this characteristic,bi-level optimization model has been widely adopted in studies that optimize policy design or evaluate its *** framework of a typical bi-level optimization model for ship emission management problem is given to show the basic structure of similar issues.A series of applications of bi-level optimization model in managing ship emissions is reviewed,including cases of Energy Efficiency Design Index,Emissions Control Area,Market Based Measure,Carbon Intensity Indicator,and Vessel Speed Reduction Incentive *** hope this paper can enlighten scholars interested in this area and provide help for them.

关键词： bi-level optimization model Ship air emissions Fleet deployment Ship operation

来源：评论

学校读者我要写书评

暂无评论

Application of a bi-level optimization model for Energy Storage Capacity Allocation in Distribution Network with Renewable Energy Integration 2nd

Application of a Bi-level Optimization Model for Energy Stor...

引用

2nd International Conference on Smart Electrical Grid and Renewable Energy, SEGRE 2024

作者： Feng, Bo Shen, Hongtao Zhang, Yangrui Ma, Hao Li, Ji Yu, Minqi Marketing Service Center State Grid Hebei Electric Power Co. Ltd. Shijiazhuang050000 China State Grid Hunan Electric Power Co. Ltd. Changsha410000 China

ISBN: (纸本)9789819619641

With the integration of renewable energy into the distribution network, the uncertainty of their output significantly increases network losses, negatively affecting the economic performance and stability of the distribution network. To address this critical issue, this paper proposes the introduction of an energy storage system (ESS) into the distribution network and the construction of a bi-level optimization model for ESS capacity allocation. The bi-level optimization model comprises two layers: the planning layer and the operational layer. The planning layer takes into account both the investment and operational costs of the ESS to optimize capacity allocation, ensuring cost-effectiveness. Meanwhile, the operational layer focuses on the daily operational scheduling of the ESS with the primary goal of minimizing the daily operational costs of the distribution network. To validate the effectiveness of the proposed model, extensive simulations are conducted using the IEEE 33-bus distribution system. The simulation results clearly demonstrate that the proposed model significantly reduces network losses, smooths voltage fluctuations, and enhances the economic operation of the distribution network, confirming its practical applicability and efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： bi-level optimization model Energy Storage System Network Losses Renewable Energy

来源：评论

学校读者我要写书评

暂无评论

A bi-level optimization model for Independent System Operator Considering Price-Based Demand Response

A Bi-Level Optimization Model for Independent System Operato...

引用

58th IEEE/IAS Industrial and Commercial Power Systems Technical Conference Asia (IEEE I and CPS Asia)

作者： Si, Juncheng Bao, Guannan Liu, Hanghang Sun, Mingyu Zhou, Lei Tan, Mingcong Wang, Lingling Jiang, Chuanwen Dongying Power Supply Co Dongying Shandong Peoples R China Smart Grid Shandong Elect Power Co Jinan Shandong Peoples R China Shanghai Jiao Tong Univ Key Lab Control Power Transmiss & Convers Shanghai Peoples R China

ISBN: (数字)9781665450669

ISBN: (纸本)9781665450669

The participation of demand response in the regulation of the power system is an effective supplement to the regulation on the generation side. In order to fully tap the loadside demand response potential and maximize the benefits of the power system and the load, this paper designs a bi-level optimization model that considers the interaction between the independent system operator and the price-based demand response load. Taking the minimum operator's comprehensive cost and the maximum load response benefit as the objectives of the upper and lower levels of the model respectively, the constructed bi-level optimization problem is transformed into an easy-to-solve linear programming problem through the KKT condition and the big M method. The results of the calculation example show that the price-based demand response load can adjust its own electricity consumption according to the change of the real-time electricity price. After the system operator adjusts the electricity price for optimal scheduling, both the operator and the response load can realize cost savings.

关键词： demand response real-time electricity price bi-level optimization model price-based demand response load

来源：评论

学校读者我要写书评

暂无评论

bi-level optimization model of Boundary Signal Control for the Network Based on Macroscopic Fundamental Diagrams

引用

INTERNATIONAL JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS RESEARCH 2020年第1期18卷 113-121页

作者： Yan, Xiaowen Xu, Jianmin Ma, Yingying Zhejiang Inst Mech & Elect Engn Dept Transportat Technol Hangzhou 310053 Zhejiang Peoples R China South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510640 Guangdong Peoples R China

This paper proposes a bi-level optimization model about boundary signal control for the network using macroscopic fundamental diagrams. Firstly, the road network is simplified as a directed graph, in which vertices and arcs respectively correspond to traffic zones and road segments connecting zones. Then a bi-level optimization model is proposed and the control objective is maximizing total output vehicles as well as keeping the existing number of vehicles optimal for each zone. The upper layer model optimizes transfer traffic flow among zones and the lower layer model optimizes the signal control scheme about boundary intersections. And a hybrid genetic simulated annealing algorithm is devised to solve the model. Finally, micro-simulation is used to test and verify the validity of proposed model. The results show that when the network congestion occurs, especially when traffic congestion is not uniform, the proposed model can improve the output vehicles for the whole network. Simultaneously, the existing number of vehicles in each zone can maintain at nearly optimal level. Thus verifying the effectiveness and feasibility of the boundary signal control model.

关键词： Macroscopic fundamental diagram bi-level optimization model Hybrid genetic simulated annealing algorithm Microscopic simulation

来源：评论

学校读者我要写书评

暂无评论

Estimating the geographic distribution of originating air travel demand using a bi-level optimization model

引用

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2019年 131卷 267-291页

作者： Li, Tao Wan, Yan North Carolina State Univ Inst Transportat Res & Educ Raleigh NC 27606 USA Univ Texas Arlington Dept Elect Engn Arlington TX 76019 USA 416 Yates St Nedderman Hall Arlington TX 76019 USA

The historical air travel demand plays an important role in the analysis of, for example, major changes in airport use, airport and airline marketing, and airport planning. We provide a bi-level optimization model as a relatively quick and less expensive alternative to survey method to estimate the originating air travel demand and its geographic distribution at an airport. The lower-level model estimates the geographic distribution of originating air travel demand and model coefficients. The upper-level model estimates the airport access distance threshold which is used to model traveler's airport choice behaviors in the lower-level model. We adopt an Evolutionary Algorithm (EA) to solve the bi-level optimization model. A General Reduced Gradient solution algorithm is used within the EA to solve the lower-level model. We present a real-world case study in which we apply the model to estimate the originating air travel demand and its geographic distribution on the contiguous United States. The model estimates are generally close to the statistics from the American Travel Survey. The comparisons of the model estimates with the statistics from the Washington-Baltimore regional air passenger survey show mixed results. Possible reasons for the estimation errors are identified.

关键词： Geographic distribution of originating air travel demand bi-level optimization model Demand estimation Path flow estimator

来源：评论

学校读者我要写书评

暂无评论

bi-level optimization model for integrated energy system considering the thermal comfort of heat customers

引用

APPLIED ENERGY 2018年 232卷 607-616页

作者： Wu, Chenyu Gu, Wei Xu, Yinliang Jiang, Ping Lu, Shuai Zhao, Bo Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China Tsinghua Berkeley Shenzhen Inst Shenzhen Environm Sci & New Energy Technol Engn L Shenzhen 518055 Peoples R China Zhejiang Elect Power Corp Res Inst Hangzhou 310014 Zhejiang Peoples R China

Significant growth in gas-fired combined heat and power units worldwide has enhanced the degree of interdependency between power, natural gas and district heating systems. This study establishes a bi-level optimization model for integrated energy systems that handles the interaction between centralized energy generation and the heating costs of end users in winter. The upper level of the model is designed to maximize the total benefit of the integrated energy system, and the lower level is designed to minimize the heating bills of residents. The lower level considers the thermal inertia of the building and the thermal comfort of the inhabitants. The indoor temperature demand is converted to a heat demand within a feasible interval. The nonlinear bi-level model is transformed into a mixed-integer linear programming formulation using the Karush-Kuhn-Tucker optimality condition. The optimal results of the traditional and proposed models are compared in case studies. The impacts of three representative auxiliary equipments (power to gas, electric boiler and gas tank) on wind power integration or gas generation cost are also investigated.

关键词： bi-level optimization model Combined heat and power Integrated energy system Thermal comfort

来源：评论

学校读者我要写书评

暂无评论

Management and performance evaluation of DSR aggregator based on a bi-level optimization model

引用

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2018年第3期13卷 432-441页

作者： Li, Bosong Jiang, Chuanwen Zhang, Gao He, Yang Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China State Grid Henan Elect Power Co Zhengzhou 450000 Henan Peoples R China

The vast potential of demand-side resources (DSR)including flexible loads and distributed energy resourcesin the optimal operation of a power system is being increasingly recognized. Such potential can be fully realized through the access of a DSR aggregator to the power market. In this paper, a DSR aggregator is introduced for the collective management of DSRs in the power system. A bi-level optimization model consisting of power market clearing and DSR aggregator internal scheduling is formulated and solved through stochastic programing. A thorough evaluation of the DSR aggregator's performance under three different operation modes, namely energy consumer mode, energy prosumer mode, and eco-friendliness mode, is carried out to study its influence on system operation concerning social welfare, system purchase cost, carbon emission, and so on. Simulation results show that even though DSR acquires a segment of the market social welfare, it brings in benefits in economic and environmental operation of the system and contributes to DSR uncertainty alleviation. (c) 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

关键词： demand-side resource power market DSR aggregator bi-level optimization model stochastic programing performance evaluation

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：