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bilevel programming model for Park-and-Ride Versus Transit-Oriented Development: A Case Study of Chengdu City, China

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JOURNAL OF URBAN PLANNING AND DEVELOPMENT 2022年第1期148卷 05021056-05021056页

作者： Li, Jinlong Luo, Xia Wang, Hongjie Qiu, Yuansen Fan, Wenbo Southwest Jiaotong Univ Sch Transportat & Logist Natl United Engn Lab Integrated & Intelligent Tra Key Lab Big Data Applicat Technol Comprehens Tran 999 Xian Rd Chengdu 611756 Peoples R China Southwest Jiaotong Univ Sch Transportat & Logist 999 Xian Rd Chengdu 611756 Peoples R China

Park-and-ride (P&R) and transit-oriented development (TOD) are two major strategies to leverage the high capacity of rail transit systems in urban areas. Both rooted in the station-area land, the two strategies must be reconciled in an integrated planning framework. To this end, a bilevel programming model is proposed to tackle the competitive location issue of P&R and TOD near rail transit stations: the upper level is a 0-1 programming model, simulating governmental land-use decision-making behavior with the objective of maximizing metro patronage and minimizing vehicle kilometers traveled, or minimizing vehicle hours of delay;and the lower level is the multimodal network equilibrium model, simulating travelers' responses and assigning traffic and passenger flows in the network. The traffic analysis zones containing rail stations are divided into transit station areas and auto-oriented zones. The household residential relocation model, accessibility quantitative model, and generation-distribution joint model are used to describe the complex interactions between transit system and land-use development near rail stations. A hypothetical scenario is designed to quantitatively analyze the impacts of different station-based land-use decisions and parameters of population and employment densities. A real case study is presented to illustrate the implementation of the proposed model.

关键词： Station-area land use Park-and-ride Transit-oriented development bilevel programming model Location problem

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Integrating Equality and Stability to Resolve Water Allocation Issues with a Multiobjective bilevel programming model

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2016年第7期142卷 4016013.1-4016013.1页

作者： Hu, Zhineng Wei, Changting Yao, Liming Li, Chaozhi Zeng, Ziqiang Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Sichuan Peoples R China Sichuan Univ State Key Lab Hydraul & Mt River Engn Chengdu 610064 Sichuan Peoples R China Neijiang Survey & Design Inst Water Conservancy & Neijiang 641000 Peoples R China

With rapid economic and social development, increasing water demands have made water scarcity a worldwide issue. Equitable, stable, and efficient water allocation, which includes water resources management and conflicting water demand management, needs a valid resolution. This paper develops a multiobjective bilevel model with the upper level reflecting the river basin authority's allocation principle of equity and stability and the lower level aimed at ensuring maximal economic benefit effiency for each subarea. The Gini coefficient is introduced to seek equity in the water allocation strategies, a power index is applied to ensure stability in the water allocation solutions, and an economic efficiency function is designed to maximize the economic benefit efficiency in each subarea. The proposed multiobjective bilevel water allocation model is then applied to a case study in Qujiang River Basin in China, and demonstrates that the proposed model provides reasonable and practical water allocation strategies for river basin authorities.

关键词： Water allocation Gini coefficient Equality Power index Stability bilevel programming model

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Connected eco-driving for electric buses along signalized arterials with bus stops

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IET INTELLIGENT TRANSPORT SYSTEMS 2023年第3期17卷 575-587页

作者： Shan, Xiaonian Wan, Changxin Hao, Peng Wu, Guoyuan Zhang, Xiang Hohai Univ Coll Civil & Transportat Engn 1 Xikang Rd Nanjing Peoples R China Univ Calif Riverside Ctr Environm Res & Technol Riverside CA 92521 USA Dalian Maritime Univ Coll Transportat Engn Dalian Peoples R China

With the rapid development of the cooperative vehicle infrastructure system, eco-approach and departure has been attracting increasing attention for mitigating the impact of signalized intersections, which helps improve the energy efficiency of equipped vehicles. However, existing studies have rarely considered the balance of electric bus energy consumption and traveling time. Meanwhile, the joint effect of bus stops and signalized intersections, and their interactions were not discussed widely with connected and automated electric buses (CAEBs). In this study, an integrated CAEB trajectory planning methodology with the balance of traveling time and energy consumption is proposed. A bi-level programming model is developed to obtain the optimal trajectories of CAEBs. Numerical experiments are conducted to analyse and compare the model with two baseline models. The results demonstrate the optimal performance of the derived scheme in terms of bus energy consumption, with approximately 30-50% energy savings. Furthermore, model sensitivity analysis is conducted to quantify the impacts of the related system parameters. The findings also reveal that the entry time, conversion coefficient, and final speed have significant impacts on electric bus energy consumption along signalized arterials with bus stops.

关键词： energy conservation trajectory control electric bus energy consumption battery powered vehicles signalized arterials Optimisation techniques Spatial variables control eco-approach connected eco-driving bus stops Automobile electronics and electrics bilevel programming model equipped vehicles sensitivity analysis road traffic control vehicle infrastructure system energy efficiency energy consumption Road-traffic system control signalized intersections energy savings Control system analysis and synthesis methods electric vehicle charging integrated CAEB trajectory optimisation road vehicles connected automated electric buses traveling time

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Optimization of Energy Storage Day Ahead Quotation Strategy Considering Negative Electricity Price 3

Optimization of Energy Storage Day Ahead Quotation Strategy ...

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3rd Asian Conference on Frontiers of Power and Energy

作者： Li, Linghao Zhang, Guofang Tang, Lun Wu, Jun Huang, Zhenyu China Elect Power Res Inst Ltd Beijing Peoples R China State Grid Sichuan Elect Power Co Chengdu Peoples R China Xi An Jiao Tong Univ Coll Elect Engn Xian Peoples R China Sichuan Univ Coll Elect Engn Chengdu Peoples R China

ISBN: (纸本)9798350378467;9798350367676

Energy storage technology can effectively convert, store, and utilize energy, thereby enhancing the flexibility and reducing the operating costs of power systems. In the electricity market, the participation of a large number of low-cost renewable energy sources has lowered market prices, leading to the occurrence of low or even negative electricity prices. This presents an opportunity for energy storage operators to charge at low costs. Based on this, this paper proposes an energy storage bidding optimization strategy that considers negative electricity prices. Firstly, the reasons for the occurrence of negative electricity prices in the energy market are analyzed. Subsequently, a bilevel programming model is established for energy storage operators participating in day-ahead market transactions, taking into account negative electricity prices. The model is solved using duality theory and KKT optimality conditions. Finally, the results of case study analysis demonstrate that utilizing negative electricity prices for energy storage charging can encourage the integration and utilization of renewable energy sources. Moreover, the energy storage bidding strategy considering negative electricity prices allows energy storage operators to flexibly adjust the timing of charging and discharging, enabling them to better seize market opportunities and improve profitability.

关键词： Electricity market Negative electricity price Bidding strategy bilevel programming model

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Energy Storage Capacity Allocation Strategy for Wind Solar Energy Storage Combined System Based on Multi Time Scale Market Transaction 6

Energy Storage Capacity Allocation Strategy for Wind Solar E...

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6th Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Liu, Guoqing Zhou, Bowen Zheng, Hongwei Liu, Yubo Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China State Grid Liaoning Elect Power Co Ltd Informat & Telecommun Branch Shenyang Peoples R China

ISBN: (纸本)9798350373486;9798350373479

The establishment of the combined system of wind power, photovoltaic and energy storage provides a strong guarantee for solving the problem of absorbing renewable energy, but there are still some problems in the economic and rational allocation of energy storage capacity. Facing the long-term cost recovery problem of energy storage equipment, this paper first analyzes the power sales models of the medium and long-term contract market and the spot market, and proposes a medium and long-term contract power decomposition method considering the demand response mechanism, which clusters and optimizes the power load curves of typical users of power purchasers, and decomposes the long-term scale power trading process into intra day periods;Then, a bilevel programming model of capacity allocation is constructed to solve the optimal allocation of energy storage and the optimal operation of the system under a variety of transaction contents;Finally, by setting different contract transaction contents, the impact on the optimal allocation capacity of energy storage and the benefits of the joint system is analyzed. The research results enable the investment cost of energy storage to be effectively recovered through the medium and long-term contract market, and provide an important basis for the actual construction of energy storage resources at the generation side under market conditions.

关键词： Medium and long term contract market Electricity decomposition bilevel programming model Energy storage optimization

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Hierarchical scheduling algorithm design of active distribution network based on multi-microgrid system

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APPLIED NANOSCIENCE 2022年第4期13卷 2901-2910页

作者： Geng, Quanfeng Lu, Xiaoxiao Liu, Shujie Su, Xin Huo, Yujia State Grid Hebei Mkt Serv Ctr Mkt Big Data Ctr Shijiazhuang 050000 Hebei Peoples R China State Grid Xingtai Elect Power Supply Co Mkt Dept Xingtai 054001 Peoples R China

In recent years, the high penetration of renewable energy into the power grid is facing an obvious phenomenon of abandoning wind and light. Microgrid provides a good platform for the full utilization of renewable energy. The coordinated scheduling among multiple microgrids under active distribution network will further improve the utilization rate of renewable energy. Aiming at the problems of reduced distribution reliability, long scheduling time, and poor load balance in the current multi-microgrid access distribution network scheduling methods, an active distribution network hierarchical scheduling algorithm based on multi-microgrid system is designed. Construct a multi-microgrid active distribution network two-level planning model, optimize the energy storage configuration of the microgrid system, and control the battery capacity, charge and discharge performance and the equivalent voltage state of the grid at the same time, to provide support for the distribution network load balancing dispatch. Cross-source scheduling method combined with big data technology is used to preprocess active distribution network load. The improved ant colony optimization algorithm is used to construct the analytical model of the corresponding user type of the hierarchical dispatching terminal of the active distribution network to complete the dispatching optimization. According to the expected adjusted hierarchical load proportion distribution, combined with the ant colony optimization results, the hierarchical scheduling of active distribution network is realized. The IEEE 14-bus distribution network system is taken as an example to verify the algorithm. The experimental results show that under the proposed algorithm, the daily average deviation between the pre-measurement and the actual quantity of distribution power transmission in multi-microgrid is less than 2%, the maximum load balancing degree after scheduling is 99.8%, and the scheduling overhead is less than 0.95 s. It can

关键词： Multi-microgrid system Active distribution network bilevel programming model Hierarchical scheduling Improved ant colony algorithm

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Effects of second-best tradable credit scheme on transportation network for travel mobility management

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TRANSPORTMETRICA A-TRANSPORT SCIENCE 2024年第1期20卷 36-36页

作者： Chai, Jiajian Wang, Guangmin Xu, Meng Gao, Ziyou China Univ Geosci Sch Econ & Management Wuhan 430074 Peoples R China Beijing Jiaotong Univ Sch Syst Sci Beijing 100044 Peoples R China

The second-best tradable credit scheme is studied to analyse its effects on travel mobility by a bilevel programming model. The transport authority optimises the credit charging scheme to minimise the total system travel time and travellers choose paths to minimise their generalised travel costs. A genetic algorithm with some improvements on the selection operator is used to solve the proposed bilevel programming model. In numerical experiments, we discuss the implications of travellers' path choice behaviour and traffic flow distribution under the second-best tradable credit scheme with different combinations of credit-charging links. The results show that the credit charging scheme with all links is obviously better than other schemes in the total system travel time. Besides, the credit charging scheme using congested links or duplicate links of the maximum traffic flow path as credit-charging links is effective in reducing traffic flow on congested links and mitigating the congestion of the whole transportation network.

关键词： The tradable credit scheme travel mobility management fixed origin-destination (OD) traffic demand bilevel programming model

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Optimal Routing Design of Feeder Transit With Stop Selection Using Aggregated Cell Phone Data and Open Source GIS Tool

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2021年第4期22卷 2452-2463页

作者： Wei, Ming Liu, Tao Sun, Bo Civil Aviat Univ China Sch Air Traff Management Tianjin 300300 Peoples R China Southwest Jiaotong Univ Sch Transportat & Logist Natl Engn Lab Integrated Transportat Big Data App Chengdu 611756 Peoples R China

A novel bilevel programming model for designing feeder bus routes to simultaneously consider bus stop selection, bus routing, and passenger route/trip choice behavior is developed in this work. The objective of the upper-level model is to minimize the total in-vehicle travel time of passengers. The objective of the lower-level model is to determine bus stop locations and assign passenger demand to stops by minimizing the total passenger walking time. An ant colony optimization-based two-stage heuristic algorithm is developed to solve the bilevel programming model within an acceptance computation time. Different from conventional methods, the proposed methodology benefits from using real temporal and spatial characteristic datasets of travel demand aggregated from cellular data and traveling time and distance matrices under actual traffic conditions resulted from an open geographic information system (GIS) tool. Results of a real-life case study in Chongqing municipality, China, show that the proposed methodology could achieve a significant reduction of 2.9% total passenger travel time compared with a traditional method. Finally, sensitivity analyses are conducted to further understand the performance of the model. It is anticipated that the proposed methodology could be very useful in designing attractive and cost-effective feeder transit service in practice.

关键词： Routing Mathematical model Transportation Analytical models programming Tools Mathematical programming Intelligent transportation systems (ITS) feeder transit service bilevel programming model cell phone data open source GIS tool

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Traffic Inflow Control Problem on Urban Freeway Network for Disease Prevention

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JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS 2021年第9期147卷

作者： Lin, Hongzhi Zhang, Yongping Southeast Univ Sch Econ & Management Nanjing 211189 Peoples R China Calif State Polytech Univ Pomona Dept Civil Engn Pomona CA 91768 USA

The outbreak of coronavirus disease 2019 (COVID-19) disrupted our regular life. Many local authorities enforced a cordon sanitaire to contain the rapid spread of the disease. Travelers can only pass the cordon after the disease screening. This paper aims to propose a method to design a traffic inflow control scheme for onramp metering to maximize urban freeway network throughput with an endurable queuing delay constraint at all offramps around cordon sanitaire. A bilevel programming model is formulated where the lower level is transportation system equilibrium to predict link traffic flows. The upper level is onramp metering optimization that is nonlinear programming. A stochastic queuing model is used to represent the waiting phenomenon at each offramp where the disease testing is conducted. A heuristic algorithm is designed to solve the proposed bilevel programming model where the method of successive averages (MSA) is adopted for the lower-level model, and a genetic algorithm (GA) with elite strategy is adopted for the upper-level model. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that these methods can find a good heuristic optimal solution. These methods are useful for freeway operators to determine the optimal onramp control for disease control and prevention. They are also beneficial to set up checkpoints for all kinds of risks such as drunk driving and criminal searching.

关键词： Cordon sanitaire Onramp metering bilevel programming model Heuristic algorithm Queuing theory

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Business strategy for high-speed rail in the express delivery sector: A case study of China using a bilevel programming method

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JOURNAL OF RAIL TRANSPORT PLANNING & MANAGEMENT 2021年 20卷

作者： Liang, Xiaohong Wang, Yong Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China Beijing Transport Inst Beijing 100073 Peoples R China Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China

The aim of this paper is to identify a business strategy for high-speed rail (HSR), including market positioning and price strategy, in the Chinese express delivery market using a bilevel programming model. Three routes were selected for case studies. The results showed that parcels with a high value of time (VOT) are mostly distributed to self-owned airlines. Compared with highway and conventional rail transport, HSR is relatively competitive for parcels with high VOT in both long- and middle-distance transport and parcels with extremely high VOT in middle-distance transport. Highway transport is the dominant mode for parcels with extremely low VOT in both long-distance and middle-distance routes. The freight rate of HSR must be more than 30% lower than that of air to be more competitive. Additionally, a sensitivity analysis considering increased speed and relocation of parcel distribution centres was performed to identify factors that affect the competitiveness of HSR in the express delivery sector. The results showed that the competitiveness of HSR for parcels with high VOT is improved significantly in middle-distance routes when either measure is adopted. However, there is no remarkable change in the performance of HSR for long-distance parcel transport and parcels with low VOT.

关键词： HSR Express delivery companies Mode choice Business strategy bilevel programming model

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