Theoretical frameworks for the strategic placement of Road Side Units(RSUs)along highways are currently insufficient.In the context of emerging Vehicleto-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication set...Theoretical frameworks for the strategic placement of Road Side Units(RSUs)along highways are currently insufficient.In the context of emerging Vehicleto-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication settings,the impact of the growing presence of smart vehicles on the existing deployment strategy has been overlooked.The current paper therefore introduces a framework for optimizing RSU placement that accounts for the influence of V2V and V2I interactions.To optimize the advantages provided by RSU,the enhancement of RSU deployment scope is realized by leveraging the relay and forwarding capabilities inherent in V2V communications,which helps identify the most efficient deployment intervals,thereby reducing costs.After ascertaining how the intelligent vehicle's transmission range affects the time taken for flooding and recognizing the influence of packet length on the sensor network's energy usage,a novel bilevel programming framework has been introduced.The upper layer model minimizes the flooding time by setting the optimal intelligent vehicle transmission radius.In contrast the lower layer model,under the influence of the upper layer model,maximizes the energy efficiency of the sensing network by setting the optimal packet length.In addition,the conventional interlinking of information and traffic flow theories is restructured for RSU placement,innovatively modeling the benefits throughout the information lifecycle.Regarding information transmission loss,a node energy loss model is determined based on the bilevel programming framework.For construction and maintenance costs,a cost model under different cluster lengths is constructed.Employing MATLAB,a study is executed to scrutinize the multifaceted interdependencies among the density of highway traffic,the saturation of intelligent vehicles,and the distribution of roadside RSUs,to establish the most advantageous spacing for RSU installations.This research lays the groundwork for the deployment of sensor networks along highways.In conclusion,the model's accuracy is confirmed by employing the Warshall algorithm and clustering routing methodologies.展开更多
在分布式能源快速发展和市场化改革加速推进的背景下,分布式能源的市场化接入路径及结算机制设计亟需优化,以提升资源配置效率和市场运行的稳定性。系统梳理美国主要区域市场分布式能源聚合资源参与批发市场的节点建模和定价机制;归纳总...在分布式能源快速发展和市场化改革加速推进的背景下,分布式能源的市场化接入路径及结算机制设计亟需优化,以提升资源配置效率和市场运行的稳定性。系统梳理美国主要区域市场分布式能源聚合资源参与批发市场的节点建模和定价机制;归纳总结FERC Order 2222下单节点与多节点聚合模型的优势、劣势,适用条件及过渡路径,揭示多节点聚合在资源包容性、市场适应性等方面的优势,及其存在的建模复杂、运营成本高、分布因子偏差引发振荡等问题;在此基础上,结合我国现货市场建设阶段、节点模型现状与资源接入特征,提出分阶段构建节点体系、差异化设置聚合范围、优化容量门槛、完善结算机制等策略建议。研究为我国分布式能源市场机制设计和运营策略提供了理论支撑和国际经验借鉴。展开更多
基金supported by the Key Science and Technology Projects in Transportation Industry of the Ministry of Transportation(Grant No.2021-ZD2-047)the Shandong Transportation Science and Technology Planning Project(Grant No.2021B49).
摘要Theoretical frameworks for the strategic placement of Road Side Units(RSUs)along highways are currently insufficient.In the context of emerging Vehicleto-Vehicle(V2V)and Vehicle-to-Infrastructure(V2I)communication settings,the impact of the growing presence of smart vehicles on the existing deployment strategy has been overlooked.The current paper therefore introduces a framework for optimizing RSU placement that accounts for the influence of V2V and V2I interactions.To optimize the advantages provided by RSU,the enhancement of RSU deployment scope is realized by leveraging the relay and forwarding capabilities inherent in V2V communications,which helps identify the most efficient deployment intervals,thereby reducing costs.After ascertaining how the intelligent vehicle's transmission range affects the time taken for flooding and recognizing the influence of packet length on the sensor network's energy usage,a novel bilevel programming framework has been introduced.The upper layer model minimizes the flooding time by setting the optimal intelligent vehicle transmission radius.In contrast the lower layer model,under the influence of the upper layer model,maximizes the energy efficiency of the sensing network by setting the optimal packet length.In addition,the conventional interlinking of information and traffic flow theories is restructured for RSU placement,innovatively modeling the benefits throughout the information lifecycle.Regarding information transmission loss,a node energy loss model is determined based on the bilevel programming framework.For construction and maintenance costs,a cost model under different cluster lengths is constructed.Employing MATLAB,a study is executed to scrutinize the multifaceted interdependencies among the density of highway traffic,the saturation of intelligent vehicles,and the distribution of roadside RSUs,to establish the most advantageous spacing for RSU installations.This research lays the groundwork for the deployment of sensor networks along highways.In conclusion,the model's accuracy is confirmed by employing the Warshall algorithm and clustering routing methodologies.
摘要在分布式能源快速发展和市场化改革加速推进的背景下,分布式能源的市场化接入路径及结算机制设计亟需优化,以提升资源配置效率和市场运行的稳定性。系统梳理美国主要区域市场分布式能源聚合资源参与批发市场的节点建模和定价机制;归纳总结FERC Order 2222下单节点与多节点聚合模型的优势、劣势,适用条件及过渡路径,揭示多节点聚合在资源包容性、市场适应性等方面的优势,及其存在的建模复杂、运营成本高、分布因子偏差引发振荡等问题;在此基础上,结合我国现货市场建设阶段、节点模型现状与资源接入特征,提出分阶段构建节点体系、差异化设置聚合范围、优化容量门槛、完善结算机制等策略建议。研究为我国分布式能源市场机制设计和运营策略提供了理论支撑和国际经验借鉴。