As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system development.To effectively promote the efficiency and economics of energy storage,centra...As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system development.To effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage batteries is developed to enable energy trading among a group of entities.In this paper,we propose the optimal operation with dynamic partitioning strategy for the centralized SES station,considering the day-ahead demands of large-scale renewable energy power plants.We implement a multi-entity cooperative optimization operation model based on Nash bargaining theory.This model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leasing payment bargaining problem.The distributed alternating direction multiplier method(ADMM)is employed to address the subproblems separately.Simulations reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities,enhances the actual utilization rate of energy storage,and increases the profits of each participating entity.The results confirm the practicality and effectiveness of the strategy.展开更多
With the development of the bike-sharing system(BSS)and the introduction of green and low carbon development,the environmental impacts of BSS had received increasing attention in recent years.However,the emissions fro...With the development of the bike-sharing system(BSS)and the introduction of green and low carbon development,the environmental impacts of BSS had received increasing attention in recent years.However,the emissions from the rebalancing of BSS,where fossil-fueled vehicles are commonly used,are usually neglected,which goes against the idea of green travel in a sharing economy.Previous studies on the bike-sharing rebalancing problem(BRP),which is considered NP-hard,have mainly focused on algorithm innovation instead of improving the solution model,thereby hindering the application of many existing models in large-scale BRP.This study then proposes a method for optimizing the CO_(2)emissions from BRP and takes the BSS of Beijing as a demonstration.We initially analyze the spatial and temporal characteristics of BSS,especially the flow between districts,and find that each district can be independently rebalanced.Afterward,we develop a rebalancing optimization model based on a partitioning strategy to avoid deciding the number of bikes being loaded or unloaded at each parking node.We then employ the tabu search algorithm to solve the model.Results show that(i)due to over launch and lack of planning in rebalancing,the BSS in Beijing shows great potential for optimization,such as by reducing the number of vehicle routes,CO_(2)emissions,and unmet demands;(ii)the CO_(2)emissions of BSS in Beijing can be reduced by 57.5%by forming balanced parking nodes at the end of the day and decreasing the repetition of vehicle routes and the loads of vehicles;and(iii)the launch amounts of bikes in specific districts,such as Shijingshan and Mentougou,should be increased.展开更多
基金supported by the National Natural Science Foundation of China“Game control-based planning and simulation modelling of coupled optical storage hydrogen production system”(No.52277211).
文摘As renewable energy continues to be integrated into the grid,energy storage has become a vital technique supporting power system development.To effectively promote the efficiency and economics of energy storage,centralized shared energy storage(SES)station with multiple energy storage batteries is developed to enable energy trading among a group of entities.In this paper,we propose the optimal operation with dynamic partitioning strategy for the centralized SES station,considering the day-ahead demands of large-scale renewable energy power plants.We implement a multi-entity cooperative optimization operation model based on Nash bargaining theory.This model is decomposed into two subproblems:the operation profit maximization problem with energy trading and the leasing payment bargaining problem.The distributed alternating direction multiplier method(ADMM)is employed to address the subproblems separately.Simulations reveal that the optimal operation with a dynamic partitioning strategy improves the tracking of planned output of renewable energy entities,enhances the actual utilization rate of energy storage,and increases the profits of each participating entity.The results confirm the practicality and effectiveness of the strategy.
基金supported by the National Natural Science Foundation of China (22071246 and 22272178)CAS youth interdisciplinary team (JCTD-2022-12)+1 种基金CAS-Iranian Vice presidency for science and technology joint research project (121835KYSB20200034)China Postdoctoral Science Foundation (2023M733499)。
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.71871022,71828401 and 71521002)the Joint Development Program of Beijing Municipal Commission of Education,the Fok Ying Tung Education Foundation(Grant No.161076)+1 种基金the National Key R&D Program(Grant No.2016YFA0602603)the National Program for Support of Top-notch Young Professionals.
文摘With the development of the bike-sharing system(BSS)and the introduction of green and low carbon development,the environmental impacts of BSS had received increasing attention in recent years.However,the emissions from the rebalancing of BSS,where fossil-fueled vehicles are commonly used,are usually neglected,which goes against the idea of green travel in a sharing economy.Previous studies on the bike-sharing rebalancing problem(BRP),which is considered NP-hard,have mainly focused on algorithm innovation instead of improving the solution model,thereby hindering the application of many existing models in large-scale BRP.This study then proposes a method for optimizing the CO_(2)emissions from BRP and takes the BSS of Beijing as a demonstration.We initially analyze the spatial and temporal characteristics of BSS,especially the flow between districts,and find that each district can be independently rebalanced.Afterward,we develop a rebalancing optimization model based on a partitioning strategy to avoid deciding the number of bikes being loaded or unloaded at each parking node.We then employ the tabu search algorithm to solve the model.Results show that(i)due to over launch and lack of planning in rebalancing,the BSS in Beijing shows great potential for optimization,such as by reducing the number of vehicle routes,CO_(2)emissions,and unmet demands;(ii)the CO_(2)emissions of BSS in Beijing can be reduced by 57.5%by forming balanced parking nodes at the end of the day and decreasing the repetition of vehicle routes and the loads of vehicles;and(iii)the launch amounts of bikes in specific districts,such as Shijingshan and Mentougou,should be increased.
