Many existing battery energy storage system (BESS) control schemes focus on mitigating negative impacts resulting from the operation of distributed energy resources-photovoltaic facilities (DER-PV). These include out-...Many existing battery energy storage system (BESS) control schemes focus on mitigating negative impacts resulting from the operation of distributed energy resources-photovoltaic facilities (DER-PV). These include out-of-firm conditions from reverse power flow or extreme variability in the service voltage. Existing control strategies fail to consider how BESS control schemes need to operate in a consecutive day-to-day basis in order for them to be implemented in the field. In this paper, a novel energy management algorithm capable of dispatching a BESS unit upstream of a multi-megawatt DER-PV is introduced. This algorithm referenced as the Master Energy Coordinator (MEC), accepts forecasted DER-PV generation and individual feeder load to create daily charge and discharge rate schedules. Logic is integrated to the cyclic discharging event to sync with the forecasted peak load, even when it will occur during the morning of the next day. To verify the MEC operation, Quasi-Static Time Series (QSTS) simulations are conducted on a 12.47 kV distribution feeder model utilizing historical head-of-feeder and DER-PV analog DSCADA measurements.展开更多
The operational stability and economy of multi-energy systems(MES)are threatened by various uncertainties,such as variable renewable energy power,energy demands,and weather conditions.Most of the existing methods for ...The operational stability and economy of multi-energy systems(MES)are threatened by various uncertainties,such as variable renewable energy power,energy demands,and weather conditions.Most of the existing methods for the dispatch decisions of MES are based on the prescribed probability distribution or uncertainty sets of random variables,which have many disadvantages,such as potential infeasibility and over-conservatism.In this paper,we propose a novel dispatch model for MES that integrates dispatch decision making,uncertainty set selection,and operational cost control into a unified framework.First,the deterministic dispatch model of MES is introduced,in which the physical characteristics of district heating systems and buildings are fully considered.Then,a novel decision framework that combines the two-stage dispatch strategy and info-gap decision theory(IGDT)is proposed for MES,where the uncertainty set is flexible and can be optimized based on the operational cost budget.Finally,a revised algorithm,based on the column-and-constraint generation method,is proposed for the model.Case studies are performed on MES that includes a 33-bus distribution system and a heating network modified from a real 51-node network located in Jinlin Province,China.The results verify the effectiveness of the proposed method.展开更多
文摘Many existing battery energy storage system (BESS) control schemes focus on mitigating negative impacts resulting from the operation of distributed energy resources-photovoltaic facilities (DER-PV). These include out-of-firm conditions from reverse power flow or extreme variability in the service voltage. Existing control strategies fail to consider how BESS control schemes need to operate in a consecutive day-to-day basis in order for them to be implemented in the field. In this paper, a novel energy management algorithm capable of dispatching a BESS unit upstream of a multi-megawatt DER-PV is introduced. This algorithm referenced as the Master Energy Coordinator (MEC), accepts forecasted DER-PV generation and individual feeder load to create daily charge and discharge rate schedules. Logic is integrated to the cyclic discharging event to sync with the forecasted peak load, even when it will occur during the morning of the next day. To verify the MEC operation, Quasi-Static Time Series (QSTS) simulations are conducted on a 12.47 kV distribution feeder model utilizing historical head-of-feeder and DER-PV analog DSCADA measurements.
基金the National Science Foundation of China(52207080)in part by the State Grid Jiangsu Electric Power Company Science and Technology Project(J2020001)in part by the National Science Foundation of Jiangsu Province(BK20200404).
文摘The operational stability and economy of multi-energy systems(MES)are threatened by various uncertainties,such as variable renewable energy power,energy demands,and weather conditions.Most of the existing methods for the dispatch decisions of MES are based on the prescribed probability distribution or uncertainty sets of random variables,which have many disadvantages,such as potential infeasibility and over-conservatism.In this paper,we propose a novel dispatch model for MES that integrates dispatch decision making,uncertainty set selection,and operational cost control into a unified framework.First,the deterministic dispatch model of MES is introduced,in which the physical characteristics of district heating systems and buildings are fully considered.Then,a novel decision framework that combines the two-stage dispatch strategy and info-gap decision theory(IGDT)is proposed for MES,where the uncertainty set is flexible and can be optimized based on the operational cost budget.Finally,a revised algorithm,based on the column-and-constraint generation method,is proposed for the model.Case studies are performed on MES that includes a 33-bus distribution system and a heating network modified from a real 51-node network located in Jinlin Province,China.The results verify the effectiveness of the proposed method.