Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal alloc...Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal allocation model is proposed to obtain the optimal allocation (location and size) of stationary ESSs (SESSs) and mobile ESSs (MESSs) in the resilient distribution networks (DNs). In the first step, a mixed-integer linear programming (MILP) problem is formulated to obtain the preselected location of ESSs with consideration of different scenarios under normal operation conditions. In the second step, a two-stage robust optimization model is established to get the optimal allocation results of ESSs under failure operation conditions which are solved by column-and-constraint generation (C&CG) algorithm. A hybrid ESS allocation strategy based on the subjective and objective weight analysis is proposed to give the final allocation scheme of SESSs and MESSs. Finally, the proposed two-step optimal allocation model is demonstrated on a modified IEEE 33-bus system to show its effectiveness and merits.展开更多
The operation characteristics of energy storage can help the distribution network absorb more renewable energy while improving the safety and economy of the power system.Mobile energy storage systems(MESSs)have a broa...The operation characteristics of energy storage can help the distribution network absorb more renewable energy while improving the safety and economy of the power system.Mobile energy storage systems(MESSs)have a broad application market compared with stationary energy storage systems and electric vehicles due to their flexible mobility and good dispatch ability.However,when urban traffic flows rise,the congested traffic environment will prolong the transit time of MESS,which will ultimately affect the operation state of the power networks and the economic benefits of MESS.This paper proposes a bi-level optimization model for the economic operation of MESS in coupled transportation-power networks,considering road congestion and the operation constraints of the power networks.The upper-level model depicts the daily operation scheme of MESS devised by the distribution network operator(DNO)in order to maximize the total revenue of the system.With fuzzy time windows and fuzzy road congestion indexes,the lower-level model optimizes the route for the transit problem of MESS.Therefore,road congestion that affects the transit time of MESS can be fully incorporated in the optimal operation scheme.Both the IEEE 33-bus distribution network and the 29-node transportation network are used to verify and examine the effectiveness of the proposed model.The simulation results demonstrate that the operation scheme of MESS will avoid the congestion period when considering road congestion.Besides,the transit energy consumption and the impact of the traffic environment on the economic benefits of MESS can be reduced.展开更多
An optimal sizing method is proposed in this paper for mobile battery energy storage system(MBESS)in the distribution system with renewables.The optimization is formulated as a bi-objective problem,considering the rel...An optimal sizing method is proposed in this paper for mobile battery energy storage system(MBESS)in the distribution system with renewables.The optimization is formulated as a bi-objective problem,considering the reliability improvement and energy transaction saving,simultaneously.To evaluate the reliability of distribution system with MBESS and intermittent generation sources,a new framework is proposed,which is based on zone partition and identification of circuit minimal tie sets.Both analytic and simulation methods for reliability assessment are presented and compared in the framework.Case studies on a modified IEEE benchmark system have verified the performance of the proposed approach.展开更多
基金This work was supported by the Science and Technology Project of State Grid Corporation of China“Research on resilience technology and application foundation of intelligent distribution network based on integrated energy system”(No.52060019001H).
文摘Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal allocation model is proposed to obtain the optimal allocation (location and size) of stationary ESSs (SESSs) and mobile ESSs (MESSs) in the resilient distribution networks (DNs). In the first step, a mixed-integer linear programming (MILP) problem is formulated to obtain the preselected location of ESSs with consideration of different scenarios under normal operation conditions. In the second step, a two-stage robust optimization model is established to get the optimal allocation results of ESSs under failure operation conditions which are solved by column-and-constraint generation (C&CG) algorithm. A hybrid ESS allocation strategy based on the subjective and objective weight analysis is proposed to give the final allocation scheme of SESSs and MESSs. Finally, the proposed two-step optimal allocation model is demonstrated on a modified IEEE 33-bus system to show its effectiveness and merits.
基金supported in part by the National Natural Science Foundation of China(No.51777126).
文摘The operation characteristics of energy storage can help the distribution network absorb more renewable energy while improving the safety and economy of the power system.Mobile energy storage systems(MESSs)have a broad application market compared with stationary energy storage systems and electric vehicles due to their flexible mobility and good dispatch ability.However,when urban traffic flows rise,the congested traffic environment will prolong the transit time of MESS,which will ultimately affect the operation state of the power networks and the economic benefits of MESS.This paper proposes a bi-level optimization model for the economic operation of MESS in coupled transportation-power networks,considering road congestion and the operation constraints of the power networks.The upper-level model depicts the daily operation scheme of MESS devised by the distribution network operator(DNO)in order to maximize the total revenue of the system.With fuzzy time windows and fuzzy road congestion indexes,the lower-level model optimizes the route for the transit problem of MESS.Therefore,road congestion that affects the transit time of MESS can be fully incorporated in the optimal operation scheme.Both the IEEE 33-bus distribution network and the 29-node transportation network are used to verify and examine the effectiveness of the proposed model.The simulation results demonstrate that the operation scheme of MESS will avoid the congestion period when considering road congestion.Besides,the transit energy consumption and the impact of the traffic environment on the economic benefits of MESS can be reduced.
基金This work was supported by the National Natural Science Foundation of China(Young Scholar Program 71401017,General Program 51277016)State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(Grant No.LAPS14002)+1 种基金Fujian regional science and technology major projects,China(2013H41010151)Hong Kong RGC Theme Based Research Scheme Grant No.T23-407/13-N.
文摘An optimal sizing method is proposed in this paper for mobile battery energy storage system(MBESS)in the distribution system with renewables.The optimization is formulated as a bi-objective problem,considering the reliability improvement and energy transaction saving,simultaneously.To evaluate the reliability of distribution system with MBESS and intermittent generation sources,a new framework is proposed,which is based on zone partition and identification of circuit minimal tie sets.Both analytic and simulation methods for reliability assessment are presented and compared in the framework.Case studies on a modified IEEE benchmark system have verified the performance of the proposed approach.
