Distributed Source-Load-Storage Cooperative Low-Carbon Scheduling Strategy Considering Vehicle-to-Grid Aggregators

The vehicle-to-grid(V2G)technology enables the bidirectional power flow between electric vehicle(EV)batteries and the power grid,making EV-based mobile energy storage an appealing supplement to stationary energy storage systems.However,the stochastic and volatile charging behaviors pose a challenge for EV fleets to engage directly in multi-agent cooperation.To unlock the scheduling potential of EVs,this paper proposes a source-load-storage cooperative low-carbon scheduling strategy considering V2G aggregators.The uncertainty of EV charging patterns is managed through a rolling-horizon control framework,where the scheduling and control horizons are adaptively adjusted according to the availability periods of EVs.Moreover,a Minkowski-sum based aggregation method is employed to evaluate the scheduling potential of aggregated EV fleets within a given scheduling horizon.This method effectively reduces the variable dimension while preserving the charging and discharging constraints of individual EVs.Subsequently,a Nash bargaining based cooperative scheduling model involving a distribution system operator(DSO),an EV aggregator(EVA),and a load aggregator(LA)is established to maximize the social welfare and improve the low-carbon performance of the system.This model is solved by the alternating direction method of multipliers(ADMM)algorithm in a distributed manner,with privacy of participants fully preserved.The proposed strategy is proven to achieve the objective of low-carbon economic operation.

Research progress of mobile cold storage using ice slurry

The demand for cooling,such as that of products,spaces,and processes,has increased with the development of urbanization.Cold storage can shift the valley time of electric power to cold energy.Compared to the fixed cold storage routine,mobile cold storage can eliminate site limitations.Ice slurry,as a new functional fluid,has recently become a new source of technology in our social lives.First,the research status of ice slurry mobile cold storage is summarized.Applications in the engineering field,such as space cooling,fisheries,pipeline cleaning,firefighting,and other real scenarios,are listed.Subsequently,key issues are summarized to understand the theoretical basis of ice slurry mobile cold storage,including flow,heat transfer,and loss in the mobile cold storage process-related ice slurry.Both tap water ice slurry and binary ice slurry are distinguished and discussed.Finally,beneficial policy analyses and market prospects for its promotion are presented.In summary,ice slurry mobile cold storage is a popular research topic with broad prospects for energy storage.

Optimal integration of mobile battery energy storage in distribution system with renewables

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.

Two-step Optimal Allocation of Stationary and Mobile Energy Storage Systems in Resilient Distribution Networks

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.

Bi-level Optimal Operation Model of Mobile Energy Storage System in Coupled Transportation-power Networks

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.