The adequacy model and analysis of swapping battery requirement for electric vehicles

Abstract

Compared with fossil fuel vehicles, plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EVs) maintain obvious and profound significance for the less city pollutant and operation noise. Moreover, EVs can benefit operation of the power systems via friendly feeding back the energy stored in the EV batteries into the grids when needed. The related research about charging of batteries for EVs has been extensively developed, which is one of the main issues for the application of EVs. This paper focuses on the cooperation between the battery demand and the supply curve problems, when the charging of EV is operated in the swapping way. Firstly, the concept of the swapping battery requirement (SBR) adequacy is presented, and then the corresponding mathematical model is established and the algorithm based on the Monte Carlo method is proposed. In addition, some critical factors which have great influence on the SBR and reserved fully charged battery (RFCB) curves are demonstrated, such as EVs driving cycle, battery capacity, average energy-consuming level and charging time. Simulation results are presented to verify the proposed method.Index Terms--Adequacy, Charging management, Demand and supply, Electrical Vehicle, Monte Carlo method, Plug-in Hybrid Electrical Vehicle, Swapping battery requirement, Vehicle-to-grid (V2G).

Optimization of Battery Swapping Stations With Battery Heterogeneity, Charging Degradation and Pv-Option

“…In [9], a wide discussion over battery degradation, interchangeability, and feasibility is presented. Furthermore, a wide range of BSS studies involving mathematical models and Monte Carlo Simulation [15], BSS integration with power grid [16] and the BSS economic advantages translated into a business case [17] can be found in technical literature. In this sense, the use of computational models can bring insights about the BSS daily operation and all trade-offs decisions involved, especially in cases with hundreds of batteries, different battery models, subjected to hundreds of EV arrivals at a day.…”

“…Constraints (3-13) limit the total batteries in charging by the total number of available chargers N , while (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14) establish the batteries minimum (R m ) and maximum (R m ) charging power rate in case they are in charging (K t,m,b = 1). Equations (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) show the composition of the BSS charging power, which may come both from the PV generation (P P V t,m,b ) or from the grid…”

“…The PV generation distribution is defined with (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16), where a part could be be directed for the batteries charging (E P V t,m,b ) or sold to the grid (E P V S t ) following the spot price (π t ). Since there is no limitation involving its use, there is no PV energy spillage being considered.…”

“…Equations (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18) show the composition of the grid power used by the BSS, with P b t,m,b being the portion below the recommended limit by the grid operator (L), where Constraints (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19) represent this limitation, while P a t,m,b is the above limit portion, which will pay a δ + % increased price. The variables scope are shown in (3-20)-(3-24) and, at last, 3-25 define the set of constraints that establish a charging control behavior, which will be further detailed in Section 3.1.3.…”

“…Along the model constraints, the energy balance between power provided by the grid and PV was adapted in order to increase the PV flexibility, since in [18], during PV generation hours, the BSS was allowed to charge its batteries using only the PV. Following the same idea, the flexibility of power provided by the grid was also increased with the insertion of Constraints (3-18) - (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19), allowing the grid limitation L to be surpassed with a price increase of δ + %. At last, in reference of the model from [18], Constraints (15) and (19) were also removed, since the first one takes use of a rough approximation for the charging limitation due to SoC increment, while the second use wasn't used in the optimization process, since the SoH wasn't even mathematically defined.…”