A novel stochastic modelling approach for electric vehicle charging power and energy requirements

Abstract

Abstract--Electrification of heat and transport in addition to integration of intermittent renewable resources into the existing electricity network is expected to occur in near future. Such a transformation is expected to force the operation of the electricity power system at different levels to its limits. A novel bottom up modelling approach for quantifying temporal variation of electric vehicle charging power and energy is presented in this paper which can be used to accurately investigate the effect of charging different penetration levels of electric vehicles within the low voltage distribution network. This EV charging model is further used for development of a deterministic control algorithm for regulating power flows at the low voltage level.

Real‐time deterministic power flow control through dispatch of distributed energy resources

“…Therefore, the following stochastic DER, load and DG models have been created in Matlab/Simulink with a temporal resolution of 1 s: † Domestic electricity load [9]. † Electric vehicle (EV) charging [10]. † Domestic heating load [11].…”

“…Every GSHP has been allocated a hot water storage tank of 200 litres which has an equivalent 1.7 kWh of electrical storage capacity, as quantified using "(1)". 7 2.78 10…”

“…This EV model is comprised of the interaction of a lithium ion battery model [14] with a novel stochastic method for quantifying the vehicle's temporal journey characteristic. This modelling approach has been described in [7]. It is worth mentioning that since the majority of network optimisation and control strategies attempt to regulate active power to achieve a combination of objectives concerning generation/delivery/utilization of active power, active power flow has been chosen as the primary control parameter in the CPFC's operation.…”

“… Domestic electricity load [6]  Electric vehicle charging [7]  Domestic heating load [8]  Ground source heat pump [9]  Photovoltaic generation [10,11]  Wind power generation [12,13]  Community battery energy storage [14] A novel modelling technique for accurate quantification of electric vehicle charging requirements in terms of charging energy, power and duration has been developed by the authors. This EV model is comprised of the interaction of a lithium ion battery model [14] with a novel stochastic method for quantifying the vehicle's temporal journey characteristic.…”

A heuristically optimized comprehensive charging scheme for large‐scale EV integration

“…With the application of smart grid and V2G technologies, the users can buy and sell energy at low price valley periods and peak hours respectively, and for power utilities, the peak adjustment compensates for equipment maintenance/investment cost and elevate the load pressure . Without incentive‐based policy guidance and consumer benefits, the uncertain charging behavior of a large number of EVs would cause a group effect, risking the operation safety and reliability of the grid …”