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Electric vehicles (EVs) have shown promise in providing ancillary services, e.g., frequency regulation. This is mainly due to their capacities and fast response. On the contrary, the rapid integration of EVs in the grid poses challenges, such as frequency and voltage stability. In order to mitigate the above-mentioned issues, several dispatching strategies have been introduced in the recent literature to optimize the charging/discharging rates of EVs. In this paper, a comparative study of power management strategies for secondary frequency regulation (SFR) employing a fleet of EVs is presented. A hierarchical control scheme is employed to compare two cases, namely control at the charging station (CS) level and novel control at the EVs level. Under both cases, a multi-objective optimization approach is utilized to define the optimal charging and discharging rates of EVs using a pattern search algorithm. Furthermore, the performance of the two models is experimented under contingency cases, a notable contribution of this study. Finally, simulations are carried out using OPAL-RT real time simulator to validate the performance of the two models based on real-time traces obtained from Pennsylvania, New Jersey, and Maryland (PJM) interconnection and California independent system operator (CAISO). To further validate the proposed model, a comparison with a mixed-integer linear programming (MILP) based model is presented. [ABSTRACT FROM AUTHOR]

Car-Sharing Systems (CSSs) are becoming increasingly popular in urban areas replacing car ownership. The most attractive CSSs give users the opportunity to make one-way trips. This behavior creates an unbalanced status between stations. Hence, some users could leave the system because they may not find a car/parking place available near their origin/destination. In recent years, CSSs are employing Electric Vehicles (EVs). A recent technology applied to EVs, called Vehicle-to-Grid (V2G), has allowed selling energy, transferring it from vehicle batteries to an electric grid. In this paper, we adopt Electric Cars (ECs) with V2G for one-way station-based CSSs. We suggest ECs distribution among stations at the beginning of each day, simultaneously making the most of V2G technology and satisfying CSSs customers' requests. These distributions represent the final configurations that should be obtained through overnight vehicle relocation. The proposed models have been applied to a real-sized case achieving promising results. [ABSTRACT FROM AUTHOR]

• A cost-effective and high-efficient shared fast charging scheme is proposed. • The enabled DC power is used to supply the terminal charging points. • More EV penetration is to be achieved in old residential communities. • The DC power supply achieves a 1.3 % average transfer efficiency improvement. Charging infrastructures are being deployed widely in urban and rural areas to solve the so-called "last one-kilometer" charging problem. However, for old residential communities, the existing difficult-to-charge issue is not easily solved solely by the widespread deployment of charging infrastructure owing to limited spaces, complex reconstruction, and huge costs. In this context, this paper introduces a cost-effective and high-efficient shared fast charging scheme for old residential communities. The comprised registration-based queuing charging mechanism is proposed to schedule electric vehicle (EV) charging. An integrated and multi-stage power electronic device called smart interlinking unit (SIU) is introduced for grid reconstruction. The SIU-based charging station architecture features flexible control capability, enabling DC power supply for terminal EV chargers. For this architecture, a novel hierarchical coordinated operation strategy is designed, comprising the upper-level real-time vehicle-to-grid (V2G) dispatching and lower-level coordination strategies. Case studies demonstrate that the proposed scheme could accommodate 40 % EV penetration, while exhibiting a significant decline in system investment and occupied area compared to the slow charging scheme. Additionally, a 1.3 % improvement in average transfer efficiency is verified under this architecture. The proposed strategy is proven to realize a prominent power peak-shaving and valley-filling, effective transformer load balance, and DC voltage restoration. [ABSTRACT FROM AUTHOR]

Highlights • Utilization of EVs for power system regulation services is proposed using V2G concept. • G2V/V2G coordination schemes for electricity market participation is developed taking two parking places. • Mobility traits dependent electrical parameters are deduced to obtain regulation schedule. • G2V/V2G model is extrapolated to test the storage capacity commitment through a fleet of BEVs. • Storage capacity contract in electricity markets would result in significant revenue openings. Abstract The objective of this paper is to present a mechanism to determine the two-way energy storage capacity of a large pool of electric vehicles (EV) which can be contracted in ancillary services market on a long-term basis to provide the regulation up (RU) and regulation down (RD) to the grid. The proposed mechanism uses a scheme which delivers the schedule of power supplied to or drawn from the grid by treating the mobility attributes dependent electrical parameters. Two operational places, the workplace, and the home were identified as per driving pattern of customers for the provision of regulation ancillary service. An illustrative model considering a fleet of representative battery electric vehicle (BEV) is presented based on the mechanism, to obtain the minute-wise storage capacity that can be contracted in the market to provide frequency regulation to the grid. Results demonstrate that two major mobility traits namely, driven distance and arrival pattern, as well as the charging and discharging power standards directly influences the regulation schedule. Further, it has been realized that even though the charging cost is associated with energy consumption, the regulation provision will yield a notable revenue stream on a long-term capacity commitment basis. This supplements the concept of EVs participation in power markets by virtue of their high ramp up ramp down speed capabilities. [ABSTRACT FROM AUTHOR]

Appropriate arrangement of the charging and discharging behavior of large number of electric vehicles (EVs) can not only avoid the negative effect to the power grid, but also improve the economy and reliability of power grid operation. In this paper, detailed mathematical model of EV charging aggregator is introduced, while corresponding multi-agent model was built to analysis how EV’s charging behavior can affect the global load characteristics. Different charging controls, consideration of extra energy consumption as well as V2G ratio are simulated in a huge study case with 1 million EVs to verify the conclusion. [ABSTRACT FROM AUTHOR]

An efficient power plant model of electric vehicles (E-EPP) considering the travelling comfort levels of EV users is developed to investigate the contribution of EVs on the unit commitment (UC) of large scale wind farms. Firstly, a generic EV battery model (GEBM) is established considering the uncertainties of battery parameters. Then, a Monte Carlo Simulation (MCS) method is implemented within the E-EPP to obtain the available response capacity of EV charging load over time. And a UC strategy using the E-EPP based on power flow tracing is developed. Finally, a modified IEEE 118-bus system integrated with wind farms is used to verify the effectiveness of the E-EPP for the UC of large scale wind farms. [ABSTRACT FROM AUTHOR]

An efficient power plant model of electric vehicles (E-EPP) considering the travelling comfort levels of EV users is developed to investigate the contribution of EVs on the unit commitment (UC) of large scale wind farms. Firstly, a generic EV battery model (GEBM) is established considering the uncertainties of battery parameters. Then, a Monte Carlo Simulation (MCS) method is implemented within the E-EPP to obtain the available response capacity of EV charging load over time. And a UC strategy using the E-EPP based on power flow tracing is developed. Finally, a modified IEEE 118-bus system integrated with wind farms is used to verify the effectiveness of the E-EPP for the UC of large scale wind farms. [ABSTRACT FROM AUTHOR]

• A fuzzy logic-based smart thermostat is integrated into a HEMS. • MILP-based HEMS enables demand response and increased self-consumption together. • Battery degradation is considered to prevent unnecessary BESS/EV energy arbitrage. • Daily bill reduces from $2.69 to $1.26, self-consumption increases from 75 % to 93 %. • V2G becomes possible in case of a transition from TOU to RTP. Smart thermostats and home energy management systems (HEMSs) are generally studied separately. However, their joint use can provide a greater benefit. Therefore, this study primarily aims to combine a smart thermostat with a HEMS. The mixed-integer linear programming (MILP)-based HEMS performs day-ahead load scheduling for cost-minimization and provides optimal demand response (DR) and photovoltaic (PV) self-consumption, and the fuzzy logic-based thermostat aims efficient DR of air-conditioning and maintenance of thermal comfort. In the first stage, unlike conventional fixed set-point thermostats, the proposed thermostat defines different set-points for each time interval, by fuzzifying input parameters of electricity prices, solar radiation, and occupant presence, to be used by HEMS. In the second stage, the HEMS schedules the operation of time-shiftable, thermostatically controlled, and power-shiftable (battery energy storage system (BESS), electric vehicle (EV)) loads. The HEMS considers bi-directional power flow between home, BESS, EV, and grid, as well as battery degradation to avoid unnecessary energy arbitrage. The simulation results show that a daily cost reduction of 53.2 % is achieved under time-of-use (TOU) and feed-in tariff rates of Turkey. AC cost is reduced by 24 % compared to conventional thermostats. In a future scenario of real-time pricing (RTP) and dynamic feed-in tariff, vehicle-to-grid (V2G) becomes possible. [ABSTRACT FROM AUTHOR]