Providing ancillary services through flexible electric vehicle (EV) charging has the potential to offer extra market benefit for EVs. EV aggregator controlling a fleet of EVs can play a significant role in managing the considerable EV charging demand and bid in the electricity markets. The increasing penetration of EVs has created the feasibility of participating in both the day-ahead energy market and frequency regulation market. This article presents a multimarket optimization model for minimizing the net operation cost of EV charging considering the benefit from performing frequency regulation. A two-level optimization algorithm for EVs controlled by the aggregator is proposed to determine optimal operation strategies of EV aggregations and the charging power of each individual EV. The optimization is able to merge revenue from frequency regulation with the cost reduction objectives of traditional EV charging management. The effectiveness of optimization algorithm is demonstrated by simulating EVs charged at the workplace and residential areas. The operation of EV aggregator is studied considering the diverse charging need of individual EV and market prices acquired from Nord Pool real-time market and Swedish power system operator. The increased profitability of participation in the sequential electricity markets has been illustrated. Net operating cost of EV aggregations can be significantly reduced considering both capacity and energy remunerations in the regulation market and the charging demand in the energy market.

A combined delivery of economic dispatch and frequency regulation (FR) services from electric vehicles (EVs) is proposed to exploit the dynamic flexibility of EV charging load and its revenue opportunities in the electricity markets. The economic feasibility is assessed with the combined operation model of EVs for optimal bidding in the day-ahead energy market and FR market. The proposed optimization adopts the hierarchical control framework with EV aggregator (EVA) as the intermediate control unit to interact with the power system operator. As EVs are paid for FR based on their actual performance, a dynamic control strategy for charging EVs in response to regulation signals is developed to validate the technical feasibility of combined operation. The autonomous control of EVA modulates the charging of each EV to ensure the optimal charging schedules and real-time frequency control. A case study reveals that the profitability of EV charging control can be significantly increased by energy cost reduction and additional regulation revenue. The proposed dynamic control with a novel power-sharing strategy of EVA provides effective frequency support based on the optimal charging schedule and capacity bids without violating charging demand and availability constraints of each individual EV.

With the increasing capacity of large-scale electric vehicles, it's necessary to stabilize the fluctuation of charging voltage in order to achieve improvement of lithium-ion battery lifecycle, and the hybrid energy storage system (HESS) including superconducting magnetic energy storage (SMES) and lithium-ion battery is introduced, which is significant to reduce the high frequency discharge cycles and to manage the state of charge (SOC) for batteries with an optimized integration scheme based on power grading approach. With the unscented Kalman filter (UKF) method for battery SOC estimation and the extended Kalman filter (EKF) method for battery internal resistance estimation, the approach for estimating the lithium-ion battery state through adaptive unscented Kalman filter (AUKF) is derived. The AUKF approach takes the form of iterative loop to estimate system parameters and state, so the system strategy has well adaptive characteristics. Experimental results illustrate that the SOC estimation based on the proposed optimized approach for lithium-ion battery in HESS can achieve the well robustness and fast convergence.

This paper presents a methodology for evaluating the techo-economic feasibility of mixed AC and DC distribution network to replace the existing AC distribution network with large-scale integration of photovoltaic energy sources. Economic dispatch of mixed AC/DC system is formulated in the presence of power electronic transformer (PET) for the flexible control of AC and DC power flows while maintaining the reliability constraints in terms of bus voltage, branch current carrying capacity, and the efficient operation of power electronic converters. Furthermore, the configuration of the PET and power losses of converters with a changing operation efficiency is incorporated into the optimal dispatch problem to assess the energy savings provided by the AC/DC power network. Two objectives for minimizing the operating cost and total power losses are also considered in the formulated economic dispatch. To obtain the Pareto-optimal solutions of this reliability constrained multi-objective optimization problem, the non-dominated sorting genetic algorithm-II (NSGA-II) associated with the interior-point method are applied in the proposed two-stage optimal algorithm to solve the optimization for PET configuration and operation. The method has been tested on the IEEE 33-bus radial distribution system with excessive PV installation and updated PETs. In comparison with the optimal dispatch of existing AC power distribution system, the joint optimization of PET AC/DC ports and PV inverters improves the flexibility of power flow control for both AC and DC networks and thus minimizing the PV curtailment and total operating cost.

This paper discusses skid steering applied to four wheel drive electric vehicles. In such vehicles, steering is achieved by differentially varying the speeds of the lines of wheels on different sides of the vehicle in order to induce yaw. Skid steer wheeled vehicles require elaborate tire model, so author choose the unite semi-empirical tire model. From this model, longitudinal and lateral tire force can be calculated by slip ratio directly. The vehicle model has 3-DOF, longitudinal, lateral and yaw direction, irrespective of suspension. Induction motor is chosen as the driven motor, and the control method is rotor flux field oriented vector control. To satisfy the requirement of the turn radius, the longitudinal slip must be controlled, so a method of slip limitation feedback is used in the simulation. When the vehicle is turning on a slippery surface, because of the drop at the coefficient of road adhesion, the drive wheels may slip. The traction control system reduces the engine torque and brings the slipping wheels into the desirable skid range. Some simulation results about the steering accuracy and maneuverability are given in the paper.