Plug-in hybrid electric vehicles are a midterm solution to reduce the transportation sector's dependency on oil. However, if implemented in a large scale without control, peak load increases significantly and the grid may be overloaded. Two algorithms to address this problem are proposed and analyzed. Both are based on a forecast of future electricity prices and use dynamic programming to find the economically optimal solution for the vehicle owner. The first optimizes the charging time and energy flows. It reduces daily electricity cost substantially without increasing battery degradation. The latter also takes into account vehicle to grid support as a means of generating additional profits by participating in ancillary service markets. Constraints caused by vehicle utilization as well as technical limitations are taken into account. An analysis, based on data of the California independent system operator, indicates that smart charge timing reduces daily electricity costs for driving from $0.43 to $0.2. Provision of regulating power substantially improves plug-in hybrid electric vehicle economics and the daily profits amount to $1.71, including the cost of driving.

Optimal Charge Control of Plug-In Hybrid Electric Vehicles in Deregulated Electricity Markets

Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks – A review

Deployment of PHEV will initiate an integration of transportation and power systems. Intuitively, the PHEVs will constitute an additional demand to the electricity grid, potentially violating converter or line capacities when recharging. Smart management schemes can alleviate possible congestions in power systems, intelligently distributing available energy. As PHEV are inherently independent entities, an agent based approach is expedient. Nonlinear pricing will be adapted to model and manage recharging behavior of large numbers of autonomous PHEV agents connecting in one urban area modelled as an energy hub. The scheme will incorporate price dependability. An aggregation entity, with no private information about its customers, will manage the PHEV agents whose individual parameters will be based on technical constraints and individual objectives. Analysis of the management scheme will give implications for PHEV modelling and integration schemes as well as tentative ideas of possible repercussions on power systems.

Demand Management of Grid Connected Plug-In Hybrid Electric Vehicles (PHEV)

Plug-in hybrid electric vehicles (PHEVs) are the next big thing in the electric transportation market. While much work has been done to detail what economic costs and benefits PHEVs will have on consumers and producers alike, it seems that the more important question is “what impact will PHEVs have on distribution networks nationwide?”. This paper finds that the impact of PHEVs on the distribution network can be determined using the following aspects of PHEVs: driving patterns, charging characteristics, charge timing, and vehicle penetration. The impacts that these aspects of PHEVs will have on distribution networks have been measured and calculated by multiple authors in different locations using many different tools that range from analytical techniques to simulations and beyond. While much work has already been completed in this area, there is still much to do. Areas left for improvement and future work will include adding more stochasticity into models as well as computing and analyzing reliability indices with respect to distribution networks.

The impact of plug-in hybrid electric vehicles on distribution networks: a review and outlook

According to one embodiment of the present invention, a computer manages an electric vehicle charging transaction. A set of principals is identified associated with the charging transaction for an electric vehicle. A principal is an entity having an interest in the charging transaction. Electric vehicle charging information is retrieved from a set of sources. An energy transaction plan is generated during a pre-charge phase using the electric vehicle charging information and based on preferences of one or more principals to govern the charging transaction. The computer initiates a charging phase of the electric vehicle charging transaction for an electric vehicle connected to a charging station according to the energy transaction plan. The charging phase comprises charging the electric vehicle with electricity, storing electricity in the electric vehicle, and removing electricity to de-charge the electric vehicle. The computer settles the financial obligations among principals according to the energy transaction plan.

Electric vehicle charging transaction interface for managing electric vehicle charging transactions

The paper examines the interaction between grid-coupled full hybrid electric vehicles (HEV) and the grid. The interaction allows the hybrid vehicle to travel a significant part of the time in all-electric mode. On the other hand, the grid coupling allows the grid to use the hybrid car as a controllable load and energy storage facility, enabling a higher penetration of variable generation units, such as renewable sources based on wind and photovoltaic cells. Experiments with a battery, grid connection and induction machine prove the feasibility of these grid-coupled hybrid electric vehicles.

Grid Power Quality Improvements Using Grid-Coupled Hybrid Electric Vehicles PEMD 2006

This paper discusses an adaptive control scheme for a bidirectional boost converter used in a hybrid gasolineelectric vehicle. The converter transforms the voltage of the low-voltage battery, approximately 96 V, to 400 V on the DC-link of the motor inverter. The switching frequency of the inverter is 80 kHz, which enables the usage of rather compact 64 μH inductors. However, the sampling frequency of the control scheme is 10 kHz, so the duty cycle of the switches will only be updated after 8 consecutive switching periods. Due to the large dead-time of the switches in comparison with the switching frequency, the response of the current to changes in the duty cycle is highly non-linear. The low sampling frequency of the control scheme combined with the highly non-linear current response makes it impossible for a simple Pi-controller to regulate the current in a satisfactory way. At first the cause of the non-linear response is investigated. Based on that knowledge, a control scheme is developed that adjusts the duty cycle when necessary and switches between two Pi-controllers, one for small currents and one for large currents. This current controller is implemented on two interleaved bidirectional boost converters. The current controller's set point is regulated by the DC-link voltage controller. (6 pages)

Adaptive control scheme for a practical bidirectional DC-DC converter with a 80 kHz switching and a 10 kHz sampling frequency

The interest in electric vehicles (EVs) experiences a strong growth. Batteries of EVs will be charged at home, which means there will be an increase in the household power consumption. This impact on the distribution and transmission grid can be minimized by e.g. (i) a coordinated charging strategy and (ii) choosing an optimal battery size for each vehicle. A second drawback of EVs are the high cost and weight of the batteries. This paper proposes some allocation scenarios to allocate battery sizes to a fleet of plug-in hybrid (PHEV) and battery electric vehicles (BEVs). Based on statistical data of Flanders (northern region in Belgium), a fleet of vehicles with realistic driving patterns is created, which is used to choose the optimal battery size. Different allocation scenarios will be compared regarding the effect on the proportion electric driving, the extra household power consumption and the fleet availability for Vehicle-to-Grid (V2G) services.

Analysis of the optimal battery sizing for plug-in hybrid and battery electric vehicles on the power consumption and V2G availability

A hybrid electric Kart is built as a didactical project for the students of the Master of Engineering: Energy of the KULeuven In order to cope with the growing number of students, a modular hybrid electric kart is conceived The hybrid configuration allows to diversify between several tasks that have to be addressed by the students The tasks include a control scheme for an induction motor, a control scheme and design of a power-factor-correction converter which enables power flow between the DC-link and a gasoline generator and finally the control scheme and design of a DC/DC converter allowing bidirectional power flow between a low voltage battery and the DC-link All control schemes are supervised by a top level control scheme which maximises efficiency The control schemes are programmed in Matlab/Simulink A rapid-prototyping control board runs the model made in Matlab/Simulink The control board interfaces between the different sensors and power electronics present on the kart

A hybrid electric kart with energy flow management as a student project

This paper investigates the impact of electrification of trucks and buses in an urban environment. The vehicles are charged while driving on electrified roads (continuous charging), and battery powered on the non-electrified roads. A power management algorithm is proposed for driving on the electrified roads. Simulations covering a 24-hour time frame are performed for a selected urban area in Paris, France. The resulting peak power demand and energy consumption are calculated for a single road segment and for several adjacent road segments.

S. De Breucker

Papers

Grid Power Quality Improvements Using Grid-Coupled Hybrid Electric Vehicles PEMD 2006

Adaptive control scheme for a practical bidirectional DC-DC converter with a 80 kHz switching and a 10 kHz sampling frequency

Analysis of the optimal battery sizing for plug-in hybrid and battery electric vehicles on the power consumption and V2G availability

A hybrid electric kart with energy flow management as a student project

Electrification of trucks and buses in an urban environment through continuous charging