Abstract

In literature, several mechanisms are proposed to prevent Plug-in Electric Vehicles (PEVs) from overloading the distribution grid. However, it is unclear how such technical mechanisms influence the market level control strategies of a PEV aggregator. Moreover, the presence of multiple aggregators in the same distribution grid further complicates the problem. Often, grid congestion management mechanisms are proposed to solve the potential interference between the technical and market objectives. Such methods come at the expense of additional complexity and costs, which is not beneficial for the large scale application of demand response. In our work, we investigate this problem by combining a simple low level voltage droop controller with an event driven control strategy for the coordination of charging PEVs. The approach is evaluated in different distribution grid settings, using two different market objectives for the aggregator. Document type: Part of book or chapter of book

Abstract

Summarization: New reports predict that the penetration levels of electric vehicles will surge across Europe the following years, as zero emissions vehicles become the mainstream item for consumers and vehicle manufacturers will introduce many new full electric models. In certain parts of Europe, like Norway, more than 50% of new car sales are electric. This will result in a heavy electrical power demand that should be predicted. Many prediction studies were made, mainly focused on the energy consumed by the vehicle and the time it stayed parked in certain locations. The effect of the electricity price on these prediction models is examined, hoping that it will ease the grid of huge charging loads during peak hours. This is accomplished by using an artificial intelligence algorithm in order to calculate the probability of charging a vehicle and then an optimization algorithm that allots the charging power in time slots based on the electricity price of each slot. Results are positive. Less cars are connected to charging stations; the charging of these cars was deemed unnecessary by the algorithm because they had enough energy to return to their home charging stations. The cars that eventually connected required less energy, because again the algorithm charged them with the necessary power only, which led to a load reduction at off-home locations. The optimization algorithm shifted the load towards low-demand time slots, where electricity is cheaper. Furthermore, when grid was on its peak hours, highly charged cars supported it by connecting on it and providing energy (V2G).

Abstract

Due to an increase in environmental awareness and an improved understanding on the impact of human activity on our planet’s climate, there is a strong desire both from governments and the general public to reduce harmful pollution and emissions. This requires action on different fronts, like decarbonizing electricity generation, industrial activity and not least the transport sector. This thesis aims to contribute to the development of a sustainable road transport system. There are several technologies that could achieve this goal, but the scope of this work is limited to automotive electrification in the form of hybrid and battery electric vehicles. Such vehicles currently seem to be the most promising technology, having a larger market share than e.g fuel cell electric vehicles. In order to increase the pace of automotive electrification it is necessary to understand the factors that are currently hindering its adoption. First, the higher cost of electrified vehicles when compared with their conventional counterpart is seen by most potential buyers as their main drawback, despite lower operating and maintenance costs. Second, their limited range and long recharging times cause range anxiety on the drivers and generate concerns over the capabilities of the vehicles to provide the expected service and level of convenience. Finally, the lack of charging infrastructure poses a challenge for potential users.In order to develop an understanding on how to address these issues, the present work takes a holistic approach that starts with the development of performance and cost models for the main components required in an electromobility system. These models are used to optimize the design of an electric powertrain for passenger vehicles. Three electrical machine topologies and two powertrain concepts are considered in this optimization. The results point out that significant cost benefits can be obtained from an increase in the top speed of the electric traction machine as well as the addition of a second speed to the transmission. Additionally, the developed methodology allows exploring a large space of search in a way that reduces development times and associated costs.Moving the focus to a higher level of abstraction, the described models are used to analyze the implications of deploying alternative forms of charging infrastructures in a national context. This analysis shows that a large deployment of a dynamic charging infrastructure accessible by both passenger and commercial vehicles significantly reduces the societal cost of electrification. This is due to the possibility of reducing the required battery capacity on-board the vehicles without affecting their driving range.

Abstract

Charging infrastructure for electric vehicles (EV) will be the key factor for ensuring a smooth transition to e-mobility. This paper focuses on five technologies that will play a fundamental role in this regard: smart charging, vehicle-to-grid (V2G), charging of EVs from photovoltaic panels (PV), contactless charging and on-road charging of EVs. Smart charging of EVs is expected to enable larger penetration of EVs and renewable energy, lower the charging cost and offer better utilization of the grid infrastructure. Bidirectional EV chargers will pave the way for V2G technology where the EV can be used for energy arbitrage and demand-side management. Solar charging of EV will result in sustainable transportation and use of the EV battery as PV storage. On the other hand, stationary contactless charging and on-road inductive charging of EV will remove the necessity for any cables, eliminate range anxiety issues and pave the way for automated driving. The electromagnetic and power converter design for contactless power transfer systems for future highways is reviewed in this paper.

Abstract

The report gives an extensive overview of the results of the project entity Electric Commercial Vehicles (ECV) that was active 2012–2016 under EVE programme of the Finnish Funding Agency for Technology and Innovation (Tekes). Contributions to this final report have been made as articles written by several project participants. All the key themes of the project are covered: battery technologies and their applications, electric powertrains and electric vehicles, city buses, non-road mobile machinery, electric commercial vehicle systems and charging, as well as electric vehicles in connection with power grid. Several businesses and products have been launched during the project's span, and continue to emerge and develop in this dynamically progressing field.

Abstract

The Swedish company Solelia Greentech AB has developed a charging station forelectric vehicles based on photovoltaic electricity. This report aims to examine theenvironmental impacts of the charging station in terms of greenhouse gas emissionsand energy flows. This has been done by performing a life cycle assessment. Theresults were further investigated through a sensitivity analysis considering recyclingand production site. From these results, the charging station’s greenhouse gas andenergy payback times have been calculated.The report concludes that the charging station has an energy payback time of 3.5years. The greenhouse gas payback time varies from 4 to 117 years depending onassumptions about the electricity in the national electricity grid, which the electricityproduced by the charging station is calculated to substitute. The total energy infusionto the system is 9.4 MWh and the greenhouse gas emissions per delivered kWh fromone charging station during its lifetime are calculated to 0.078 kg CO2eq.

Abstract

How many Teslas will it take to crash the Los Angeles, California, grid? This thesis conducts a thought experiment to explore whether rapid adoption of electric vehicles (EVs) in Los Angeles will reduce the reliability of electric power in the Los Angeles Department of Water and Power (LADWP) service territory. Federal and state regulations are encouraging the shift to electric transportation in support of policy priorities that include reducing greenhouse gas emissions and reducing dependence on foreign energy sources. However, high market penetration by EVs will change the patterns of electricity use, especially in urban areas. Under some scenarios, EVs could pose a risk to the reliability and resilience of the electric grid serving these areas. To explore this issue, I developed a model that projects the impact of EVs on the peak power load in Los Angeles in 2030 under different scenarios of EV market penetration and constraints on demand for vehicle charging (e.g., time-of-day pricing). I found that even with moderate EV penetration, if vehicle charging is unconstrained, the load placed on the LADWP grid will exceed the established reserve margin in 2030. Only by adopting some form of incentives for EV drivers to shift their power demands from the normal end-of-day charging routine will the LADWP be able to maintain the reliability and resilience of the power grid. http://archive.org/details/hittingtheaccele1094563490 Civilian, Department of Homeland Security Approved for public release; distribution is unlimited.

Abstract

Electric vehicles recharged from renewable energy sources will play an important role in reducing the key adverse impacts of transport: air pollution, depletion of oil resources, and CO2 emissions. But they will also add to the demand for electricity. Most electric vehicles will be charged at home, overnight. If they all charge at the same time, during the evening peak, they could cause the electricity supply of households or streets to become overloaded. Increases in peak demand ultimately require upgrades to the transmission and distribution infrastructure, which add significantly to the cost of electricity. An electric vehicle will typically need to charge for a few hours overnight. Coordinating the charging of electric vehicles distributed over many premises in an area can smooth the total demand in that area. In this paper we describe a simple load control system that uses signals broadcast from street transformers, typically servicing 30-50 premises, to influence the behaviour of smart appliances in the supplied premises to control the demand profile. Time-of-use tariffs can encourage users to shift their demand to times when electricity is cheaper because demand is usually lower. But to better manage the demand for electricity and control peak demand, we need appliances, including electric vehicles, that respond in real time to changing supply conditions by shifting their demand. Ultimately, having demand that can respond to the available supply will allow greater use of variable, renewable energy sources. Refereed/Peer-reviewed