The feasibility of long range battery electric cars in New Zealand

New Zealand transport accounts for over 40% of the carbon emissions with private cars accounting for 25%. In the Ministry of Economic Development's recently released “New Zealand Energy Strategy to 2050”, it proposed the wide scale deployment of electric vehicles as a means of reducing carbon emissions from transport. However, New Zealand's lack of public transport infrastructure and its subsequent reliance on private car use for longer journeys could mean that many existing battery electric vehicles (BEVs) will not have the performance to replace conventionally fuelled cars. As such, this paper discusses the potential for BEVs in New Zealand, with particular reference to the development of the University of Waikato's long-range UltraCommuter BEV. It is shown that to achieve a long range at higher speeds, BEVs should be designed specifically rather than retrofitting existing vehicles to electric. Furthermore, the electrical energy supply for a mixed fleet of 2 million BEVs is discussed and conservatively calculated, along with the number of wind turbines to achieve this. The results show that approximately 1350 MW of wind turbines would be needed to supply the mixed fleet of 2 million BEVs, or 54% of the energy produced from NZ's planned and installed wind farms

Technology, Sustainability, and Marketing of Battery Electric and Hydrogen Fuel Cell Medium-Duty and Heavy-Duty Trucks and Buses in 2020-2040

The objective of this study is to project the introduction of battery-electric and fuel cell technologies into the medium-duty and heavy-duty vehicle markets and to identify which markets will be most suitable for each of technologies and the factors (technical, economic, operational) which will be most critical to their successful introduction. The use of renewable energy sources to generate electricity and produce hydrogen are key considerations of the analysis. The present status of the battery-electric and hydrogen/fuel cell technologies are reviewed in detail and the futures of these technologies are projected. The design and performance of various types of buses and trucks are described based on detailed simulations of the various electrified vehicles. The total cost of ownership (TCO) of each bus/truck type were calculated using EXCEL spreadsheets and their market prospects projected for 2020-2040. It was concluded that before any of the electrified vehicles can be cost competitive with the corresponding diesel powered vehicle, the unit cost of batteries must be $80-100/kWh and the unit cost of the fuel cell system must be$80-100/kW. The long term economics of battery-electric buses and trucks looks more favorable than that for the fuel cell/hydrogen option if the range requirement (miles) for the vehicle can be met using batteries. This is primarily due to the significantly lower energy operating cost ($/mi) using electricity than hydrogen.View the NCST Project Webpag

Charging Scheduling of Electric Vehicles with Local Renewable Energy under Uncertain Electric Vehicle Arrival and Grid Power Price

In the paper, we consider delay-optimal charging scheduling of the electric vehicles (EVs) at a charging station with multiple charge points. The charging station is equipped with renewable energy generation devices and can also buy energy from power grid. The uncertainty of the EV arrival, the intermittence of the renewable energy, and the variation of the grid power price are taken into account and described as independent Markov processes. Meanwhile, the charging energy for each EV is random. The goal is to minimize the mean waiting time of EVs under the long term constraint on the cost. We propose queue mapping to convert the EV queue to the charge demand queue and prove the equivalence between the minimization of the two queues' average length. Then we focus on the minimization for the average length of the charge demand queue under long term cost constraint. We propose a framework of Markov decision process (MDP) to investigate this scheduling problem. The system state includes the charge demand queue length, the charge demand arrival, the energy level in the storage battery of the renewable energy, the renewable energy arrival, and the grid power price. Additionally the number of charging demands and the allocated energy from the storage battery compose the two-dimensional policy. We derive two necessary conditions of the optimal policy. Moreover, we discuss the reduction of the two-dimensional policy to be the number of charging demands only. We give the sets of system states for which charging no demand and charging as many demands as possible are optimal, respectively. Finally we investigate the proposed radical policy and conservative policy numerically

Electric vehicle possibilities using low power and light weight range extenders

Electric cars have the disadvantage of a limited range, and drivers may experience a range anxiety. This range anxiety can be solved by adding a range extender. But, the range extender should be light so as not to significantly increase the weight of the original vehicle. In urban areas with dense traffic (usually developing countries), the average speed around cities is typically lower than 50km/h. This means, the rolling resistance losses are more important than aerodynamic losses, and a weight reduction results in a bigger electrical range. Therefore, smaller and lighter range extenders are of much interest. The contribution of this paper is to indicate the possibility of range extenders with less than 25 kg with a capacity of 150 to 200 cc to suit a condition where weight counts. In this paper, the cost, environmental and grid impacts of going electric are also discussed. The effect of high altitude and driving style on the performance of an electric vehicle is assessed. The challenges and opportunities of vehicle electrification between countries with decarbonated power generation and fossil fuel dominated power generation are highlighted. Throughout the article, the case of Ethiopia is taken as an example

Emission-aware Energy Storage Scheduling for a Greener Grid

Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the ACM International Conference on Future Energy Systems (e-Energy 20) June 2020, Australi