The impacts of electric vehicles and heat pumps load profiles on low voltage distribution networks in Great Britain by 2050

The impacts of uptake and electricity load profiles of Electric Vehicles (EVs) and Heat Pumps (HPs) on the low voltage (LV) distribution networks were analyzed. The United Kingdom (UK) has a legally mandated policy concerning reduction of greenhouse gasses (GHGs) emissions. Therefore, the integration of low carbon technologies (LCTs) especially EVs and HPs at the LV networks is expected to increase in the drive to reducing the GHGs emissions. Future uptake scenarios, adapted from the National Grid studies, of EVs and HPs were developed for a real and typical urban LV distribution network in Great Britain (GB). Gridlab-D, an agent-based power system simulation software, was used to model the LV distribution network. The model was run for four different scenarios considering seasonal load profiles and projected EVs and HPs uptakes for each of the year 2020, 2030, 2040 and 2050 respectively. The results were analyzed in terms of transformer loading, voltage profiles of the feeders, and the ampacity loading of the cables for the different scenarios of the years

Adaptive thermal model for loading of transformers in low carbon electricity distribution networks

The uptake of low carbon technologies, particularly Electric Vehicles (EVs) and Heat-Pumps (HPs), at the low voltage (LV) distribution network, in the quest of cutting down on greenhouse gas (GHG) emissions in the transportation and residential sectors, has the potential to cause general load increase and may lead to higher and longer peak load demand. This development can, as hinted in previous studies, pose a real challenge of capacity overloading to transformers at the LV distribution network of electricity system. Prolonged periods of transformer overloading could lead to premature transformer failure and shortens transformer's life expectancy. A direct solution to addressing transformer overloading is the upgrading of the transformer capacity. However, the number of LV distribution transformers in electricity system to be upgraded and the resources needed for such operation make the solution less desirable to the Distribution Network Operators (DNOs). Therefore, it is important to develop cost-effective solutions for the optimal utilization of the existing transformer capacity. Adaptive thermal loading of transformers is one of such solutions. This paper focusses on the Adaptive Thermal Loading (ATL) of transformers in LV distribution networks with considerable penetration level of EVs and HPs. The thermal model of a 500-kVA, 11/0.415-kV (no load), 50-Hz, Dyn11, ONAN mineral oil filled, free breathing, ground mounted transformer serving a real and typical urban LV network in the United Kingdom (UK) is developed based on IEC 60,076–7:2005 standard and used as the case study. A method of adaptive thermal loading of the transformer is presented to examine its capacity performance when serving the future load of the LV network following the integration of projected uptake figures of EVs and HPs for the years 2020, 2030, 2040 and 2050 into the network. Given the load and temperature forecasts of a day, the method aims at optimizing, considering the real and present conditions of the operating environment, the overall daily transformer capacity utilization that gives maximum daily return on investment without undermining reliability of supply and normal life expectancy of the transformer. Results show improved performances of the transformer when the adaptive thermal loading method is used

Dispatch model for analysing the impacts of electric vehicles charging patterns on power system scheduling, grid emissions intensity, and emissions abatement costs

Dispatching of generating resources at Power Stations is a complex task based on the balance of economics, contractual agreement, regulations, and environmental consciousness in terms of emissions produced in the course of electricity generation. The complexity of the task could be exacerbated with the integration of a large percentage of Electric Vehicles (EVs) in the quest to reduce CO2 emissions in the transportation sector. In this paper, a dispatch model, which is suitable for analysing the impacts of charging patterns of EVs on grid emissions intensity and emissions abatement costs, is described and developed for dispatching generating resources/technologies. The dispatch model is based on the correlation between historical system load and capacity factors of generating units. The dispatch model is tested on data from the UK power system on a typical winter day in December 2015 with an assumed 50% integration of EVs on the system. Results show amongst others that charging of EVs in the off-peak period may affect the optimal deployment of generating technologies/resources with storage capacity and could produce a higher average grid emissions intensity