A Modelling Tool for Distribution Networks to Demonstrate Smart Grid Solutions

Abstract

-The increased deployment of low carbon technologies in power distribution networks, particularly at the distribution level, is expected to cause significant problems to network operation unless existing networks are appropriately adapted and actively controlled as part of a smart grid. This paper describes the development of a modelling tool to examine Smart Grid solutions to a number of issues affecting low voltage power distribution networks. Use of the tool in the context of transformer overload, line overvoltage, active load control, Grid storage and Black Start analysis is examined.

Smart EV charging schedules: supporting the grid and protecting battery life

“…Uncontrolled charging refers to charging determined by the EV driver, which may occur at any time. To show the effect of different types of charging on the LV network, the authors have developed a network modelling tool [16], which forms the basis of the figures in this section and Section 3. It calculates the effect of different loads on a LV feeder, using a typical winter and summer daily load profile for domestic customers in the UK (Fig.…”

“…(a) Profile of the SOC of an EV battery over one day, with early and late charging, (b) Capacity loss in cells cycled for 5 months with early and late schedules they do support the grid [16]. The battery current is assumed to be the same for charging and V2G.…”

“… Effect of increasing EVs on LV network [16] (a) Transformer loading in p.u., (b) p.u. voltage showing statutory minimum as the dotted line…”

“…• Identify EV charging schedules used at present from driver behaviour studies. • Use a grid-modelling tool [16] to identify the charging schedules that would be beneficial to the grid. • Map these schedules onto the battery degradation model using the impact factors as variables.…”

“…Using a battery degradation model [15], it is possible to compare the degradation of a battery providing grid support with one that does not (conventional use). The methodology adopted in this investigation is: Identify the factors that impact battery life from published results for lithium ion batteries. Run laboratory tests to measure the correlation between each impact factor and battery life. Identify EV charging schedules used at present from driver behaviour studies. Use a grid‐modelling tool [16] to identify the charging schedules that would be beneficial to the grid. Map these schedules onto the battery degradation model using the impact factors as variables. Compare the results of the battery degradation for uncontrolled charging and smart charging that provide support to the grid (G2V and V2G). In this paper, Section 2 gives a summary of the potential impact of uncontrolled charging of EVs on the grid. Section 3 summarises the methods available for EVs to support the grid (G2V and V2G) and introduces their potential impacts.…”