Impact of Smart Charging for Consumers in a Real World Pilot

Abstract

A smart charging profile was implemented on 39 public charging stations in Amsterdam on which the current level available for electric vehicle (EV) charging was limited during peak hours on the electricity grid (07:00-08:30 and 17:00-20:00) and was increased during the rest of the day. The impact of this profile was measured on three indicators: average charging power, amount of transferred energy and share of positively and negatively affected sessions. The results are distinguished for different categories of electric vehicles with different charging characteristics (number of phases and maximum current). The results depend heavily on this categorisation and are a realistic measurement of the impact of smart charging under real world conditions. The average charging power increased as a result of the new profile and a reduction in the amount of transferred energy was detected during the evening hours, causing outstanding demand which was solved at an accelerated rate after limitations were lifted. For the whole population, 4% of the sessions were positively affected (charged a larger volume of energy) and 5% were negatively affected. These numbers are dominated by the large share of plug-in hybrid electric vehicles (PHEVs) in Amsterdam which are technically not able to profit from the higher current levels. For new generation electric vehicles, 14% of the sessions were positively affected and the percentage of negatively affected sessions was 5%.

Flexible Charging of Electric Vehicles: Results of a Large-Scale Smart Charging Demonstration

“…This study is a follow up to the project 'Flexpower 1', and a detailed description of the experimental design, data sources, and methods of analysis is presented in the corresponding research paper [21]. The costs associated with upgrading a grid connection are about EUR 700/year and were sponsored by the city of Amsterdam.…”

“…Rather than making the current limitation directly proportional to the local solar power production, a two-level approach was chosen to ensure transparency to the users of the charging stations and to simplify the statistical analysis of the data. This study is a follow up to the project 'Flexpower 1', and a detailed description of the experimental design, data sources, and methods of analysis is presented in the corresponding research paper [21]. The costs associated with upgrading a grid connection are about EUR 700/year and were sponsored by the city of Amsterdam.…”

“…These studies confirm the potential of smart charging to suppress peaks in grid load, but the number of empirical studies is still limited, and these tend to have only few chargers in a well-controlled environment [18][19][20]. In the period of January to August 2018, a medium scale pilot called 'Flexpower 1' was conducted in order to perform a quantitative analysis of how the various stakeholders are affected by smart charging in the complicated setting of the public charging network in Amsterdam [21]. A static smart charging profile was deployed on 39 public charging stations in Amsterdam, providing a lower charging current limit during peak consumption hours (07:00-08:30 and 17:00-20:00) and a higher current limit during the rest of the day.…”

Electric Vehicle Aggregate Power Flow Prediction and Smart Charging System for Distributed Renewable Energy Self-Consumption Optimization

“…By introducing an SA-CMS in PED it is possible to operate in Smart Charging mode, i.e., the aggregate charging power, which is given by Equation 2, is controlled to follow the daily power profile of the internal generation sources. This can result in an EV's load shifting during the hours of more internal generation or may involve a decrease in each EV's charging power to smooth the EV's load profile during peak hours [24][25][26][27]. Of course, this operating mode aims to minimize the power that the system absorbs from the grid, by prioritizing the internal and non-programmable RESs, which present a lower energy price.…”

“…Regarding the integration of EVs into electric systems, the reference literature, apart from the classical charging mode, the so-called grid-to-vehicle (G2V), distinguishes two principal operating modes. The first one is known as smart charging (SC) and it happens when the charging station is capable of monitoring, managing, and restricting the use of charging devices to optimize the energy consumption and charging cost [25,26]. Therefore, the SC may result in EVs' load shifting and shaving [27,28].…”