KiWi Power – Demand Response for Electric Vehicles

Codibly / KiWi Power – Demand Response for Electric Vehicles

KiWi Power – Demand Response for Electric Vehicles


“Codibly has been a vital partner in our development and I have been impressed with their professionalism, flexibility and understanding of our key needs.”



Electric Vehicles (EVs) are seen as an important sustainable alternative and governments see them as key to cutting emissions and reducing global warming. However, the combined impact of mass vehicle charging at peak times of the day would put the existing electricity grid under extreme pressure. The challenge lies in creating a smart system to recognize charging behaviors and manage demand efficiently.


Without smart charging, the use of EVs is likely to result in higher electricity costs to end users and poor reliability of electricity supply. KiWi Power is working with Shell on a trial to understand and measure the potential value that managed smart charging will provide. A smart charger would monitor and control multiple charging assets, optimize these for peak time use and demand response purposes – reducing overall electricity costs. Together with Shell, KiWi Power has designed a smart system that looks for charging behavioral patterns and identifies best times for inclusion in demand response and frequency response programmes. The first pilot for the programme is taking place in London with additional trials planned across three global markets.


Shell has a possibility to earn money on demand response while interrupting charging a group of electric cars when energy demand is high.

Our Technolgy

Throughout the project we have been working on developing the following:
  • REST API (PHP) to communicate with Routemonkey (3rd party application) to send/receive information when and how many kilowatts of energy we can get when we dispatch.
  • Java queuing system (RabbitMQ) to collect power measurements of chargers from Drives (3rd party application)
Together with and (those partners provided a platform for fleet vehicles management and handling fleet chargers) our solution and software was back-end part of the application – for data collection, dispatch decision making, rest API communication between the whole ecosystem, with following goals:
  • collecting, storing and transferring information when fleet vehicles are being charged;
  • gathering information how many energy we can obtain when we will dispatch them;
  • sending information when to start/pause/stop charging cars for optimum energy usage;