WP3 Overview - Distributed integration technology development

30. April 2012


The purpose of the EDISON WP3 workpackage was the development of a technical solution for intelligent system integration of distributed electric vehicles (EVs) plugged into an electric grid, in private homes or at charging stations in company and public parking lots.


The main challenge were the development of a suitable aggregation technology for low-cost, efficient, plug-and-play integration of small-scale distributed energy resources (here EVs) into the power system. The technical solution was expected to benefit from the virtual power plant (VPP) technology that is being developed for microCHPs, as well as from ongoing demand-response (DR) activities that aim at standardizing interactions to shape power production and consumption. The key issue is how to maintain security of supply in an electric grid that incorporates a high percentage of green, but fluctuating wind energy and also has a significant number of mobile EVs, which represent both a challenge and huge storage/regulation potential. Both central and distributed control with grid DSO/TSO and market integration methods were investigated, which are also being studied as part of EcoGrid. For EV communication, the objective was to define a solution that gives the user a choice of aggregator and degree of grid-support services in order to analyze and enable a range of vehicle-to-grid optimization plans.

The overall focus was on designing and prototyping a secure server solution to support the functioning of a wide-area intelligent system spanning geographical distance and various classes of intelligent devices potentially generating huge amounts of real-time data flows. While the initial prototyping was tested and benchmarked in the Consortium laboratories, the goal was to facilitate the Bornholm island pilot and help in the assessment of full-scale Danish national plans in this space.

The key participants in EDISON WP3 were DTU Centre for Electric Technology and Informatics, and IBM Denmark and Research – Zurich. As part of the WP3 Special PhD Study, we appreciate the contributions of Peter Bach Andersen, Francesco Marra, and Anders Bro Pedersen. Essential interactions with WP2, WP4, WP5, and WP6 are also acknowledged.