2011-01-04 13:06
The new EU directive sets ambitious targets for all EU countries, such as to reach 20% share of energy from renewable sources by 2020. Many countries which started implementing this directive are facing the same problem - the production from renewable energy sources (RES, e.g., windmills, solar panels) cannot be planned, but can only be predicted. Thus, electrical power produced by RES usually does not match the energy consumption, and it must be discarded or given away for free.
The MIRACLE (Micro-Request-Based Aggregation, Forecasting and Scheduling of Energy Demand, Supply and Distribution) project aims to invent and prototype key elements of an energy system that is better able to accommodate large volumes of electricity from RES. The approach is based on flexible offers that allow an individual consumer/producer to specify when and what amount of energy he or she wants to consume/produce. These flexible offers are collected, aggregated, and matched with production from RES. Afterwards, flexible offers are disaggregated and consumers/producers are informed when he or she should start energy consumption/production. We are estimating that in the future every household in Europe will be equipped with such technology and will be sending tens of flexible offers per day. In order to appropriately manage very large volumes of flexible offers, a reliable, distributed, and highly scalable computer system infrastructure is needed.
Work Package 3 concerns data collection, aggregation and storage solutions for the MIRACLE system. This deliverable, which is a part of Work Package 3, specifies a data collection and management system, its components, and presents a methodology for flexible offers aggregation.
Authors:
Laurynas Šikšnys, Dalia Kaulakiené, Torben B. Pedersen, Ralf Rantzau, AAU; Matthias Boehm, TUD.
Work Package 3 concerns data collection, aggregation and storage solutions for the MIRACLE system. This deliverable, which is a part of Work Package 3, specifies a data collection and management system, its components, and presents a methodology for flexible offers aggregation.
Authors:
Laurynas Šikšnys, Dalia Kaulakiené, Torben B. Pedersen, Ralf Rantzau, AAU; Matthias Boehm, TUD.
