Abstract
Energy demands are constantly increasing worldwide and forecasts estimate them to rise by approximately 44% worldwide by 2030 . At the same time traditional energy sources such as oil, coal gas, etc. diminish continuously, and consequently, there is a demand for renewable clean energy that is closely tied with a general need for more efficient energy production, usage and distribution strategies. In particular, the use of micro-power plants that are, for example, incorporated into smart homes or public buildings offer great potential by providing more dynamic yet dependable energy supply mechanisms. Nevertheless, in order to maximize such resources it is necessary to correlate energy demand with potential supply mechanisms efficiently in order to reduce energy overheads and to maximize the use of available resources in general. Moreover, it is necessary to take into account individual social as well as economic aspects in order to model the underlying environment and the dynamics thereof accurately. For that, new mechanisms are required that lead to intelligent and self-managing networks of knowledge that have the capability to self-organize energy management according to various operational, spatial and socio-economic aspects such as demand, costs, consumer preferences, business goals and others. From an Information and Communications Technology (ICT) perspective, this paper discusses some of the requirements of next-generation energy grids and identifies some of the tasks and challenges in this area that need to be addressed in order to realize infrastructures that are fully intelligent and are also aware of their social and economic parameters so that energy usage can be dynamically and autonomously controlled in relation to global demand and supply.
Original language | English |
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Title of host publication | Proceedings Fourth International Conference on Self-Adaptive and Self-Organising Systems - Workshop on Socio-Economics Inspiring Self-Managed Systems and Concepts (SEISMYC-2010) |
Publisher | IEEE Computer Society |
Pages | 72-75 |
ISBN (Print) | 978-0-7695-4229-4 |
DOIs | |
Publication status | Published (in print/issue) - Oct 2010 |