The Intelligent Electricity Network of the Future: SmartGrid

We live surrounded by networks. The first such network was probably the postal services, and now the young generation are already using 4G mobile Internet. Megawatts and gigawatts are not as easy to handle as megabytes and gigabytes. Transferring huge amounts of electrical energy requires big investments. The story started at the end of the 19th century with steam engines, generating power first for factories, later for the settlements of workers, moving close to the big industrial centers. Connecting those resulted in national grids available at least for the urbanized areas. It may sound strange, but the consumption habits have changed very little during the last 120 years. There is a meter outside the house and anybody can draw any time as much energy as he/she pleases. All this has happened with fixed prices not depending upon the actual state of the supply and the demand - which is rather strange nowadays. The events on 11th of Sept. 2001 taught us that we are vulnerable even at home. The 2003 big blackout lasting four days on the east coast of USA and causing huge damages and losses implied that something has to be done: it should not happen any more. We already know from the information technology: networks should be redundant, diverse, distributed, hierarchically built, self-diagnosing and self-healing in order to be able to provide robust and reliable service. How to achieve that? On the other hand, the unpredictable and renewable energy resources are growing very rapidly. Photovoltaic cells, wind turbines, biogas, etc. They are relatively small, but very numerous and they cannot be handled efficiently in the old-fashioned centralized way. We need local energy storage as much as possible to cover periods of time when the sun is down and the wind is not blowing. That implies that customers have to be smart, more intelligent to optimize the various possibilities in the environment of new, fast-changing flexible electricity tariffs. Different countries are in different situations, depending upon their individual historical background and levels of development. There is no common approach for improvement. There will be different ideas, different methods presented and compared in a relatively easy understandable way. This is where our knowledge and experience steps in: simulation. Experimenting with big power is expensive, but the modelling is straightforward and reliable, and different approaches can be worked out relatively easily and this need not take very long periods of time.