| Abstrakt: |
There is a massive disconnect between the level playing field around which we do electricity, and the way in which we do power system generation (especially electricity generation with distributed energy systems). Some companies are already well-aware of this process and work on it more closely, as their own business model, they do their due diligence, make sure they have the required capital, and build a comprehensive, and sustainable, system that is able to keep costs down and maintain high margins while maximizing value. The concept of self-contained energy networks is discussed in this study (AEGs). These systems have a scalable, reconfigurable, and self-organising information and control architecture, are exceptionally secure and robust (self-healing) and can self-optimise in real-time to ensure economic and dependable performance while systematically integrating all types of energy. It has not yet been established whether self-healing is economically cost-effective or economically sustainable in comparison with a single-energy-grid system, but both are options which may be considered in the coming phases of the field. When detached from a bigger grid, AEGs rely on cell building pieces that can self-advance and participate in optimal functioning when linked to a larger grid. Using the same methods, AEGs are able to integrate into different environments at will and integrate with real world environments more efficiently. For example, they can be able to do their jobs on a single cell tower rather than the cell building process at hand. While they may be very hard to make, they do not require any additional resources. The second reason you may come across AEGs is because they may have several different uses. AEGs are used to develop self-assemblers that are compatible with different technologies that use AEGs. These self-assemblers are then sold to any manufacturer or service provider that utilizes them. This article displays the key ideas and research needed in the wide fields of optimisation theory, control theory, big data analytics, and complex system theory and modelling to achieve the AEG aim. [ABSTRACT FROM AUTHOR] |
