## 6 Conclusions  
The paper has presented the principal applications concerning the SGs. The use of AI-based techniques is being used extensively in SG. For example, this work has analyzed around 316 works, of which at least 115 works are based on AI. This represents 37% of the works shown, being the majority of the last decade. It has already been commented that the SG focuses on ICT, and this is demonstrated by the analysis of a large number of works focused on IA. Statistical models, linear techniques, not-linear techniques, expert systems, ANN, AI and other methods have been used in the four areas of the SGs. The area with the highest number of papers presented is \"Operation and Control\", and within this \"Enterprise Architecture\". The second area with the largest number of jobs in AI is \"Grid Planning and Design\", and within this \"Development Alternatives of the Electrical Grid of the Future\". The third area with the largest number of jobs in AI is \"Maintenance and Lifespan Management\", and within this \"Advanced Decision-Making Systems\". In last position is \"Metering\", and within this, the subarea with the most jobs in AI is \"Demand Response\". Therefore, it can be said that the AI-based techniques are of majority use in the SG, regardless of their area of interest. Initially, the AI was used for forecasting models (demand and later generation), but nowadays Ai is used for the whole compendium of services associated with the SG. It is very likely that the distribution infrastructure (and its control) does not look anything like the present when twenty years pass. This will be due to the incorporation of advanced measurement, DG and distributed storage. This will allow self-healing, QoS, cybersecurity, operate reliably and economically, etc. Operation and control, maintenance and lifespan management, grid planning and design and metering need the applications of science. The evolution of the SGs will need new developments and major efficiency. The SG needs algorithms, materials, devices and other new paradigms for its future development. The operation and precise control of new intelligent equipment, together with the architecture of communications and new protocols, allows the networks to be smarter. With this advance, the electric companies will be able to guarantee a better supply and QoS, and increase their penetration percentage of renewables in the network. The new applications should be integrated into current systems, and if possible, easily. Operation and control involve making the current network as inactive and future electrical grid. To achieve this, it is necessary to develop advanced equipment, with new communication systems that allow complete automation (transport, distribution and low voltage). New fault detection techniques are also needed to enable the integration of distributed resources. The new support tools for the operation should be integrated into the architecture of the company, becoming a new company that integrates new services. Maintenance and lifespan management require new smart signals from new equipment. In addition, the new applications of the SG will allow asset management and decision-making systems. The operation and maintenance have become a crucial task in many aspects of the SG, for example, these are essential in large renewable generation plants (mainly wind and photovoltaic systems), but also for the management and management of the transport network and distribution. The evolution of the current electricity network will allow the design and implementation of new networks of the future. These new networks will bring new development models and new functionalities. New paradigms such as microgrids will allow renewable generation sources to be integrated in a massive way, but for this, it is necessary to plan and design electrical grids in another way. Therefore, everything must evolve consistently, from the grid itself to the equipment that composes it. Perhaps the fundamental pillar of the SG is the metering.