В. Стефанова-Стоянова, К. Стоянов. Същност, свойства и предимства на интелигентните разпределителни енeргийни мрежи със съхранение на електрическа енергия

Статията е 3 от 8 в списание АВТОМАТИКА И ИНФОРМАТИКА 1-2, 2020 г.


Key Words: Smart Grid; distributed grid networks; intelligent management; energy storage; microgrid; ICT; smart home; smart sities.

Abstract. In the future, the methods and technical means for intelligent control of final energy consumption by economic criteria in real time, based on the integration of electricity and information networks, will become a priority for the construction and operation of Smart Energy Networks (SMART GRIDS), i.e. Energy Internet. Thus, energy and information processes in micro-networks must be considered as interconnected. Electricity storage is a key element of future smart distributed energy networks. For energy companies, the key pursued goals for the development of Smart Grid technologies are: reduction of energy losses; increasing the timeliness and completeness of payment for consumed energy resources; control of unevenness of the electric load schedule; improving the efficiency of asset management of energy companies; improving the quality of the integration of renewable and distributed generation facilities into the power system; improving the reliability of the energy system in the event of emergencies; improving the visualization of energy infrastructure facilities. The key tasks to be solved by energy consumers in the implementation of Smart Grid technologies are: improving consumer access to energy infrastructure; improving the reliability of power supply to all categories of consumers; improving the quality of energy resources; creation of a modern interface for interaction between energy consumers and its suppliers; the opportunity for the consumer to act as a full participant in the energy market; enhanced opportunities for consumers to manage energy consumption and reduce the level of payments for consumed energy resources. Governments and regulators of the energy industry are striving to achieve the following goals through the development of Smart Grid technologies: increasing the level of satisfaction of energy consumers with the quality and cost of energy supply; ensuring a stable economic position of enterprises in the energy industry; ensuring the modernization of fixed assets of the energy industry without a significant increase in tariffs. From the presented information it can be concluded that Smart-Grid is a system that is able to self-monitor and provide reports for all participants in the network (its status, needs, etc.) and complete information about the electricity generated and transmitted in every aspect: efficiency, losses or economic benefits; This is especially important for liberalized electricity markets, where trade is hour-ahead. In this way, the smart system builds a load profile of each user and can accurately redistribute prepaid energy from exchanges. The surplus can be accumulated in a storage battery module or in heat energy in the consumers’ boilers, depending on what the consumer or the consumer group has. In case of lack of (requested) energy, when the consumption has to be limited, the system has variants of strategy in which it either stops powerful consumers, without special significance (eg electric water heaters) or switches consumers to energy storage, until the next period/hour, thus the system includes as an energy generator the accumulator unit for storage of electricity and delivers in the network the insufficient amount of energy, ie. this user is active, i.e. it consumes and produces energy. This would reduce the need to maintain a cold reserve and make the energy produced cheaper. The authors study the behavior of a real SG system developed by them, have a lake of data on its operation for several years and prepare a patent solution for cheap home smart composite batteries. The concept of using smart controllers as perceptrons – elements of neural networks, in which SG can be trained and respond autonomously as effectively as possible, is also the author’s. The more modern and up-to-date perspective that the authors apply is to use neural network technology and machine learning to predict consumer behavior and energy generation in generating capacity, and to develop a strategy for the use of storage capacity (energy storage) as generating ones in order to balance the networks and use the cheapest source of electricity for a given period. It is also possible to apply purely economic approaches such as clearing, in the supplier-consumer relationship, consumer-consumer, many users to supplier. Thus, networks of pure distribution, if they have elements of smart grid, have energy storage capacity, can become highly efficient generating capacity to provide third parties (consumers, which can be entire networks) capacity, which far exceed their own consumption, but this will be the subject of a separate article by the authors.

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