METHOD FOR REDISTRIBUTING ELECTRICITY IN A MICROGRID NETWORK BASED ON AN ONTOLOGICAL MODEL
DOI:
https://doi.org/10.20535/2411-2976.12025.43-53Keywords:
ontology, Microgrid, energy distribution, flexibility, scalability, semantic approachAbstract
Background. Effective management of electricity distribution in microgrid networks is a key factor in ensuring such systems' reliability, stability, and flexibility. Due to the decentralisation of energy systems and the active introduction of renewable energy sources, there is a growing need for adaptive methods of electricity redistribution that can consider dynamic changes in load and generation. Existing approaches are mostly based on rigid algorithms or centralised control, which makes it difficult to implement flexible scenarios and leads to limited adaptability. The absence of a unified knowledge representation complicates the interaction between Microgrid elements and creates obstacles to system expansion.
Objective. The purpose of this paper is to develop a method for redistributing electricity in a Microgrid using an ontological model that will provide a consistent representation of knowledge about system elements, their interconnections, constraints, and priorities. The proposed approach should facilitate context-oriented decision-making and increase the level of the power system autonomy without the need for radical changes in control schemes.
Methods. The paper analyses typical scenarios of electricity redistribution, identifies conflicts of interaction between Microgrid nodes, and proposes an ontological model that reflects the system structure, connections between sources and consumers, load priorities, and decision-making rules. The main attention is paid to the construction of a formalised knowledge base that ensures interoperability and flexibility in management.
Results. The analysis has confirmed that most existing electricity management systems have limited capabilities to adapt to dynamic changes and do not take into account the semantic relationships between system elements. The proposed ontological model allows for realisation of dynamic energy redistribution, taking into account the context and a set of factors. This ensures an increase in the reliability of the Microgrid and also contributes to a faster response to changing operating conditions.
Conclusions. The proposed method of redistributing electricity in a Microgrid based on an ontological model is a promising direction for building adaptive and intelligent energy systems. Further research is planned to be directed to the implementation of a prototype of the software control module, as well as to the expansion of the ontology to take into account the specifics of various Microgrid configurations.
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