Production rule ontology of automatized smart emergency dispatching support of the power system
DOI:
https://doi.org/10.15276/hait.02.2021.6Keywords:
Ontology, Intelligence, Trigger, Algorithm, Production, Context, Power System, Dispatcher, AutomationAbstract
The research deals with improving methods and systems of control over power systems based on intellectualization of dispatch decision support. There are results of developing a principal trigger scheme of the decision support system algorithm. The proposed model of algorithm visualization in the form of a trigger state network of the computer system provides interaction with power objects of mining and metallurgical complexes and regions. A new interpretation of components of the network trigger model is introduced. The model is interactively related to both user-operator actions and states of power system components. With that, the state of the automata model is associated with fulfillment a set of metarules to control the logical inference. There are new forms of presenting algorithms controlling knowledgebases that interact with the external environment and aggregate primitives of states, triggers and transactions of operations and generalize standard visualization languages of algorithms are proposed. This allows unification of smart systems interacting with the external environment. The authors develop models for representing knowledgebase processing algorithms interacting with power objects that combine states, triggers and transaction operations and generalize standard visualization languages of algorithms. This enables description of functioning database algorithms and their event model, which provides a reliable unification of smart systems interacting with control objects of mining and metallurgical power systems. The research solves the problem of building a knowledgebase and a software complex of the dispatch decision support system based on the data of computational experiments on the power system scheme. The research results indicate practical effectiveness of the proposed approaches and designed models