10.25729/esr.2018.01.0010
Stennikov, V.
Melentiev Energy Systems Institute Siberian Branch of the Russian Academy of Sciences, Irkutsk, Russia
Barakhtenko, E.
Melentiev Energy Systems Institute Siberian Branch of the Russian Academy of Sciences, Irkutsk, Russia
Sokolov, D.
Melentiev Energy Systems Institute Siberian Branch of the Russian Academy of Sciences, Irkutsk, Russia
Determination of Optimal Parameters of Heating Systems Based on Advanced Information Technologies
Energy Systems Research
2018
en
2018-04-25
Journal Article
http://esrj.ru/index.php/esr/article/view/2018.01.0010
2618-9992
This paper presents a new method for the development of software to determine optimal parameters of heating systems. The method is based on the Model-Driven Engineering paradigm. The essence of this paradigm is that the software is generated on the basis of formal descriptions represented by models. This method makes it possible to automate the process of software development. The ontologies of heating systems, problems, and software are a means of representing the models. The paper proposes metaprogramming to make the software architecture flexibly adjustable to the problem of parameter optimization of a concrete heating system in the course of the problem-solving process. Metaprogramming technologies enable the development of software to change or create software components when solving the problem. The proposed method includes four stages: 1) development of a computer model of the heating system; 2) formalization of the applied problem; 3) automatic construction of the software model; 4) automatic development of the software on the basis of the model. This method underlies the SOSNA software intended for solving parameter optimization problems of heating systems. The software makes it possible to calculate large-scale systems with a complex structure with any set of nodes, sections, and circuits. The use of the software to control the expansion of heating systems will enhance their energy efficiency and cost-effectiveness. The software was applied to solve the optimal reconstruction problems of urban heating systems.
№1(1) (2018)