Table of Contents
Improving the energy efficiency of the economy is a complex problem, the solution of which involves the development and implementation of a number of system solutions, at the level of both a country, a region and separate enterprises. Development of an enterprise multi-level energy efficiency management system is an important tool for improving the energy efficiency of an enterprise. The purpose of the study is to develop and improve models, methods and synthesis of data collection and processing tools of an enterprise multi-level energy efficiency management system with high technical and economic characteristics. The theory of Petri nets and their expansion is used for building functional models of an enterprise multi-level energy efficiency management system, the theory of solving the problems of multi-criteria optimization — for selection of an element base, methods of neural network technologies — for synthesis of intellectual data processing tools, the theory of hardware and software design for synthesis of information technology elements, and the methods of object-oriented approach are used in the process of software development. The method of calculating the signal of postsynaptic excitation of neural elements in artificial neural networks has been improved, which is based on parallel tabular-algorithmic calculation of scalar product with the use of two or more tables and reduces the time of data processing. The results of the synthesis of a basic element consisting of a microcontroller, temperature sensor, heater and communication module are given. 284 alternatives were generated, from which a variant with a higher value of the target function was selected. In conclusion, a simulation model of the system of automated synthesis of elements of the regional energy management system is developed, which uses the free Octave environment and allows to examine and check the operation of the method of selecting the element base and synthesis of components of the enterprise technological process energy efficiency management.
Keywords: energy efficiency; management system; neural network; algorithm; dynamic analysis