Flowchart for Controlling the Normalization and Optimization of Electrical Energy Consumption in Industrial Enterprises

Abstract

Relevance: At present, the efficient and rational use of electrical energy in industrial enterprises, reduction of energy consumption, and improvement of the energy efficiency of production processes are among the important priorities. This issue is particularly relevant for enterprises with continuous production processes, where high electricity consumption and the presence of numerous technological, energy, and operational factors make accurate energy consumption normalization more challenging. In existing normalization approaches, insufficient consideration of the interrelationships among these factors may lead to errors in calculation results. Therefore, the determination of specific electricity consumption using mathematical and statistical methods, identification of the main influencing factors, and management of energy consumption through modern automated systems represent an important and relevant research problem.

Aim: o develop a scientifically based mathematical model for normalizing electricity consumption and determining specific electricity consumption in industrial enterprises, as well as to propose a control algorithm for optimizing energy consumption.

Methods: The study employs methods of mathematical statistics, correlation and multiple regression analysis, the least squares method, and the Fisher criterion. In addition, a real-time monitoring and control algorithm based on Smart Meter, ENHAT, and SCADA systems has been developed.

Results: The main factors having the greatest influence on electricity consumption were identified as the duration of operation under current, furnace downtime, and melting mass. The adequacy of the developed model was confirmed using the Fisher criterion, while the average deviation between the actual and calculated values was 1.9%. The proposed control algorithm makes it possible to reduce electricity consumption by up to 3–5%.