Optimal redistribution of production load as a method for minimizing electricity consumption in an industrial enterprise

Abstract

Relevance: for industrial enterprises, reducing electricity consumption directly by limiting the operation of major electrical loads is not always permissible, as it may disrupt the technological process and reduce productivity. In this regard, a rational approach to management is the optimal redistribution of production and the corresponding electrical load among technological units while maintaining the specified production output. To address this task, it is necessary to establish a quantitative relationship between the productivity of the units and the corresponding electrical energy consumption, while also taking technological and electrical constraints into account.

Aim: formation of a mathematical model for the optimal redistribution of the production load of an industrial enterprise, ensuring the minimization of total electricity consumption while maintaining the specified production output and complying with established technological constraints.

Methods: the study employs mathematical formalization of the production-energy system, representation of specific electricity consumption as a function of production output, exponential approximation of the energy characteristics of production units, the Lagrange multiplier method, and stationarity conditions to determine the optimal distribution of the production load. When active constraints are present, the production load is fixed at the corresponding technological boundary, while the remaining portion of the load is redistributed among the other units.

Results: a mathematical formulation of the problem of minimizing total electricity consumption while maintaining the specified total production output was obtained. The calculation was performed for three production lines with a total production volume of 3,000 t and an allowable productivity range of 850–1,150 t for each line. In the initial mode, the load was distributed evenly: 1,000 + 1,000 + 1,000 = 3,000 t. As a result of the optimization, the distribution obtained was 1,140 + 850 + 1,010 = 3,000 t. At the same time, total electricity consumption decreased from 2,797,136 to 2,743,655 kWh, with an absolute reduction of 53,481 kWh.