ENERGY-EFFICIENT AUTOMATIC LIGHTING CONTROL SYSTEM FOR EDUCATIONAL INSTITUTIONS BASED ON MULTI-OBJECTIVE OPTIMIZATION METHOD

Abstract

The work is devoted to solving the urgent problem of increasing the energy efficiency of artificial lighting systems in educational institutions. In modern schools and universities, lighting accounts for a significant share of total energy consumption, while ensuring a high-quality lighting environment is critically important for the health and performance of students. The aim of the work is to develop and study a centralized control method that effectively combines artificial and natural light, minimizing energy losses while complying with sanitary standards. The authors analyzed the shortcomings of traditional decentralized control systems based on local PID controllers. It was shown that such systems, due to the lack of coordination between light sources, are prone to overestimating the level of illumination to guarantee standards at the worst points. To solve this problem, a mathematical model of the light field in a classroom with combined lighting was developed. The control problem is formulated as a multi-criteria optimization problem. The proposed approach uses the method of approximation to a utopian point in the space of criteria to find a compromise between three conflicting criteria: total power consumption, light distribution uniformity and tracking error.

Numerical simulation was carried out for a typical auditorium with a window under conditions of intense insolation. Comparative analysis showed that the proposed automatic control system reduces electricity consumption from 114.56 W (baseline PID model) to 103.58 W. Energy savings amounted to 9.58%. The system demonstrated higher control accuracy: the average absolute error decreased from 303.6 lux to 269.5 lux. In contrast to the baseline model, which maintained an excess minimum illumination of 474.1 lux, the optimized system reached a level of exactly 450.0 lux, operating at the limit of the permissible area. This proves that the algorithm intelligently adapts the light flux, dimming the lamps near the window and compensating for the lack of light only in the depths of the room.

The implementation of the developed algorithms in building control systems allows achieving significant energy savings in educational buildings without upgrading power equipment, solely through software optimization of control modes.