Research on the Application of Real-Time Optimization Algorithm in Improving the Intelligent Energy Consumption Control System of Elevator Transportation Efficiency

This study focuses on improving the operating efficiency and intelligent energy consumption control of elevator systems, and cleverly integrates the global optimization technology of simulated annealing algorithm. The core goal of this framework is to improve the elevator scheduling strategy, to effectively reduce energy consumption while ensuring efficient transportation. For the complex scenario of multi-elevator coordinated scheduling, the simulated annealing algorithm demonstrates its excellent ability in global search and solution. To rigorously verify the practicality and effectiveness of the proposed algorithm, this study constructed a detailed mathematical model of elevator operation and conducted comprehensive and in-depth experimental verification in the MATLAB simulation environment. The experimental results strongly confirm that compared with the traditional scheduling algorithm, the system designed in this study successfully achieved significant energy consumption reduction based on maintaining or even optimizing the elevator transportation efficiency. Specifically, under the set experimental conditions, compared with the traditional control system, this system achieved about 15.3% energy saving and about 12.7% transportation time optimization. Through in-depth analysis of a large amount of experimental data, people further confirmed that the simulated annealing algorithm not only performs well in solving the elevator scheduling problem, but also has good stability and convergence characteristics. The intelligent control module embedded in this system can keenly perceive the dynamic changes in floor demand and adjust the elevator operation strategy in real time, thereby achieving the effect of dynamic energy consumption optimization.