Development of an Intelligent Energy Management method for Continuous Manufacturing Plants

Abstract

Relevance: Continuous manufacturing industries—such as metallurgy, chemical, cement, and food processing—represent the largest consumers of electrical energy. In Uzbekistan, industrial energy intensity is 1.8–2.2 times higher than the global average, mainly due to outdated equipment and inefficient reactive power compensation. Under the Green Energy Strategy 2030, Uzbekistan aims to reduce industrial energy intensity by 35% and implement digital, intelligent energy management systems. Therefore, developing a complex energy management architecture for continuous manufacturing plants has become a critical scientific and practical task.

Objective: The study aims to develop a comprehensive energy management architecture that optimizes electricity usage, ensures production stability, and reduces total energy costs in continuous manufacturing enterprises of Uzbekistan.

Methods: Real-time data from SCADA systems were analyzed for multiple subsystems (melting, casting, machining, packaging, auxiliary). Active power was calculated as:  and total consumption as: . The optimization model minimized total energy costs under production and power-quality constraints:

Results: Implementation of the proposed architecture reduced overall energy consumption by 3–5%, improved power factor to 0.95–0.96, and stabilized production performance. The system’s modular design allows integration with existing SCADA and AI-based predictive systems, supporting Uzbekistan’s transition to a sustainable, energy-efficient industrial economy.