Autonomous Control and Parameter Optimization for Electrolytic Aluminum Loads Participating in Primary Frequency Regulation Ancillary Services

Abstract

Electrolytic aluminum (EAL) loads, with their large capacities and fast active power regulation capability, are promising providers of primary frequency regulation (PFR) ancillary services. However, their practical participation remains limited by the incompatibility between existing industrial control systems and PFR requirements, as well as by production constraints. This paper proposes an autonomous PFR control and parameter optimization framework that accounts for net economic benefit and production safety. A local frequency feedback loop is integrated into the existing industrial current control system, enabling EAL loads to respond autonomously to frequency deviations. An electrical, thermal, and material coupled dynamic model is established to characterize key production states, and production safety constraints are quantitatively mapped into energy boundaries applicable to PFR control. Based on these boundaries, a multi-objective optimization model determines the frequency deadband and droop coefficient by considering net economic benefit and production risk. The resulting Pareto optimal parameter set enables aluminum smelters to determine PFR control parameters according to their operating requirements and risk preferences. Case studies verify that the proposed framework enables autonomous and economically beneficial participation in PFR ancillary services while maintaining production safety.