Power construction in university mechanical equipment laboratories typically faces challenges from heavy loads and complex load types, including predominantly inductive loads from machine tool motors, resistive loads from heating devices, and occasional capacitive loads from certain control circuits. These challenges lead to issues such as unbalanced three-phase loads, low power factor, and high transient currents during equipment startup, which may affect power supply quality and even cause equipment damage. Moreover, these issues lead to persistent problems in power distribution design, including excessive redundancy that causes resource wastage and inadequate capacity that impedes scalability. To address these problems, this paper explores power distribution design methods tailored to the specific load characteristics of mechanical equipment laboratories, aiming to provide a scientific basis for optimizing power supply systems in such environments. This research develops reasonable principles and methods for power distribution design to ensure safety, cost-effectiveness, and long-term adaptability in university laboratory infrastructure.

Using the construction of the Intelligent Manufacturing Equipment and Systems Public Platform of the Academy Frontier Equipment at Xi’an Jiaotong University as a pilot project, the research began by investigating the load types, power ratings, and operating modes of various equipment. Through theoretical analysis and practical case studies, it summarized key design principles, such as scientific load calculation and reasonable equipment layout, to achieve three-phase load balancing and reasonable load capacity. Calculating power demand by simply summing the rated powers multiplied by a safety factor often results in oversized loads, making the existing power busbars incapable of meeting the demand and requiring additional transformer installations. This research shows that traditional design methods rely on extreme assumptions and overlook factors such as the low probability of simultaneous operation and the complexity of equipment usage. These oversights lead to overestimation of power demand. The root cause is an overemphasis on “absolute safety,” misinterpretation of load calculations, diverse equipment operation profiles, and unpredictable turnover. Therefore, a design concept of “balancing load distribution and optimizing calculated power” is proposed. The following measures are implemented: First, classify equipment based on load type (resistive, inductive, and capacitive), usage frequency and operational modes (continuous, intermittent, and short-term); second, employ the demand factor method to convert rated powers into calculated loads, accounting for operation probability and peak load variation; third, group equipment to balance loads across different regions, considering differences in power devices and load types.

When a similar project is initiated, the following systematic methods can be applied: ① comprehensive power resource assessment involving evaluation of infrastructure (e.g., distribution panels and busbars) to optimize utilization; ② developing detailed equipment inventory with matrices of types, power ratings, and usage characteristics; ③ balanced zoning strategies based on load type to reduce peak demand; and ④ precision load modeling using area-specific power density formulas and demand factors, which yield calculated loads substantially lower than simple power summations. These methods are applied to the Intelligent Manufacturing Equipment and Systems Public Platform, which spans an area of 3 000 m² and includes 100 sets of equipment. Approximately 600 000 RMB was saved by avoiding unnecessary transformer upgrades. Moreover, the platform supports 10 years of scalability, with current loads consistently monitored below 50 A, validating the operational efficiency of the system.

This research establishes a systematic framework for power distribution design in mechanical equipment laboratories that integrates safety, economic viability, and scalability. The proposed methods were validated through 3 years of operation in the Intelligent Manufacturing Equipment and Systems Public Platform, thereby demonstrating their efficacy in optimizing load distribution and reducing construction costs. This approach provides a valuable reference for universities undertaking similar laboratory projects, facilitating rational resource allocation and sustainable laboratory development.