Non-intrusive efficiency estimation method for energy auditing and management of in-service induction motor using bacterial foraging algorithm

TLDR

Accurate efficiency estimation of in‑service motors is crucial for energy auditing and management, yet the IEEE Standard 112 method cannot be used because it disrupts production. This study proposes a non‑intrusive method for estimating in‑service motor efficiency using a bacterial foraging algorithm. The method measures stator current, voltage, input power, stator resistance, and rotor speed, then applies the bacterial foraging algorithm to estimate equivalent circuit parameters and compute efficiency via a modified motor model, and was tested on a 5 hp motor against several optimization and measurement techniques. The results show that the method accurately and rapidly estimates motor efficiencies, making it suitable for energy audits, cost‑savings predictions, investment decisions, and online monitoring.

Abstract

Accurate efficiency estimation of in-service motor is crucial in industries for energy auditing and management. The method defined in IEEE Standard 112 cannot be used for in-service motors, because it disrupts the production process. This study presents a non-intrusive method for in-service motor efficiency estimation based on the bacterial foraging (BF) algorithm. The proposed method relies on measuring the stator current, stator voltage, input power, stator resistance and rotor speed of the in-service motor. The BF algorithm is used for evaluating the equivalent circuit parameters of the motor instead of using the no-load and locked-rotor tests. The efficiency is then estimated using a modified motor model. The proposed method has been tested on a 5 hp motor directly supplied by the grid and the results are compared with those obtained by particle swarm optimisation method, immune algorithm method, ant colony optimisation method, torque gauge method, equivalent circuit method, slip method, current method and segregated loss method. The results demonstrate that the proposed method can estimate motor efficiencies accurately and speedily. Hence, the method is suitable for conducting energy audits and management of the motor to predict cost savings and payback, to assist decisions concerning the investment of an energy efficient motor and also to integrate in an online monitoring system.