Abstract

Due to their notable share of the total energy consumption of industries, pumps hold particular significance in industrial energy audits. In industrial facilities, pumps exist in large numbers, which leads to only the pumps most critical to the process being monitored. Meanwhile, many old or poorly sized pumps may operate inefficiently without attention. To determine the energy efficiency of a pump, information on the pump’s flow rate is required. To this end, flow meters are often used to determine the flow rate produced by a pump, which can be used in determining the pump’s specific energy consumption. However, flow meters tend to be costly and impractical for some applications and are laborious for energy auditing, if no preexisting metering can be found in the audited process setup. Thus, soft sensor approaches to estimate flow rate are suggested by several authors. However, the use of model-based flow rate estimators is still uncommon, because they require detailed information on the pump characteristic curves and manual configuration of the device employing the flow rate estimator. This paper introduces a novel flow rate estimator tuned with only four variables: the nominal flow rate, head, shaft power and rotational speed of a centrifugal pump. The estimator operation is based on the expected characteristic performance curves of the centrifugal pump according to its specific speed. Due to a small number of required input parameters, and no need for manufacturer’s pump curves, the proposed estimator is easier to commission than existing solutions available both in fixed speed systems and commercial variable-speed drives. The performance and accuracy of the presented estimator are studied by comparing it with the basic QP and QH-curve-based estimation methods through simulations with four different centrifugal pumps and through measurements with two different centrifugal pumps in a test laboratory. In the experimental evaluation, the suggested estimator estimated the flow rate produced by centrifugal pump with an error of 7–15% of the nominal flow rate through a flow rate range of 60–100% of the nominal flow rate. Thus, the presented method is accurate enough to be used in continuous large-scale energy auditing, for example to highlight inefficiently running pumps from large pump populations.

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