This review develops a cost-benefit framework for motor system optimization, indicating significant energy and non-energy savings.
Industrial and commercial motor-driven systems account for a large share of electricity consumption and represent a major opportunity for energy savings, cost reduction, and decarbonization. However, investment decisions for motor system optimization are often based mainly on direct electricity savings, while non-energy benefits such as reduced downtime, lower maintenance costs, improved reliability, higher productivity, enhanced safety, and reduced noise are frequently omitted or treated qualitatively. This study aims to develop a structured cost–benefit evaluation framework that integrates energy benefits and non-energy benefits to support motor system optimization and investment decisions. The methodology combines a literature review, case-study synthesis, classification of motor-system optimization technologies, development of a non-energy benefit monetization index, subsector–technology weighting factors, conservative scaling factors, and sensitivity analysis. The proposed framework is applied across industrial and commercial subsectors and technologies, including premium-efficiency motors, variable speed drives, synchronous reluctance motors, and permanent-magnet motor systems. The results show that motor system optimization can deliver electricity savings, commonly exceeding 30% in applications, particularly when system-level measures such as variable speed drives and improved controls are implemented. When non-energy benefits are included under conservative assumptions, total project benefits increase substantially and estimated payback periods be reduced on average by approximately 50%, considering a large variety of case-studies. The findings demonstrate that excluding non-energy benefits can significantly underestimate the economic attractiveness of motor system optimization. The proposed framework provides decision-makers with an approach for comparing technology options, adapting benefit weights to site-specific conditions, and prioritizing investments based on combined energy, operational, financial, and environmental benefits.
No takes yet. Share an insight, caveat, or question.
Almeida et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: