Supporting government’s actions to reach energy efficiency : the motor replacement problem

Abstract

Considering current policies and trends, world energy consumption will increase by 8% by 2040. In Brazil, the industrial sector consumes approximately 40% of all national electrical power, and the complexity of energy industrial system demands appropriate energy management. To address this problem, the government with its energy efficiency law, established minimum energy performance standard for motors manufactured since December 2009 to ensure adequate energy consumption. However, with current mechanisms, companies continue to practice motor rewinding, increasing their lifespan and reducing the efficiency, consequently increasing the energy costs and emission of polluting gases into the atmosphere. The public policies to encourage the motors replacement are unattractive and there is low participation of companies, making it difficult for the government to achieve its energy efficiency goals. Moreover, companies need suitable tools to support their strategies to meet energy efficiency regulations and promote energy gains. In this way, this thesis proposes to build models to support energy efficiency decisions with regard to motor replacement projects. Two models were developed, the first, based on the FITradeoff method, seeks to support the companies to prioritize their non-efficient motors and build a replacement plan in the face of conflicting criteria, budget constraints and limited available data. The second one is based on ACUTA method, an holistic approach, different from classic negotiation direct rating models, used to support a negotiation process between the power utilities and companies, in order to align current incentive options of the Public Calls for motor replacement with their preferences, making the options more attractive to increase companies participation on energy efficiency projects. As for the applicability of the models, both were applied in real-life situations through two different case studies and were able to deal with conflicting criteria against a range of options. They deal with the data inaccuracy, are agile, interactive and flexible; also, they reduced the cognitive effort of the decision-maker/negotiator while conducting the analytical process by achieving robust results with scarce data. The results were satisfactory and showed an adequate direction to promote energy efficiency in organizations.