A Decision Framework for Broker Selection in Smart Grids

Trust and reputation are critical factors for successful cooperative relationships between broker agents and producers/consumers in "SmartGrids" electricity markets. In this paper, we present SmartRate, a trust and reputation-based decision framework for Smart Grids, based on the available ratings provided by other customers. This model considers multiple trust factors associated with the broker and the preferences of customers for each of these factors. Our previous work has shown the importance of learning the behavior of the agent who is providing reports or rates in selecting trustworthy partners. SmartRate uses direct interactions with brokers to learn the rating behavior of customers. We define a multi-attribute utility function for broker selection and show how learning customers' rating behaviors helps to increase a decision maker's utility, which leads to an increase in customer satisfaction. We evaluate this framework by simulating a market based on real-world data. Our results show that learning the characteristics of a rating population helps to interpret and personalize the rates, which results in better decision making and an increase in customer satisfaction.