Utilities and electricity retailers can benefit from the introduction of smart meter technology through process and service innovation. In order to offer customer specific services, smart meter mass data has to be analyzed. In the article we show how to integrate cluster analysis in a business Intelligence environment and apply cluster analysis to real smart meter data to identify detailed customer clusters.
The authors present a mathematical model for Service Value Networks (SVNs) describing the main components and their interdependencies. To coordinate distributed activities in SVNs, they present a scalable multidimensional auction mechanism that enables the allocation and pricing of complex services. The mechanism and its bidding language support the multidimensional description of QoS attributes, their (semantic) aggregation and enforcement. It is analytically shown that the mechanism is incentive compatible with respect to all dimensions of service providers' bids, i.e. truth-revelation of QoS attributes and private valuations is an equilibrium in weakly dominant strategies. Based on these results, the authors numerically analyze strategic behavior of participating service providers regarding possible collusion strategies.
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