Web-based decision-support system methodology for smart provision of adaptive digital energy services over cloud technologies

Energy information systems, which manage energy consumptions over internet, have been evolving over the past decade and can be considered as a part of a specialised sequential decision process, regarding the provision of personalised energy services to the community. The aim of this study is to develop and present an innovative decision-support system and cloud computing software methodology that brings together energy consultants, consumers, energy services procedures and modern web interoperable technologies. The authors propose a web-based knowledge system, using distributed cloud architecture and metering grids over ADSL broadband connections. By using some clustering algorithms and a web middleware, energy profiles over time are analysed and observed. The resulting clusters and centroids are projected and statistically analysed over time, producing a centroid-locus. Hypercube topology was used for efficient data management and software agent-based parallel analysis. The system operates efficiently on a multi-tier cloud-based middleware that generates in real-time using various service software components to the end consumers. The case study on real Greek energy measurements, for the first time in Greece, indicated a compact and efficient distributed procedure that could analyse and produce adaptive personalised information services.