Energy Efficiency is an important factor in helping to reduce organisational carbon emissions. The availability of energy data from commercial settings although not uncommon is lack luster. This is in part because of the lack of an open platform that allows easy access, deployment and processing of data. Additionally, the capture devices (smart meters) are often unreliable in transmitting data consistently; often they rely on technologies such a GSM.
This investigation uses Energy data from the University of Lincoln Estates Department in the hopes of opening their vast array of data and helping them to fill gaps in their data. The case study that we will focus on is a University campus which is comparable to most commercial environments with offices and employees. However, it also has dynamic environments which have constantly changing populaces of students (e.g. student courts and lecture theatres). Furthermore, there are large shifts in demand seasonally (e.g. deadlines) and sporadically (24 hour libraries).
“If we analyse the nature of electricity demand it is clear that it is characterized by cyclicality, seasonality and randomness.”
(Gładysz and Kuchta, 2008)
The ability to provide an open platform to collect data from smart meters can not only reduce carbon footprints but also give improved efficiency and cost savings for businesses. Encouraging data to be shared could enable greater insight into operating patterns. When this data is combined with other data sets (external or internal to the company) it can help in providing further insight into micro and macro processes.
European countries are now legally required to address energy efficiency under European Directive (Directive on the energy performance of buildings, 2002/91/EC). In the United Kingdom this leaded to the introduction of the Energy Performance Certificate (for residential properties) ( The Energy Performance of Buildings (Certificates and Inspections) (England and Wales) Regulations. 2007)and the Display Energy Certificate(DEC) (for operational properties). There are several approaches the various stakeholders are taking to address energy consumption e.g. from International Trade Agreements to Carbon Emission Taxes
This project alone is not to solve all the problems posed by energy efficiency and climate change but to provide a platform for future work to be undertaken to address these issues. The availability of a restful system which can be implemented across multiple organisations means that an easier access to data for research and accountability. The application of accurate retro filling and predictive modelling will further enhance future work as they will have a more reliable and complete set of data.
This project combines several different emerging technological fields these include Big Data, Internet of Things, Predictive Modelling, Cloud Computing and Machine learning. Which as can been seen in Figure 1 has seen a considerable increase in popularity in recent years.
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