Abstract
The Advanced Metering Infrastructure (AMI) data represent a source of information in real time not only about electricity consumption but also as an indicator of other social, demographic, and economic dynamics within a city. This paper presents a Data Analytics/Big Data framework applied to AMI data as a tool to leverage the potential of this data within the applications in a Smart City. The framework includes three fundamental aspects. First, the architectural view places AMI within the Smart Grids Architecture Model-SGAM. Second, the methodological view describes the transformation of raw data into knowledge represented by the DIKW hierarchy and the NIST Big Data interoperability model. Finally, a binding element between the two views is represented by human expertise and skills to obtain a deeper understanding of the results and transform knowledge into wisdom. Our new view faces the challenges arriving in energy markets by adding a binding element that gives support for optimal and efficient decision-making. To show how our framework works, we developed a case study. The case implements each component of the framework for a load forecasting application in a Colombian Retail Electricity Provider (REP). The MAPE for some of the REP’s markets was less than . In addition, the case shows the effect of the binding element as it raises new development alternatives and becomes a feedback mechanism for more assertive decision making.
Highlights
One of the pillars of Smart Cities is the intensive use of information-based technologies.big data and data analytics have become robust tools that support the development of applications for actors involved in them
Advanced Metering Infrastructure (AMI) data represent a source of information in real time on electricity consumption and potentially on population behaviors, such as concentrations of people, population migration, demographic trends, and economic changes in various sectors of the population, among others [1]
We focused on the electricity consumption data analysis from smart meters in London from 2011 to 2014
Summary
One of the pillars of Smart Cities is the intensive use of information-based technologies.big data and data analytics have become robust tools that support the development of applications for actors involved in them. One of the most important actors is Smart Grids, which enable data harvesting to implement an evolved and more efficient electrical network. Adopting Advanced Metering Infrastructure (AMI) is geared toward promoting tools available to quantify and measure the energy flow throughout the grid. This infrastructure acts to provide information to the utility but it enables the customer as a stakeholder in the energy value chain. AMI data represent a source of information in real time on electricity consumption and potentially on population behaviors, such as concentrations of people, population migration, demographic trends, and economic changes in various sectors of the population, among others [1]
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