A Mobile-based Platform for Big Load Profiles Data Analytics in Non-Advanced Metering Infrastructures

Abstract

Abstract. With the rapidly increase of electricity demand around the world due to industrialization and urbanization, this turns the availability of precise knowledge about the consumption patterns of consumers to a valuable asset for electricity providers, given the current competitive electricity market. This would allow them to provide satisfactory services in time of load peaks and to control fraud and abuse cases. Despite of this crucial necessity, this is currently very hard to achieve in many developing countries since smart meters or advanced metering infrastructures (AMIs) are not yet settled there to monitor and report energy usages. Whereas the communication and information technologies have widely emerged in such nations, allowing the enormous spread of smart devices among population. In this paper, we present mobile-based BLPDA, a novel platform for big data analytics of consumers' load profiles (LPs) in the absence of AMIs' establishment. The proposed platform utilizes mobile computing in order to collect the consumptions of consumers, build their LPs, and analyze the aggregated usages data. Thus, allowing electricity providers to have better vision for an enhanced decision making process. The experimental results emphasize the effectiveness of our platform as an adequate alternative for AMIs in developing countries with minimal cost.