Energy Disaggregation for SMEs using Recurrence Quantification Analysis

Energy disaggregation determines the energy consumption of individual appliances from the total demand signal, which is recorded using a single monitoring device. There are varied approaches to this problem, which are applied to different settings. Here, we focus on small and medium enterprises (SMEs) and explore useful applications for energy disaggregation from the perspective of SMEs. More precisely, we use recurrence quantification analysis (RQA) of the aggregate and the individual device signals to create a two-dimensional map, which is an outlined region in a reduced information space that corresponds to ‘normal’ energy demand. Then, this map is used to monitor and control future energy consumption within the example business so to improve their energy efficiency practices. In particular, our proposed method is shown to detect when an appliance may be faulty and if an unexpected, additional device is in use

Optimising Parameters in Recurrence Quantification Analysis of Smart Energy Systems

Recurrence Quantification Analysis (RQA) can help to detect significant events and phase transitions of a dynamical system, but choosing a suitable set of parameters is crucial for the success. From recurrence plots different RQA variables can be obtained and analysed. Currently, most of the methods for RQA radius optimisation are focusing on a single RQA variable. In this work we are proposing two new methods for radius optimisation that look for an optimum in the higher dimensional space of the RQA variables, therefore synchronously optimising across several variables. We illustrate our approach using two case studies: a well known Lorenz dynamical system, and a time-series obtained from monitoring energy consumption of a small enterprise. Our case studies show that both methods result in plausible values and can be used to analyse energy data

Investigating Robustness of Energy Management Maps for SMEs

Using the data from three small businesses, we are investigating robustness of the recently proposed Recurrence Quantitive Analysis (RQA) based method for energy management of small and medium enterprises. The method consists of two phases, the training phase where the map or maps of ‘usual’ behaviour is obtained, and the operational phase where the new data is tested against the existing map(s). We measure how the output changes when there is a small change in input, with respect to the sampling rate, missing data and noise. Our results over three qualitatively different datasets show that the method is relatively robust and can be used for different SMEs

Energy Data Analytics for Smart Meter Data

The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal

Resilience of large investments and critical infrastructures in Europe to climate change

This technical report describes the key findings, methodological aspects and underlying assumptions and limitations of the research activities undertaken by the JRC in the CCMFF project financed by DG CLIMA. The project provides the first comprehensive multi-hazard multi-sector risk assessment for Europe under climate change and identifies the most vulnerable and impacted regions in Europe throughout the 21st century. It significantly contributes to a better understanding and awareness of hazard impacts that is crucial for the management of future climate risks.JRC.H.7-Climate Risk Managemen

Applying the Kaizen in Africa

At present, how to develop industries is a burning issue in Africa, where population growth remains high and economic development has thus far failed to provide sufficient jobs for many, especially young people and women. The creation of productive jobs through industrial development ought to be a central issue in steering economic activity across the continent. The authors of this book, consisting of two development economists and five practitioners, argue that the adoption of Kaizen management practices, which originated in Japan and have become widely used by manufacturers in advanced and emerging economies, is decisively the most effective first step for industrial development in Africa. This open access book discusses what Kaizen management is, why it is applicable to Africa, and why it can provide Africa with a springboard for sustainable economic growth and employment generation