Energy disaggregation using a single voltage sensor

Continuous and detailed energy monitoring is essential to ensure the energy efficient operation of complex systems, for instance, buildings. Energy efficiency is becoming a relevant topic in the last years because of the growing concerns on sustainability and the will of reducing the energetic costs. The idea behind this Master’s thesis is a novel energy monitoring solution that with a single sensor enables the monitoring of energy consumption per each single device in an electrical group.The proposed method enables an extremely simple energy monitoring since it does not require monitoring the overall current. All other existing methods need to have access to the electrical current to estimate correctly the power consumption of the different devices. The current meter has to be clamped around a wire inside the electrical cabinet and its installation is a non-trivial task. The main advantage of this novel method is that the unit of sensing can be installed by any user in any socket. Our method monitors only the voltage signal and maps the voltage variations to the power jumps caused by the different device

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

A principle based system architecture framework applied for defining, modeling & designing next generation smart grid systems

Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 81).A strong and growing desire exists, throughout society, to consume electricity from clean and renewable energy sources, such as solar, wind, biomass, geothermal, and others. Due to the intermittent and variable nature of electricity from these sources, our current electricity grid is incapable of collecting, transmitting, and distributing this energy effectively. The "Smart Grid" is a term which has come to represent this 'next generation' grid, capable of delivering, not only environmental benefits, but also key economic, reliability and energy security benefits as well. Due to the high complexity of the electricity grid, a principle based System Architecture framework is presented as a tool for analyzing, defining, and outlining potential pathways for infrastructure transformation. Through applying this framework to the Smart Grid, beneficiaries and stakeholders are identified, upstream and downstream influences on design are analyzed, and a succinct outline of benefits and functions is produced. The first phase of grid transformation is establishing a robust communications and measurement network. This network will enable customer participation and increase energy efficiency through smart metering, real time pricing, and demand response programs. As penetration of renewables increases, the high variability and uncontrollability of additional energy sources will cause significant operation and control challenges. To mitigate this variability reserve margins will be adjusted and grid scale energy storage (such as compressed air, flow batteries, and plugin hybrid electric vehicles or PHEV's) will begin to be introduced. Achieving over 15% renewable energy penetration marks the second phase of transformation. The third phase is enabling mass adoption, whereby over 40% of our energy will come from renewable sources. This level of penetration will only be achieved through fast supply and demand balancing controls and large scale storage. Robust modeling must be developed to test various portfolio configurations.by Gregory Sachs.S.M.in Engineering and Managemen