A zero-energy building can be defined as a building with almost zero net energy consumption. This means that the total amount of energy spent in the building in a year is approximately equal to the amount of energy generated on the site by renewables or cogeneration. A smart meter system is very important for these buildings in order to manage and control the energy flows. In fact, the smart meter system monitors, supervises, visualizes and stores the energy generated and the energy consumption in the building providing the information to the users. Typically, it consists in a complex architecture with a central server with a supervisory system. The scope of the present work is to propose an innovative approach for the implementation of smart metering systems in zero-energy buildings and a practical methodology to classify the systems. The proposed classification rates the system performance via a set of weighted indicators-according to the positioning of meters, measured data, system architecture, data visualization and monitored loads-, then calculates an overall grade. © 2015 IEEE.
Classification of smart metering systems for zero-energy buildings
Di Pietra, B.
2015-01-01
Abstract
A zero-energy building can be defined as a building with almost zero net energy consumption. This means that the total amount of energy spent in the building in a year is approximately equal to the amount of energy generated on the site by renewables or cogeneration. A smart meter system is very important for these buildings in order to manage and control the energy flows. In fact, the smart meter system monitors, supervises, visualizes and stores the energy generated and the energy consumption in the building providing the information to the users. Typically, it consists in a complex architecture with a central server with a supervisory system. The scope of the present work is to propose an innovative approach for the implementation of smart metering systems in zero-energy buildings and a practical methodology to classify the systems. The proposed classification rates the system performance via a set of weighted indicators-according to the positioning of meters, measured data, system architecture, data visualization and monitored loads-, then calculates an overall grade. © 2015 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.