Abstract:The Smart Meter (SM) is an essential tool for successful balancing the demand-offer energy curve. It allows the linking of the consumption and production measurements with the time information and the customer's identity, enabling the substitution of flat-price billing with smarter solutions, such as Time-of-Use or Real-Time Pricing. In addition to sending data to the energy operators for billing and monitoring purposes, Smart Meters must be able to send the same data to customer devices in near-real-time conditions, enabling new services such as instant energy awareness and home automation. In this article, we review the ongoing situation in Europe regarding real-time services for the final customers. Then, we review the architectural and technological options that have been considered for the roll-out phase of the Italian second generation of Smart Meters. Finally, we identify a collection of use cases, along with their functional and performance requirements, and discuss what architectures and communications technologies can meet these requirements.

Abstract:The proposed framework enables innovative power management in smart campuses, integrating local renewable energy sources, battery banks and controllable loads and supporting Demand Response interactions with the electricity grid operators. The paper describes each system component: the Energy Management System responsible for power usage scheduling, the telecommunication infrastructure in charge of data exchanging and the integrated data repository devoted to information storage. We also discuss the relevant use cases and validate the framework in a few deployed demonstrators.

The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart building, enabling it to maximize the self-consumption of photovoltaic electricity and to participate in the energy market, thus taking advantage of time-variable tariffs to achieve economic savings. This paper proposes an energy management infrastructure specifically tailored for a smart office building, which relies on measured data and on forecasting algorithms to predict the future patterns of both local energy generation and power loads. The performance is compared to the optimal energy usage scheduling, which would be obtained assuming the exact knowledge of the future energy production and consumption trends, showing gaps below 10% with respect to the optimum.

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Abstract-Low voltage, in-home power-line communications (PLC) networks allow direct communication between smart meters (SM) and in-home devices (IHD). In order to minimize security issues, in many deployment scenarios transmission takes place only towards the IHD to display consumption data, with no backwards channel. As a result, channel estimation is difficult and it is necessary to use robust transmission techniques to mitigate the effect of the impulsive noise within the PLC channel. Performance of such system must be evaluated by taking into account realistic interference and channel models for a broad range of configurations. In this work we focus on performance in terms of bit error rate (BER) of a narrowband PLC (NB-PLC) operating in the CENELEC-C band (125-140 kHz) taking into account realistic noise models. Our system is based on binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulation.