Abstract
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.
Highlights
The novel smart grid concept is revolutionizing the electricity grid infrastructure, and incentivizing awareness of a more sustainable energy utilization: “green” solutions for residential and commercial buildings have been investigated with the aim of increasing the diffusion of renewable energy sources and reducing carbon footprints [1,2]
The “smart building” paradigm [4,5] aims at improving the energy efficiency and occupant’s quality of living by integrating intelligent control mechanisms enabled by information and communication technologies (ICT)
In our preliminary work [11], we propose a smart office architecture in which the energy usage of an office equipped with a photovoltaic plant, a storage bank and a set of loads is controlled by means of an energy manager, which makes decisions based on energy production and consumption forecasting algorithms and exploits the following peculiarities of the smart office ecosystem:
Summary
The novel smart grid concept is revolutionizing the electricity grid infrastructure, and incentivizing awareness of a more sustainable energy utilization: “green” solutions for residential and commercial buildings have been investigated with the aim of increasing the diffusion of renewable energy sources and reducing carbon footprints [1,2]. We present a novel algorithm by which the EMS can minimize the energy expenses or maximize its ability to work in islanded mode, i.e., without injecting nor absorbing energy into/from the grid The latter objective could be adopted in case the DSO notifies the EMS of an ongoing emergency (e.g., a high probability of outages due to temporary faults or malfunctions in the power grid), in order to privilege a grid-detached operational regime. To achieve these objectives, the EMS solves a mixed-integer linear program (MILP) at regular intervals, taking as input both the actual energy production/consumption data and forecasts about the future production/consumption patterns.
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