The energy policy approach is carrying out a long-time renewal process of the electric and in general energy framework. The energy spent in commercial, residential, and institutional buildings is a great amount (in EU is estimated about 40% of total energy consumption and about 90% in high-density urban areas) [1]. The general encouragement of the rational use of energy, also for residential users, introduced the new approach of the nearly zero-energy buildings (NZEBs) by the European energy performance of buildings directive (EPBD) [3]. NZEB means a building that has a very high energy performance, as determined in accordance with Annex I of Directive [3]. The nearly zero or very low amount of energy required should be covered to a very significant extent by energy from renewable sources, favoring energy from renewable sources produced on-site or nearby. Let us note that the major appliances (both white and brown goods) and other electric loads not fixed (equipment supplied by plugs) are not taken into account in the NZEB qualification. The EPBD requires all new buildings to be NZEBs by the end of 2020 (public buildings must be NZEBs by 2018). A building may reach the NZEB qualification through a complex of efficient technical building systems (TBSs), building automation control system (BACS), and renewable sources, besides a very high energy performance given by envelope insulation and other passive measures [4] . The TBSs that must be provided vary with the type of building, but will generally include a building electric service and power distribution system to serve the loads, a heating, ventilation, and air conditioning (HVAC) system, a domestic hot water (DHW) system, electronic safety and security systems, and a communication system (ICT). The extremely low amount of energy that NZEBs require (energy spent ES2) comes mostly from renewable local sources (energy generated ERES) like: photovoltaic (PV), ground-source heat pumps (GSHP) or thermal solar systems

No abstract

Contrary to expectations, the development of smart (mini) grids is slow. Due to drastic improvements in innovative technologies, the reasons are not strictly technical but the problem mainly lies in regulatory barriers. The current business models are centric to utilities rather than customers. Net metering is a key enabling factor for smart (mini) grids. This paper addresses the economic benefits of net metering for individual residential customers. Energy demand for the individual apartments and common areas is calculated using the daily energy consumption behavior of occupants for typical days of each month of the year. Photovoltaic generation is estimated via PVGIS for a residential building in Italy. The proposed net metering scheme is applied on the aggregate energy demand of selected building without any modification in the current energy billing and net metering tariffs. Results show the noticeable difference in the savings of individual apartments

Building Automation Systems BAS are the key to\ud improve the energy performance of buildings and the occupants’\ud comfort. There is a need to build a knowledge base on the matter\ud and to grow suitable algorithms for a smart management of the\ud “intelligent buildings”. Indeed, fuzzy logic is a valuable\ud candidate for developing robust algorithms. The scope of the\ud present work is to validate a fuzzy logic approach able to\ud optimize the level of energy performance and comfort in an\ud office space, taking advantage of BAS and solar energy. In BAS,\ud dynamic elements (e.g. dynamic façade and luminaires) can\ud exploit daylight and solar gain; on the condition that wellprogrammed\ud integrated multicriteria decision making methods\ud are used. In this paper, a virtual model of a Smart Office Room\ud SOR, equipped with dynamic shading, lighting and air\ud conditioning control system, was studied and different scenarios\ud were considered: i) control versus no-control; ii) economy versus\ud comfort mode; iii) fluorescent versus LED; iv) dimming versus\ud switching. Both economy and comfort mode showed a better\ud energy performance than non-controlled scenarios. In\ud conclusion, the proposed model is a valuable tool to optimize\ud comfort features and energy demand as a whole